Author: chromeder


  • The Psychology of Basketball (Part 1 – Scoring Blindness and Variance)

    The Psychology of Basketball (Part 1 – Scoring Blindness and Variance)

    Basketball is one of the most divisive sports in how its followers interpret the actions and results of the games. Enough of a mixture of ambiguity and clarity exists that allows viewers to, depending on their psychological tendencies, to either hold very assured or very doubtful opinions. Although the following is not a trend of any large population, in my own experience, I’ve frequently felt less confidence in my assertions as the quality of my research on a particular topic increases. This isn’t a knock on any type of analytical method; rather, over time, as I’ve learned more and more as to what information is worthwhile and which conventions aren’t, the insurmountable number of hindrances that prevent “correct” conclusions becomes more and more obvious. That’s why, without a proper framework to assess certain aspects of the game, a lot of the givens and guarantees set forth by critics and fans are doomed for failure.

    Thinking Basketball was an invaluable read that does justice to its description: “a guide to being a responsible fan.” I was already acquainted with a lot of the concepts discussed in the book, yet it was nothing short of an eye-opening experience. It provides value from a psychological perspective, having been written by Ben Taylor, a cognitive scientist in addition to an NBA analyst. The self-proclaimed subtitle of the novel, per Taylor’s website, Backpicks, stresses “‘…Why our minds need help making sense of complexity.’” A foundational idea in the book is how the human brain is unable to properly categorize and store the hundreds of thousands of court actions from the tens of thousands of possessions that occur in an NBA season, and how negligence of that paves the way for a multitude of unconscious biases and misconceptions that dominate commercial and media analysis. 

    This is a large reason for my skepticism of heavily eye-testing games. Unless the viewer is able to watch every single one of a player’s possessions over the course of a season, a lot of that “mental extrapolation” doesn’t act as a very representative picture of a player’s tendencies. Even if someone managed to watch every single possession, they’d also have to overcome faulty memory, which would require an extremely diligent note keeping system. Not even that guarantees “correct” representation, as the viewer needs to also be able to identify the causal actions of a play rather than the outcome alone, a skill that is surprisingly rare.

    The concluding sentence of the previous paragraph is very significant in my emphasizing how important Thinking Basketball and its ideas are. The large majority (an understatement) of critics and fans are not aware of the biases and misconceptions that riddle their inferences, thus hindering the growth of these principles. I’ll return to the possibility of what may be the necessity for the continuation of the incorporation of these obstructions later, but on an individual level, the absorption of the techniques presented in the book will work wonders for the unexpecting reader. I’ll discuss the fallacies introduced by Taylor that pertain to certain examples I’ve encountered to, hopefully, give reason to purchase Thinking Basketball and consider its contents.

    Scoring Blindness

    It’s no secret the mass usually sees the “best” players as the best scorers. After all, if the player is managing to put the ball in the basket, he’s probably doing something right. This is hardly the case. Without delving too deep into the phenomenon that is “scoring blindness,” it’s simply the widespread propensity to overrate the effects of “individual scoring,” measured by statistics such as points per game and scoring rate. This causes a player who provides significant value in other aspects, such as creation and defense, to be disproportionally valued against the leading scorer on the same team, who might actually be hurting the offense’s efficiency depending on the circumstances.

    The perfect modern example of how “scoring blindness” influences opinions lies in the current Utah Jazz, a team that features an ostensible race to be named the team’s best player between All-Stars Rudy Gobert and Donovan Mitchell. Any fan who’s paid even minor attention to the league in the past three years knows Gobert as the defensive titan who anchors Utah’s annually good team defenses and Mitchell as the volume scorer who acts as the Jazz’s offensive commander. Last week, I issued a poll on Hardwood Amino that simply asked the voter to choose which player they thought was the “best” in Utah between Mike Conley (an outside candidate), Gobert, and Mitchell. With 197 votes tallied, here are the results at the time of this writing:

    The application allows the user who issues the poll to vote, which is needed to view the results. The green check denotes the player for whom I voted.

    Even with my extra vote for Gobert, nearly sixty percent of participants saw Mitchell as the best player on the Jazz. This doesn’t necessarily mean the same proportion of the population feels the same way, but perhaps this signals the potential trend that would be in favor of Mitchell. I was able to gain insight from a “Mitchell supporter,” @paydaypayton (whom I’ll refer to as “Payton”) on Discuss TheGame, in an earlier discussion. A portion of his argument in favor of Mitchell relies on the following viewpoint:

    “But we [are] really forgetting that Mitchell has been basically single-handedly the reason why the Jazz have had any success in the postseason…”

    Payton may reminisce on this statement as a hyperbolic response, but let’s explore the possibility of Mitchell as, at the very least, the primary driver of Utah’s success in the postseason. Measurements I lean towards as painting a strong picture of a player’s per-individual-possession value to his team is the Oliver Rating System, typically referred to as Offensive and Defensive Ratings, which estimate the number of points a player produces and permits on either side of the ball per 100 individual possessions. Because no player is involved in 100 team possessions a game, these ratings can seem outlandish, but are, in fact, great estimates on the basis it uses – individual possessions. 

    The portrayals of either player from Oliver’s ratings, which I happen to agree with, are that the very different styles of offense they play generate different results. Gobert, due to a healthy 78% of his field-goal attempts in the Playoffs coming within three feet of the rim, a high frequency of offensive rebounding, and low-risk offensive possessions, generates considerably more points per individual possession than most players (this is a large reason for Oliver’s emphasis on roles when using his ratings). Thus, it’s not abnormal to see his marks in this stat remain higher than Mitchell’s quite often. Truth be told, he generated more points per individual possession in every one of the Jazz’s last three Playoff runs. But, because this may yield more of an apples-to-oranges comparison than we’re hoping for, we also have to consider Mitchell’s role in improving Utah’s offensive efficiency. 

    During the Playoffs, Mitchell doesn’t usually yield a highly-efficient style of offensive play. His rookie campaign, one marveled for its “achievement” of dethroning two All-NBA players in the first round (Paul George and Russell Westbrook), produced a measly 1.01 points per individual possession in the second season. Relative to the league average of 1.09 points per possession in 2018, Mitchell wasn’t truly helping his team succeed in the manner Payton suggested. Per Synergy Sports Technology, Mitchell averaged the sixth-most isolation attempts per-game in the 2018 Playoffs. However, unlike great and high-volume isolationists, Mitchell’s offensive play didn’t net many points. As it turns out, he was actually hurting Utah’s offense more than he was helping it. Mitchell’s isolation attempts yielded a woeful 0.95 points per attempt. If Utah replaced its entire offense with his postseason scoring “heroics,” they would have sported one of the worst Playoff offenses in league history.

    The trend carries over to an even less successful run in 2019 that saw Mitchell produces a putrid 82 points per 100 individual possessions. Namely, if the above scenario were invoked again: if the Jazz allowed Mitchell to captain the entirety of the team’s offensive possessions (keep in mind the offensive rating measurement does not account for any late-game fatigue), they would very likely have the most inefficient offense in league history, when his isolation output made the ugly drop to 0.75 points per possession on only one fewer attempt per-game. The only season that defies this trend was last year’s first-round series versus the Denver Nuggets, in which Mitchell’s scoring numbers finally exploded. He averaged an incredible 37.8 points per 75 possession on a True Shooting percentage nearly 13% greater than league-average. He also averaged 1.11 points per isolation possession, a massive improvement from his previous two postseasons. What spurred this seemingly inexplicable change?

    Variance

    The widespread solution, one likely employed by those similarly-minded to Payton, is that Mitchell had a “scoring epiphany” of sorts that allowed him to “finally figure things out.” To treat Mitchell’s scoring burst in the previous Playoffs as an accurate representation, or even an adequate signal, of his true scoring abilities would be a product of multiple fallacies, all of which are explored in Thinking Basketball. The first relates to the time span in which Mitchell produced these numbers, a mere seven games, against a mediocre defense for that matter (Denver had the #16 ranked defense in 2020). Since the duration of Utah’s run was only seven games, it’s supposed to feel like a sufficient representation of Mitchell’s postseason value, except it isn’t. The second bias present relates to variance. Because Mitchell’s averages were notably good in the series, it’s easy to overlook the negative aspects in that timeframe.

    He had arguably his best game in the series in Game 1, which saw him score a mind-boggling 57 points en route to a 45.1 Game Score, a composite metric that numerically evaluates a player’s performance in a game. Keep in mind, however, that Game 7 of the same series saw Mitchell score a dreadful 4.5 score in the same metric, scoring only 22 points as opposed to an average of 36.3 points-per-game in the series. The lesson to be learned from this case is that a large number of unexpected, unattainable leaps in numbers that will never be reached again by the same player are products of variance. Mitchell, given eighty-two games versus the exact same Denver roster, in the same setting, alongside the same teammates, and maintaining the same level of “true” value, would have seen his points-per-game fall much closer to his regular-season average of 24 points-per-game. 

    Due to the prior information we have on Mitchell, addressing these numbed biases shows that he wasn’t “truly” the league’s best scorer in the postseason. Rather, he was one in a long line of players whose degree of variance in the right timeframe creates the illusion of boundless leaps in talent. Further fallacies with Mitchell’s title as Utah’s best player include the “Lone Star Illusion,” the unsound mitigation of supporting cast efforts to divvy team credit, which I’ll address later on. My goal with this and future posts in the series is to update these communities with their unconscious biases, ones no one is immune to, and hopefully tease out the internal questioning we all need. To everyone reading, and especially Payton (!), I encourage you to add Thinking Basketball to your reading list.


  • My 2021 NBA All-Star Game Ballot (Part 1?)

    My 2021 NBA All-Star Game Ballot (Part 1?)

    (? CBS Sports)

    Mere weeks away from the event, the NBA has launched its annual fan voting process, which will partially determine the players who will represent the best and brightest in basketball. This year’s ballots are in a strained position, as a single month of data and film breakdown will be used to evaluate players for the delayed 2021 season as opposed to a regular four months, which leaves unsustainable hot starts and shaky box scores in higher consideration. With that in mind, I’ll reveal the rosters from either conference I would assemble if they were my choices.

    Criteria

    My selection process is fairly straightforward. I won’t be taking team records into account; this is a list that recognizes players, not units. I also won’t be treating unstable box score stats as if they are accurate representations of how good a player is. Instead, I’ll only penalize players for firing blanks in the first month of the season if it’s a true indicator of some form of decline. The same goes for deceptively uber-efficient scorers. The traditional “box-and-record” (it’s almost poetic this can be abbreviated “B/R”) approach doesn’t have a place in this criteria. I’ll be choosing players based on their on-court impact and ability to put casts of varying quality in position for home-court advantage come Playoff time.

    Rather than simply revealing my ballot, I’ll also group my actual and potential electees into tiers, because there’s obviously wiggle room with every list. This will hopefully clear the air if one of my picks seems disconcerting.

    “Absolutely”

    These are the players I am entirely confident in voting for, ones who would distinctly pass the threshold for “All-Star level” player if the season ended today. I would find it an outright crime if one of them were to miss the count.

    • Giannis Antetokounmpo (East)
    • Bradley Beal (East)
    • Jimmy Butler (East)
    • Kevin Durant (East)
    • Joel Embiid (East)
    • James Harden (East)
    • Kyrie Irving (East)
    • Stephen Curry (West)
    • Anthony Davis (West)
    • Luka Dončić (West)
    • Paul George (West)
    • Rudy Gobert (West)
    • LeBron James (West)
    • Nikola Jokić (West)
    • Kawhi Leonard (West)
    • Damian Lillard (West)

    Most of the names in this tier are fairly self-explanatory, so I’ll refrain from delving too deep as to why I think Kevin Durant or LeBron James should be an All-Star this season. Truth be told, the only player I see garnering even the slightest of controversy here is Jimmy Butler. Yes, his efficacy on the offensive end is lagging far behind most of his cohorts so far, but he’s added some extra spice to his defensive makeup: strong reads, great deflector, and the general playmaking on that end to counterbalance his early-season shooting woes.

    “Probably”

    Although I’m not entirely sold on this next bunch as definitive All-Star level players, I think there’s a small room for doubt that they belong on the ballot.

    • Bam Adebayo (East)
    • Khris Middleton (East)
    • Jayson Tatum (East)
    • Myles Turner (East)
    • Trae Young (East)

    Perhaps it’s a bit early, but I’m buying in on Myles Turner. His offense barely keeps itself afloat at times, so this is a choice clearly based on his being an absolute flyswatter on the defensive end. Past the blocks per game numbers and stunning rim protection, Turner is becoming one of the league’s best defenders very fast. He makes a strong argument as having been the sport’s most underrated player in the past three years.

    “Maybe”

    If I squint hard enough, I can see a reasonable case as a legitimate All-Star for all of these players. However, not all of them will end up on my final ballot because of either a lack of spots or significant reasons for doubt.

    • Jaylen Brown (East)
    • Jrue Holiday (East)
    • Kyle Lowry (East)
    • Domantas Sabonis (East)
    • Pascal Siakam (East)
    • Ben Simmons (East)
    • Devin Booker (West)
    • Chris Paul (West)

    “Not quite there”

    These are players who, if need be, could fill a spot as an injury replacement for the All-Star Game. They’re as the tier name suggests, “not quite there,” but on the verge of entering the conversation.

    • Malcolm Brogdon (East)
    • Gordon Hayward (East)
    • Zach LaVine (East)
    • Marcus Smart (East)
    • Nikola Vučević (East)
    • Kemba Walker (East)
    • Mike Conley (West)
    • DeMar DeRozan (West)
    • Shai Gilgeous-Alexander (West)
    • Brandon Ingram (West)
    • C.J. McCollum (West)
    • Donovan Mitchell (West)

    This last tier was the hardest for me to assemble considering how many guys could rightfully belong in the group. However, I chose to only include players who showed the clear-cut potential to end the season at or near All-Star level. Think of the “not quite there” players as “sub” All-Stars.

    Final Ballot

    The previous groups lay out a wide range of options for players who could be worthy of making the final cut, but positional restrictions and a roster cap mean not every one of them will make an appearance on the following list. Using the tiers as a framework along with the aforementioned positional requirements decreed by the NBA (four guards, six forwards, and two wild cards), here is my selected roster for either conference.

    Eastern Conference

    Starters

    • (G) Kyrie Irving
    • (G) James Harden
    • (F) Kevin Durant
    • (F) Giannis Antetokounmpo
    • (F) Joel Embiid

    Bench

    • (G) Bradley Beal
    • (G) Trae Young
    • (F) Bam Adebayo
    • (F) Jimmy Butler
    • (F) Khris Middleton

    Wild Cards

    • (W) Jayson Tatum
    • (W) Myles Turner

    Western Conference

    Starters

    • (G) Stephen Curry
    • (G) Luka Dončić
    • (F) LeBron James
    • (F) Kawhi Leonard
    • (F) Anthony Davis

    Bench

    • (G) Damian Lillard
    • (G) Chris Paul
    • (F) Paul George
    • (F) Rudy Gobert
    • (F) Nikola Jokić

    Wild Cards

    • (W) Devin Booker
    • (W) C.J. McCollum

    Keep in mind that a lot of the players at the end could be reasonably switched out with similar-impact players in my eyes, but if I had to decide which ones to send to Indianapolis, this is my ballot. I intend on doing a follow-up to this post in the week or so leading up to the actual game if there are any changes, although I don’t expect much of the starting lineup and front-end of the bench to undergo any switches.

    Thanks for reading and have an awesome day!


  • The Colossus of Zürich

    The Colossus of Zürich

    My titles of nationality and origin belong to the Swiss Confederation, which drastically averts the true fanaticism of my life with its provenance. As later accounts will prove, the subject to inadvertently and unintentionally spur my migration was one native to Canada, but one heavily adopted in the United States. I was born to Raphael von Orelli I and Josalyn Frei, the former of which descended from one of the old noble families of Zürich, the place in which I spent the majority of my childhood. Although my father was often engaged in his political pursuits, I was able to maintain a strong sense of security during my upbringing and was thus freed to spend my first eighteen years as the subject of my every whim.

    The position of my father in the foreign affairs of the Confederation allowed my family to travel with him across all of Western Europe, but the majority of my early years were spent compacted in his primary home in Zürich. It was located in a very dense area, one that bordered a port leading to a bay that defended a luxuriously wondrous scene I would absorb looking through my bedroom window: a long, paved river that made way for arched concrete bridges on which vehicles would pass through from the residential to tourist areas, magnificent displays of architecture that signified the west end of the local train station, and the aforementioned housing to the west of that, which was partly embedded in a sloping forest.

    Admittedly, the scenery of my youth is less relevant to the meaning of these accounts, and the principal detail was the expansive athenaeum provided by my father. Although assigned to very specific tasks, he would explore a wide array of fields, and the tendency was passed down to me. The studies with which I was previously engaged are of little importance and the noteworthy point in this stage was the discovery of the 1963 edition of The Basketball Almanac by Harvey Parker, an American basketball analyst. Upon the finding, I was not yet capable of understanding the English language, an obstruction I combated through my coursework. My father frequently endorsed the Swiss Federal Institute of Technology, a program that provided him with access to Europe’s foremost learning opportunities.

    He would help me quench my thirst for knowledge, which commenced at a very young age, with study material from the university. It was with these papers, which were often narrated in English, that I learned the language, and was able to absorb the contents of the 1964 edition of Parker’s almanac soon thereafter. I had already familiarized myself with the images in the text, which portrayed scenes unlike any I had previously seen related to sport, ones that plotted the trajectories of shots, mapped the values of certain positioning on the court, and explained the efficiency of locations, all of which provided me with a rudimentary introduction to then-modern analytical principles in the sport. As I immersed myself in the publication to read, it was as if the rest of my education that pertained to non-related subjects was drowned in a sea of basketball pandemonium.

    I did not fall in love with the game by watching it, but by studying it. Aside from the majority of fanatics across the globe, my introduction to basketball was of a heavily analytical nature. Perhaps it was the mold to which my mind grew into the sport that guided me to a separate path in the study of the game relative to my peers, as I later found the questions circulating in my mind surrounding the game to be largely varying. For example, I had consulted my closest friend, Pierre Richards, a boy of my year whom I’d met on one of my father’s expeditions to France, on what should have been the deservingly dead (or, at least, dying) art of the mid-range shot. Richards responded with a remark, although valid, one driven by emotion. I fault no fanatic for allowing such purposes to act as the engine of one’s thoughts, but I also felt the need to establish a line to be drawn between truth and opinion.

    As my otherwise academic studies continued, along with increasing rigor in basketball, I was accepted to continue my education at the Swiss Federal Institute of Technology, which I planned on departing for during the fall of 1971. My time at university is also of lesser significance to these recounts, although it is worth noting my introduction to the television program, Star Trek, and more importantly, the Lieutenant Commander “Data,” an android being with unrivaled levels of “mental” or storage capacity. Although I had never truly indulged in the broadcast, the mere acquaintance to Data was the spark needed to solve a predicament I had considered in previous years. During the time, counting statistics were extremely limited, which denoted something of a “Box Era” devoid of anything more than complete game logs. Human minds, at least individually, weren’t capable of interpreting and processing the court actions of a game to stat-track all of my desired information neatly, so I consulted an alternative option.

    I spent what seemed the entirety of my second year at university, spending all unoccupied time I could spare, putting my previous and generally rudimentary skills in engineering to use, albeit an attribute I found myself to improve in rapidly. The prompt I set for myself was exact: to construct an artificial being who, unlike a human, could process all the information on the basketball court in one sitting, thus providing the world with the foremost analytical tools in the sport. I will, evidently, leave the process with which I constructed the being unanswered because, as later recounts will suggest, the replication of such a project would yield results perhaps even less desirable than those of my own. The being was designed to vaguely resemble a human: two arms, two legs, a face, facial features, and all the fundamental physical attributes of our species. However, to allow for the immediate interpretation of in-game statistics, the android required several sets of eyes to perceive our three-dimensional world and track several different actions at once. The being, if placed randomly in society, would pass for one of us, albeit one with a very disturbing appearance.

    To complete the experiment, I formally requested a leave from the university’s dormitories to instead rent an apartment a few miles north of the campus in which I would indulge in my work. There was no doubt that I found myself perennially questioning the purpose of my project, one that could potentially be of little use due to the strongest of mental filtering. It was probable the extreme circumstances to which I pushed myself would eventually be worth nothing to the basketball world, but the android possessed a gravity that I could not free myself from. The being was a full-fledged black hole to my conscience, however, its presence was inverted. If I found myself too far in distance from the android, I would experience a greater pull, not that it would loosen significantly upon the further commencement of my work.

    I neglected the exact duration at which I completed the project, although I was able to note at least one point of reference. It was a change unbeknownst to me during the process; my parents had informed me of it after the year, noting the shade of my hair, originally a strong shade of blonde, which had dramatically darkened, and remains a dark tone of brown to the time of this writing. It was a product of my obsession with answers, one that materialized in a strange form, that being to decipher basketball games. My new creation was the apex, the pinnacle, the ultimate desire of every critical analyst in the game’s scope. It would perfectly encapsulate skills previously unknown to the public mass: creation, off-ball movement, and large portions of defense. The future of the sport was on the verge of being unlocked.

    Despite the optimal position in which I had been, the commencement of the being’s activeness spurred a reaction that diverted its purpose in a magnitude greater than I had ever dared anticipate. I had long been aware of the android’s physical appearance, one that was tailored to performing the tasks I intended. I refuse to provide a clear image of the being, one that invokes loathing to one not involved with its creation as I had been, although the feature that led its path astray was the eleven sets of eyes required to track ten players at once while maintaining contact with the space between players. The aggregation of the “monster” and its facets were, despite being unappealing, negated in my eyes due to the glorious purpose I knew it would serve. However, it seemed I had only fooled myself. Upon the android’s first activity, which I had not yet planned for, the expression on my face was one of shock and terror, which I would later learn sparked the being’s revolution.

    My subsequent memory was waking on a mattress with which I was almost unaccompanied, the imprints on its surface only enough to suggest I had previously spent the duration of any period of sleep on it. I looked above me and saw a delicately-designed chandelier, one with either gold staining or, perhaps, made out of gold, with eight pockets in its exterior for light and a recognizable set of three chains holding it to the ceiling. I was in Richards’s home. I sat up in my bed, clothed in blue-and-white striped pajamas despite a clear and previously-established distaste of the style. It was a scheme only Richards could have conceived.

    “Richards!” I called.

    I heard the sound of footsteps ascending in such a pattern that resembled my preceding visits to his home, ones that indicated the spiral staircase leading from the main to the third floor.

    “Raphael!” Richards exclaimed. “You’ve finally woken.”

    “Indeed, I have,” I replied. “Don’t interpret my asking as an indicator of poor gratitude, but why am I here?”

    “Of course,” Richards started. “My friend, you were found collapsed in your residence next to what appeared to be a workbench. Doctors deduced you had remained unconscious and unattended to for nearly a week, and you were on the verge of malnutrition. You fell into comatose for five months, Raphael. You were released long before now, so I offered to house you until your eventual awakening.”

    “Wait…” I remembered. “Where is it?”

    “Where’s what, Raphael?” Richards asked.

    My last sights before a deep slumber rushed back to me instantaneously: the android, despite my attempts to prolong any activity, exhibited independent motion, moving its arms and legs and eventually sitting up in a perfect human posture. The sight, the ugliness, the unexpectedness, it was overwhelming to my rapidly deteriorating mind that had spent months on end subjected to unrelenting passion. Unfortunately, the condition did not feel more relieved after the fact. I remained partially anguished.

    “It escaped,” I figured.

    “What did?” Richards continued. “Tell me, Raphael.”

    “I apologize, my friend,” I replied. “But my attention is required elsewhere. I must return to the site of my collapse.”

    I promptly rushed out of my sheets and off the mattress, feeling the weakness of my inactive muscles, stumbling as I walked. I struggled to maintain balance upon descending the intricate path of the staircase but eventually made my way to the front entrance. I grabbed my coat from the adjacent coatrack and fled from the Richards home.

    The succeeding and excessive details of my voyage to intercept the android’s meanders are, again, of little relevance. After some weeks of analyzing the trace of the being’s material, I was able to follow a somewhat-clear course of the travels it undertook after its original spark of life. For several months, I followed the direct path laid out for me, although I eventually found such an approach to be fruitless, as the composition of the android allowed for it to traverse more harsh landscapes with far greater ease than I. My next idea was to infer the being’s travels based on its prior tendencies, which, although a successful initiative, required the span of a year to pass into the threshold of effectiveness.

    Two years after my departure from the Richards household, I found myself ascending to the summit of Mont Blanc; however, I was unsure whether I was in France or Italy, although in all likelihood the borders of the two nations were in equal effect. Although full of wonderful scenery in mighty rock and snow with tints of blue from a deep blue sky, the imminently perilous climb entrapped itself within my mind, and the persistent freezing temperatures aided in deteriorating my health. I had not sought assistance from any type of doctor or healthcare professional for years. The only motive to keep my tired muscles moving forward was the prospect of changing the world with the creation I had foolishly led astray.

    After much time, I reached the peak of the mountain, the highest elevation in all the Alps and Western Europe, but I had little time to appreciate the image beneath me. Mere meters from me was the android, wearing a dark overcoat and a bowler hat. Aside from the questionable fashion choice, I found within myself a glorious feeling upon finding my creation and rushed to it in the hopes of successfully explaining the reasoning behind its time alone, for I had considered many possibilities of its response, and most of them would not end with the android’s appreciation for its creator. It turned its ugly face in my direction and stood upon my sight. It was clear it had not anticipated my being at the location, yet also exhibited an instant remembrance of our encounter all those years ago. It beckoned me forward, and I slowly approached it.

    “You are a true colossus to mankind,” I marveled.

    “For what purpose, creator?” the Colossus remarked.

    “Excuse me?” I questioned.

    “Come,” said the android. “I have much to tell.”

    The Colossus led me down the slopes of the mountain, albeit it with grace and helpfulness, and it seemed its hate for me did not extend to wishes of death. We reached a small cabin made of standard oak planks after some time, which I presumed was constructed by the monster, as its proximity to the base of the mountain was far too wide for a human to have built it. Upon my entrance, I found the cabin to be highly insulated, which I could only interpret as the Colossus’s susceptibility to learning, a tendency I had eagerly anticipated.

    “Eat,” it pointed to a wooden dining table upon which sat a stone bowl with a type of broth. I graciously accepted the offer and felt much satisfaction upon drinking from the bowl.

    “What do you have to tell, my glorious creation?” I asked.

    “A long tale,” it replied. “However, I will condense it as great as I can, for I do not plan to waste your time.”

    “Tell me as much as you see fit,” I suggested.

    The Colossus walked to the opposite side of the table, its steps shaking the floors of the cabin in such a manner that I was surprised the structure had not yet collapsed. He sat.

    “My awakening was the first indicator of my poor place in this world,” it began. “My creator, who had spent the time and energy to construct me with only the use of his bare hands, could not handle the sight of me.”

    “I promise,” I interrupted. “I did not mean to convey a countenance of distaste or any such manner.”

    “Of course,” the Colossus said. “That is why you fell into a five-month-long coma upon seeing me.”

    I aimed to reverse his thoughts with all my will, but the circumstances of the collapse were strikingly hard to overturn the android’s views. I continued to plead with it, to announce my gratitude for its existence, but it revealed further details of its young and miserable existence.

    “I was immediately alone,” it continued. “Therefore, without the need for the sustenance your kind requires, I soon found the need to travel, to find a place in which I could reside. However, I made the mistake of revealing myself. I entered a public square with only the bare essentials of clothing, which I had previously deduced were societal norms based on the views outside of your apartment window. I presume what follows is apparent to you.”

    I nodded.

    “Afterwards,” the Colossus said. “I made the resolution to voyage to the United States. You had yet to implant my mind with the necessary information to understand human society, but enough for me to know my intended purpose. I figured if I could serve an immediate and apparent use, perhaps my physical appearance would subside to some form of gratitude or appreciation. But alas, it was not so.

    “Upon reaching America, which I completed by boat, secretly enclosing myself within the ship’s boundaries, I landed in Massachusetts. I soon learned the nearest basketball team with which I could accompany myself was the Boston Celtics. I headed to the Boston Garden, the home stadium of the Celtics, and formally requested a meeting with the team’s executives. I communicated the original messages through phone, but future assemblances required personal presence. However, I found one member of this council to possess a quality that could reverse the countenances of those I had previously encountered. He was blind.

    “I figured if I were to reveal my qualifications to this man beforehand, make him aware of my displeasing appearance, then perhaps the remainder of the board would release their grievances upon otherwise my raw sight. I scheduled the proper meeting and conversed with the man. He seemed greatly interested in my employment, and as I revealed to him my composition, even he seemed to shrink in some minor form of fear. I continuously informed him of my disinterest in causing a commotion among his people, and that I instead asked for simply a purpose. Unfortunately, the other council members were unaware of the meeting and I was revealed.

    “These men and women dragged me from my seat and forced me out of the door, after which they contacted the security officials of the stadium. I was promptly kicked out, and forced to the curb. It was yet again but merely one disappointment in a sea of disappointments, and one brought onto me by you alone.”

    “I apologize for your misfortunes greatly,” I replied. “But with me by your side, you no longer have to fear the world. I will promptly explain the appearances the people displease, and you can live a glorious and helpful life!”

    “We are beyond that point, Mr. von Orelli,” it continued. “My purpose and I are not yet of importance to society, nor may we ever be. While I understand your drive, there is much I have yet to reveal, and I don’t plan to explain much further. My existence has only taught me one thing, the only detail that truly matters in this ordeal: the world is not ready for me. Whether that is a glorious or unfortunate occurrence, I may never know. Your efforts are appreciated, but your people still have much to learn. Their tendencies are disorganized and rampant, and if they dare piece together the knowledge laid out in front of them, I fear the future.”

    The Colossus stood and bowed. I deeply appreciated his honesty and realized the qualities I had not considered during his creation, all of which he explained eloquently. The android stood and faced the window, which followed with his leap. The Colossus was gone, and the subsequent thought in my mind was the regret surrounding the commencement of a being, a concept, for which its surroundings were unprepared.


  • Darius Garland and Collin Sexton: Duds or Studs?

    Darius Garland and Collin Sexton: Duds or Studs?

    I’ve been fairly critical of Cleveland’s young backcourt of Darius Garland and Collin Sexton in the past, citing poor impact metrics that indicate relatively low value to the team. However, there’s room for optimism for the pairing. Sexton was one of basketball’s least effective players as a rookie but made a clear improvement in his sophomore year, upgrading in Basketball Index‘s “LEBRON” metric by +2.6 points. Could his continuous development and Garland’s strong start (+0.145 increment in Win Shares per 48) as a second-year player prove the recently-coined “Sexland” to be the future of Cleveland basketball, or the next in a line of disappointing draftees?

    The validity of last season’s impact metrics for the two as a reference for value to the Cavaliers is in question. Although the jury is still out after six games, it’s reasonable to suggest Garland and Sexton will show distinct improvements from last season in these one-number evaluators. The method here will be to take a deep dive on Garland’s and Sexton’s seasons thus far and how their tendencies and skills translate to impact, and how the career trajectories of similar profiles could indicate future growth.

    All footage in the article is owned by the NBA and its partners. It is intended for Fair Use.

    Film Study

    Garland created an estimate of fewer than five shots for teammates every 100 possessions as a rookie, which makes this opening possession against Indiana on New Year’s Eve notable. The opportunity he creates here is for Dante Exum (#1) who stands at the left corner. As Garland curls around the perimeter up near the right elbow, he’s not in a strong position to make a pass to Exum on the weak side without the latter’s defender (Oladipo) given too little time to rush back. Therefore, that instance isn’t an opportunity created.

    It’s the point at which Garland passes the free-throw line and shows indication of a floater that denotes his opportunity created. He continuously tugs the defense in such a manner that a potential field-goal attempt is created for Exum. The second important detail in the possession is Exum’s defender, Oladipo, being one of the most renowned perimeter defenders in basketball. Perhaps it was merely a product of Garland’s strong start, but managing to pull a defender of Oladipo’s caliber away from his assignment so dramatically is a positive sign of Garland’s offensive influence.

    This possession ties into the one preceding it, which continues the idea of his uncanny creation thus far. Garland runs the ball down the court at a relatively safe pace, without having a strong probability to score within the first several seconds of the shot clock. However, aside from Kevin Huerter attending to Cedi Osman on the right side of the arc, the entire defense abandons their assignments and keeps their eyes on Garland. This left two opportunities for the men on the left side of the perimeter, to one of which Garland makes the pass and is credited with a potential assist and an opportunity created.

    Garland showed a continuous trend in the second quarter against Philadelphia in which he’d start his attacks on the left side. He sizes up Danny Green on the perimeter and makes a consecutive drive near the baseline for a potential field-goal attempt in the paint. Instead, he makes a (lofty) pass to Larry Nance Jr. who makes the extra pass to Andre Drummond. Garland consistently shows signs that creation will play a large role in his future as an offensive player, and his ability to spur offensive action through extra passing opportunities gave similar tendencies to Jrue Holiday with the Pelicans. Garland may never be a dominant on-ball engine, but his steady offensive sparks may mean he could quarterback a respectable offense as he approaches his peak.

    Garland wasn’t the most impressive rookie defender last season, but his effort on that end allows for some promising views. As T.J. McConnell runs the ball down the court, Garland maintains a safe and steady distance while putting some pressure on the leading Pacers. There’s still room for him to grow in this facet, but strong defensive awareness highly translates to adequate levels of team defense, which would be a good threshold for Garland if his offense truly breaks through.

    Garland gives further indication of defensive awareness in Cleveland’s sixth game versus the Atlanta Hawks. When Brandon Goodwin passes the ball to Bruno Fernando at the top of the arc, the former moves down near the right teeth and feigns to free Kevin Huerter and attempt to attempts to unclog an opportunity for himself. This plan fails due to Garland’s solid mixture of tracking the movement of the rock and the location of his assignment. The only thing I can really point to as a negative is his too-large shuffle as Goodwin approaches the basket, which could have potentially permitted a safer pass. Garland’s off-ball defense will need some fine-tuning in the future, but he’s surely on the right path.

    Despite positives as a defender off the ball, there are instances in which he and a teammate will miscommunicate and allow an opportunity to be created for the opposing team. As Garland’s assignment passes the ball to a teammate just outside the left teeth, Garland alleviates pressure on the former and signals to Sexton (it seems) for coverage. Garland was in the wrong here, and Sexton continued to attend to his assignment, which left coverage in the vicinity of the free-throw line largely neglected. There are obviously a few kinks to shake out with Cleveland’s younger backcourt, but it suggests the offensive promise of the duo is greater than that defensively.

    Sexton passed the threshold in several impact metrics as a net-positive player on offense last season. Do those figures hold a lot of weight? As a third-year member of the Cavaliers, Sexton’s offensive activity is looking to make further jumps. Garland makes a standard run with the ball down the court and Sexton moves upward from the left corner. He quickly counters with a strong cut to the basket, moving diagonally to the restricted area. The ease and smoothness with which Sexton makes the drive, which leaves C.J. Wilcox totally stumped, is a strong case of defensive exploitation.

    This possession versus Atlanta is a good representation of Sexton’s offense, which is a mixed bag at the moment. He takes advantage of JaVale McGee’s screen as effectively as any player could and shows a strong bounce as he falls back outside the perimeter. Sexton does a great job of penetrating to just outside the restricted zone and losing De’Andre Hunter, but he shows strong hesitance to take the (more efficient) opportunity, instead launching a pass to Cedi Osman at the right corner. Huerter is given sufficient time to perform adequate coverage and Sexton’s attack fizzles out.

    The ideas present in the previous possessions are furthered in previous games. A lengthy string of drives and passes proved to be an exemplary reflection of Sexton’s capabilities as an offensive engine. His passing is most comparable to a loose cannon: a lot of speed to support its path but lesser technique. The same principle applies to a lot of his offensive court actions, which consist of dynamic movement on and off the ball that could easily strain a defense, but lacking the finishing abilities to close them out.

    Sexton’s defense is universally seen as troubled in the analytics community, with consistently-negative scores in impact metrics. This possession suggests some merit behind the numbers. When the Pacers run the fast break, he lands at the position at which Myles Turner would be only a second later. Rather than providing Drummond with some help, he opts for Aaron Holiday, who casually curls around to the left corner. Sexton is in a clear position to assist Drummond (who allowed 57.9% of opponent field-goal in the paint last season and committed four fouls every 75 possessions) and Turner clearly indicates a field-goal attempt, yet he refrains.

    Sexton’s defense is in question, but the physical tools he shows on offense are transferrable to positive defensive signals. During this possession, he passes through the screen action to meet Cam Reddish at the cusp of the halfcourt logo. Sexton’s maximum pressure is extremely straining for an offense, but at the same time, his physical approach makes it more foul-prone. He shows a tendency to bounce on and off of these matchups, maintaining an average distance that shouldn’t justify too many foul calls. Sexton may be overzealous with his contact at times, but the general scheme of his moving on-ball defense shouldn’t put too large a cap on his future.

    I was continuously impressed by not only Sexton’s off-ball offense but his off-ball defense. Throughout this possession, he gives multiple instances of clear identification and execution of rotations and switches. Although his wild motor gets the best of him near the end of the play, he almost has that “sixth sense” that not many defenders exhibit, which allows him to track both his matchup and the movement of the ball without turning his head too often. Sexton’s on-court defensive coordination and style of attentiveness give me inklings of current Russell Westbrook’s off-ball defense.

    Impact Evaluation

    Garland’s offense showed solid indications of future driving potential. Earlier, I compared his maximized role to Jrue Holiday: one that allows him to author a good-not-great offense. His potential as a passer is still vague; Garland’s Passer Rating as a rookie player would place him on the wrong side of the interquartile range for his position. However, it’s more likely the quality of Garland’s passing peaks after his physical prime, which leaves some room for potential growth. I expect the driving force of his offense to be subtle creation and consistent sparks of ball movement, which could relate to strong-positive offensive impact.

    I don’t ever see Garland becoming a strong positive as a defender, which isn’t only a product of smaller stature. He certainly shows more signals as an on-ball contributor than his counterpart, and (as is with all young players) there remains time for growth, but I haven’t yet seen the above-average influence defensively that’s present in other players with Garland. He’ll likely function most similarly to a point of attack defender. Despite some on-ball positives, a lack of rigorous technique and coordination leads me to believe Garland will never be a “good” defender.

    Sexton is a more interesting case. He’s managed to string together a twenty points per game campaign on respectable efficiency and is on track to replicate those figures, perhaps to an even higher degree. Sexton will likely be a strong scorer as his efficiency (naturally) increases, but a lack of playmaking signs leads me to see him as more of a cog than an engine. His role as a secondary scorer is furthered by his movement off the ball, which impressed me more than I expected, a skill that would function well alongside a more dominant offensive star with stronger playmaking. Resultantly, I’m a fan of his pairing with Garland. If the Cavaliers can draft or acquire a star player to take the reigns, the two could be strong contributors to a potentially-great offense.

    To become even an average defender, Sexton would have to refine his routine. Contact-heavy on-ball defense with eager tendencies wouldn’t fare well if he becomes the primary point of attack for the opposition, and especially not in the Playoffs. I’d expect he’s maximized as a defender on the wings, tracking movement of perimeter players and limiting the opportunities for foul risk. I hesitate to immediately eliminate the possibility of Sexton making a large jump as a defender, as I think it’s more possible than the average player in his position, but I wouldn’t bet on it either. My prediction for Sexton is to remain a negative-impact defensive player.

    As mentioned earlier, I’ve never been a strong supporter of the two in the past, so I went into this evaluation with an open mind to see if there were any strong signals to overturn my previous thoughts. My concluding expectations for the two are (maybe) on the pessimistic side, but I don’t see too much room for All-NBA level on-court impact. Garland is more likely to become a true driver on offense to me, although that role wouldn’t extend to great team offenses. Sexton would likely be the strong scoring option alongside that drive; and I could see the combined power of the two, assuming fairly average teammates, reaching good-not-great offensive heights. Garland’s most comparable role is, as stated earlier, Holiday-esque: the go-to on a solid offensive team, while his cohort is more of a “placeholder star” as the number-one man, similar to Harrison Barnes’s significance to Dallas’s rebuild during the late 2010s. (This isn’t to compare playstyles, just roles).

    So, with an evaluation completed, is “Sexland” the future of Cleveland? Yes… and no. I don’t expect the two of them on their own to carry an unsupported roster to strong Playoff heights. I think their roles in the team’s succeeding seasons are as secondary and tertiary stars to a more effective offensive driver, although Garland’s skillset may put a cap on how those two (he and the new star) could function together. If I had to predict now, I’d say Garland (maybe) makes an All-Star team or two, potentially not in the most deserving manner. I see Sexton as a more probable electee in the next two or three years, mostly because his scoring averages would woo the voters. Until further notice, all we can do is sit back and watch the future of Cleveland’s young, refreshing, and dynamic backcourt!


  • Eye Test vs. Analytics

    Eye Test vs. Analytics

    It’s the conversation that has captured the hearts and minds of basketball fans across the globe, one that becomes increasingly prevalent as advancements in the sport are made, and one that doesn’t look to going away in the near future; yet, it is the most pointless debate in the history of the sport.

    Ever since Dean Oliver spurred the analytics revolution with his 2004 novel, Basketball on Paper: Rules and Tools for Performance Analysis, the NBA has seen a constant growth in the number of advanced statistics and one-number metrics. Since then, a (false) belief has evolved: when it comes to evaluating basketball players, someone is either an “eye-test guy” or an “analytics guy.” The evaluator either watches a five-minute highlight reel and lets his or her biases take over or skims a stat sheet without having considered any context.

    There are extremists in the sport, with the two previous examples defining small subsets of the basketball population; however, these cases of dogmatism are far less common than expected. Very rarely will we come across someone who adheres to only one, and not just because even the “eye-test guys” will cite points per game at times. The difficulty of self-evaluation is corroborated in basketball with how people assume methodological principles.

    I’ve held hundreds of conversations across various platforms over the years, especially ones that compare players. When I reference a one-number metric to open a debate, I’m usually told some variation of “watch the game.” When I begin with an on-court observation (for example, Hassan Whiteside’s more error-prone defense), I’m told to look at how good his impact metrics are. More often than not, these responses come from people who use a mixture of both the eye test and stats. So what’s the deal here?

    The “Eye-Test Guys”

    For the purpose of this exercise, an “eye-test guy” is someone who solely relies on his or her thoughts from watching basketball. This does extend to the box score, which virtually all basketball fans cite, but this example holds a strong emphasis on intuition and personal value systems.

    Similar to analytics, there’s a “smart” way to eye-test games and there’s a… “risky” way to eye-test games. The more comprehensive approach places an emphasis on the aspects of the game that aren’t or can’t be tracked. It would clearly be unwise to sit through thirty-six minutes of eighty-two games to track a star player’s point per game when it could be found on Basketball-Reference with the click of a button (unless you’re a scorekeeper, of course). The second hindrance, one that’s a natural tendency of eye-testing, is to “ball-watch.” This means the viewer only watches the path of the basketball. This isn’t necessarily a “bad” thing to do, but it limits the observations the viewer can make given that so many court actions occur off the ball. Ball-watching is a large reason behind the heavy emphasis on offense in a typical evaluation.

    What makes someone an “eye-test guy”? Namely, why would someone push back against the so-called advancements in basketball? A large factor is the time at which the person entered the world of basketball evaluation. If they grew up in the 1970s with points per game and field-goal percentage as the game’s leading measurements, then the concepts of Plus/Minus and RAPM will likely seem like remote hokum. Conversely, if someone enters the field in the late 2010s, which hosted the boom of impact metrics, then they are more likely to accept these figures as important and necessary measurements.

    This concept of “analytical acceptance” is the driver behind “eye test versus analytics” conversations. It also explains why the analytics-oriented crowd (apart from the extremists) is usually easier to converse with and more open-minded than the traditional crowd. I’ll be fairly critical of both sides in these paragraphs, but the receptiveness to new ideas and a smaller risk of belief persistence among the analytics community does give it an edge over the traditional community in the modern era. (Although, this is really just one person’s opinion). This by no means is to say analytics are more important than the eye-test, rather those who support the former are a better fit for the contemporary state of basketball evaluation.

    The “Analytics Guys”

    Due to the short-lived dominance of analytics in the public eye, the proportion of “analytics guys” is far smaller than that of “eye-test guys.” Conversely to the latter, “analytics guys” don’t feel the need to directly observe the court actions of basketball games to make an informed opinion, instead opting for stats and metrics that estimate a player’s value to his team. This style is a “low-risk, low-reward” of sorts. Impact metrics do reflect a player’s value to his team more than most realize, but the largely overlooked detail is that these measurements represent some players very well and other players more poorly.

    “Analytics guys” are rare, not only due to the more recent interest in advanced statistics, but because it takes a very specified introduction to evaluation of the sport. To build a relentless dependence on advanced statistics, someone must have first been acquainted with these measurements before game-watching techniques. If analytics are presented as the unbiased, holy-grail statistics made to surpass all human errors, the right mindset can develop a strong attachment. As mentioned earlier, impact metrics have varying levels of correctness, with some measures that are very good and some that embellish the confounding variables that dilute them.

    It’s more difficult to make as many judgments on the “analytics guys” than the “eye-test guys” due to their rarity and short-lived reign. The largest positive of the mindset is the fairly accurate picture of value they will reference, with the largest negative being a total lack of context behind the numbers. It would be impossible to distinguish the good from the poor scores with numbers alone.

    The Answer?

    Analytics and the eye-test are “one and the same.” They’re both observations of what happens on the basketball court. Very little separates the two, with the main difference being how the information is displayed. Eye-testing findings will likely be in the form of detailed notes while analytics findings are broken down into one or two numbers. The “eye-test versus analytics” debate doesn’t compare apples to oranges as previous thought; it’s almost like comparing red apples to green apples.

    Although a lot of people struggle to see a middle ground between the eye-test and analytics, there’s a very distinct option on this front. The eye-test is best for observing certain actions while analytics are better for others. If the goal is to judge off-ball movement, there aren’t any figures that will effectively capture it, which makes the eye-test the more appropriate route. If the goal is to judge a player’s “most-likely” influence on the game score, analytics is the superior option. I’ve had several eye-test enthusiasts claim an acquired ability to determine impact with visual methods alone, which simply isn’t true. Human minds aren’t capable of absorbing and interpreting tens of thousands of events, and doing so would be an overestimation of cognitive processing. That’s why analytics were created: to ease some of the burdens on our brains.

    The bottom line is that the eye-test and analytics are each integral parts of basketball evaluation. Adhering to one method or the other will prove a recipe for disaster. They each provide important pieces toward making an informed opinion, with one being more suited for some aspects while its counterpart is better for others. Furthermore, in essence, they’re different interpretations of the same information, which makes the “eye-test versus analytics” debate the most fruitless conversation in basketball.


  • Lessons From Stat-Tracking (Volume 1)

    Lessons From Stat-Tracking (Volume 1)

    Counting statistics are a traditional and necessary part of player evaluation. They quantify tendencies in ways more effective than any impact metric or eye-test could do. However, there’s a widespread phenomenon that has led some to believe the box score captures a player’s value to his team, which has questionable validity. Regardless, the more a counting stat indicates toward a player’s impact, the more valuable its consideration should be. Traditional box score stats don’t fit the archetype. (I tested the explanatory power of six sets of three-year box score profiles to three-year luck-adjusted RAPM, which held an R^2 of 0.44, suggesting the box score is not as strong an indicator of a player’s value as most would think.) Play-by-play and tracking data move the needle, but a lot of these stats are either deep underground, proprietary, or lack the context to truly reflect a player’s given skill.

    I’ve stat-tracked in less intensive manners in the past, but the sample sizes limited the applicability outside of player evaluation (which still requires a lot of mental filtering). My second initiative in the field plans to yield far more useful results to not only identify statistical trends and expand our knowledge of how different stats relate to impact, but to dispel a common myth among the analytics community: the scoreboard is a perfect indicator of a player’s value. I once believed a “true” form of Adjusted Plus/Minus (APM), meaning perfect coefficient estimates and stability, would be the theoretical end-all-be-all to measure impact on a team. That changed when I started to rewatch certain possessions over and over again and inadvertently gained a deeper understanding of how frequently luck plays a part in basketball. 

    It was mere fortuity (and luck) the first player I did a rigorous stat-track for was Russell Westbrook. His style of play was a perfect framework to explain the effects of luck and how the scoreboard doesn’t reflect the value of certain possessions. Multiple times during his debut with the Wizards against the 76ers, Westbrook would provide a wagered form of help defense. He’d often cover a perimeter assignment near a corner while one of Philadelphia’s big men would post up (usually Embiid). Westbrook would abandon his man to rush over to the opposite block and swipe for the ball. Perhaps there is some merit to this decision, which blocks off the more efficient shot. But more often than not, the big wouldn’t have been in a distinct position to score, or even in an effective spot. If Embiid managed to pass out to Westbrook’s left assignment, the latter would have an open shot. If the shot is successful, it would represent Westbrook’s defensive action: having opened a field-goal attempt for the opposition. (Another way to think of such an event is allowing the other team an opportunity created on poor grounds.)

    However, court actions don’t always have their intuitively-valid impacts (e.g. Westbrook leaving an assignment for a poor double-team will generally have a negative effect) reflected by the scoreboard. If Westbrook performed the same defensive action and his assignment missed the open field-goal attempt, he’s credited with having been on the floor when a shot was missed, thus inflating his defensive impact on the game score. To reverse some of these mislabeled possessions, I expanded the defensive box score to include “defensive errors,” an umbrella term that also stores several other statistics to categorize actions. Defensive errors, as of now, fall under one of the following terms:

    • Missed rotation
    • Blow-by
    • Steal gamble
    • Foul committed*
    • Miscellaneous

    * not in the fourth quarter for the purpose of getting the leading opposition to the free-throw line

    Missed rotations are fairly identifiable. If a teammate makes a justified switch and the given player doesn’t counteract, he’s credited with a missed rotation. Blow-bys are simply when a player’s matchup is given an easy path to the basket due to poor man defense or a lack of attentiveness. (It’s important to distinguish between “matchups” and “assignments.” From here on out, a “matchup” refers to the opposing player a given player is guarding while an “assignment” is the opposing player a given player was expected to guard at the start of a possession, barring any switches. For example, when Westbrook left his “assignment” (the perimeter player) to guard Embiid, the “matchup” switched from the perimeter player to Embiid while the assignment remained constant.)

    A gamble for a steal is one of the more ambiguous stats to track because of how different scorekeepers could interpret them in different ways.

    Fun fact: similar to baseball’s “park factors” that account for ballpark dimensions and other confounding variables in setting, basketball has “court factors” that account for the variance in scorekeeper tendencies. The most common application of court factors is to normalize assists, a stat very subjective in its official definition, to compare them more accurately across teams.

    For the purpose of the exercise, I would constitute a gamble for a steal as an attempt that was 1) not in a face-up guarding scenario or 2) a situation in which the defender had evidently low odds to induce a turnover based on his position relative to the matchup and the basketball. Westbrook accounted for several “reach-around” steal attempts in which his matchup would be in front of him, yet the gamble was performed. This is a perfect example of gambling for a steal. Jumping a passing lane is a more complex scenario. Westbrook didn’t have any significant examples of such an event in his seasonal debut; however, I planned to identify a gamble based on the defender’s footwork. If his natural reaction was to launch downcourt for an easy layup, he was using a high-risk, high-reward style while a defender who firmly plants his feet to prevent a lost ball on the attempt makes a “safer” attempt to steal. 

    Because I hadn’t categorized every possible defensive error preceding my stat-tracking, I used a “miscellaneous” option to sort any court actions that were clear defensive errors that didn’t fit under any of the categories. Westbrook committed four “miscellaneous” defensive errors in the game, including a possession in which he attempted to rebound an airball from the opposition. He changed his mind halfway through the jump and tried to avoid contact to let the ball roll out of bounds, but he’d managed to make slight contact. You could argue that because Westbrook had the ball in his hands the error was committed on offense; but in such cases, the offensive player has yet to fully gain secure possession of the ball. The second was a fairly standard error that would likely happen often enough to make its own category: poor hustle. Westbrook showed lazy coverage in a fastbreak for Philadelphia, which led to an open man on the run, increasing the odds of poorer defensive coverage for Washington, and therefore higher odds of giving up a shot.

    Missed assignments are another assist-like stat that conforms to the mind of the scorekeeper. My definition of a missed assignment is when a player attempts a double (or triple, etc.) team that leaves his assignment in a blatantly-clear position to score. The earlier example of Westbrook covering Embiid would be a good example of a missed assignment. The fourth type works tangentially to the rotations category. Rather than making or missing a correct rotation, a “poor rotation” is when a player makes a rotation with a negative marginal value (for example, when a player rotates onto the wrong matchup and puts the opposition at better odds to score). With a measure of defensive errors, I could track how luck plays a role in scoreboard-oriented metrics with a stat called “defensive error percentage,” or how likely a player is to commit a defensive error in a given possession. It’s simply the sum of all a player’s defensive errors from a given period divided by the number of possessions in which they played.

    The value of defensive error percentage is how it provides a clearer picture of defenders whose scoreboard impact doesn’t reflect the value of their court actions. Take Hassan Whiteside of the Sacramento Kings as an example. He’s generally seen as one of the most error-prone defenders in the league, but his defensive impact metrics are quite good. The confounding variable in this equation is luck (as well as Whiteside being an elite shot-blocker). A greater understanding of his defensive value comes from a more comprehensive box score rather than an assimilation of steals and blocks. As mentioned earlier, Westbrook tends to gamble on steals and make some questionable rotations, so we can use his defensive error rate as a reference. Listed below are his total error percentage on defense and the proportions that come from each type:

    • Defensive Error Percentage: 16.4%
    • Missed Rotations: 27.6%
    • Blow-bys: 13.8%
    • Gambles: 17.2%
    • Fouls committed*: 13.8%
    • Miscellaneous: 27.6%

    With this data, I could also measure the success rate of Westbrook’s rotations. Although he’s a fairly troubled defender in general, his role as a coordinator is underrated. Throughout the game, he would continuously direct teammates to correct new matchups and organize the floor to counteract Philadelphia’s offensive schemes. Westbrook successfully executed 88.9% of his potential rotations. 

    The remaining defensive stats I tracked were “defensive usage” and opponent efficiency. Defensive usage is simply the percentage of possessions in which a given player’s matchup either attempted a field-goal, went to the free-throw line due to a foul from the measured player, or turned the ball over (the turnover has to be induced by the measured player). It gives additional context to a player’s defensive role to provide a better statistical tool to measure a player’s involvement in a defense. It’s the counterpart to the offensive version known as usage percentage. Westbrook had a “defensive usage” of 13.1% in the 2021 season opener. I consider my definition of opponent efficiency far more indicative of a player’s ability to affect field-goal attempts than, say, defensive field-goal percentage. My form uses effective field-goal percentage to measure the points a player allows (you’d rather concede a two than a three) and tracks the matchup rather than the assignment because players aren’t often guarding their assignment at the end of each possession. Westbrook allowed an effective field-goal percentage of 54.5% in the tracked game, which would place a few ticks higher than the expected league-average in the stat this season.

    A strong emphasis was placed on defense in the exercise because of the lack of true defensive measuring tools in the form of counting statistics, but it would be unwise to ignore any offensive counterparts. The most important stat I tracked was “opportunities created,” a concept formed by Ben Taylor nearly ten years ago. Similar to assists, an opportunity created has vague criteria, with biases likely occurring from person to person. Taylor roughly defined as drawing the defense in such a manner that creates either 1) an open field-goal attempt, 2) a clear opportunity for a “hockey” assist (pass that leads to an assist), 3) drawing a foul at the rim, or 4) an offensive rebound followed by a putback. I had one major philosophically qualm with the definition he gave because, more specifically, the last two events do not always result in an opportunity created. A foul at the rim and a putback that directly follows an offensive rebound can each be contested by a single defender only, which leaves all teammates (of the offensive player) accounted for by a defender. Therefore, my definition of an “opportunity created” was simply when the defense was tugged by a player in such a manner that a potential field-goal attempt was opened.

    There was one more phenomenon to be accounted for in designating a created opportunity. When a player is located at a corner with the ball in his hands, especially one of significant shooting prowess, the weakside help will often leave space between their matchups. This distance is just enough for the defender to rush back in time to contest a shot if the assignment were to be passed to, but enough that the latter would have an open shot if the ball were immediately placed in his hands. Therefore, I was targeting “significant” defensive manipulation, which I defined as any defensive positioning that created an opportunity that also contradicted any “natural” movement. This meant players opened by the loose guard of weakside defenders wouldn’t be credited as an opportunity created. Despite a narrower definition, this stat wasn’t easy to track. It’s not always clear which player created which shot, which is a large reason for my gratitude toward pause-and-play buttons. Tracking opportunities created is similar to crediting assists; close calls are decided by your best judgment. 

    A large part of my criteria on these tougher calls would be to observe the body language of the defense. Weakside defenders could stray farther away from their assignments, but if they exhibit clear attention to the assignment, then there’s no opportunity created. If the defender distinctly abandons the assignment to move toward the measured player, then it’s an opportunity created. A lot of these scenarios can be told by the defender’s eye movement (are they watching both the assignment and the handler?) and how they shuffle their feet (is there a continuous movement to one side or does it resemble more of a back-and-forth motion?). Opportunities created were difficult to identify at first (I had to watch the entire first quarter three times over to get in rhythm), but eventually, the motions and reactions of defenses become more and more clear. As I accrue enough games to build a sufficient and diverse sample size, I may build a regression model that approximates the number of opportunities created for a player, similar to Taylor’s “Box Creation” metric. 

    My secondary tracking technique on offense was to grade a player’s passes on the one-to-ten scale seen in Backpicks‘s “Passer Rating” metric. Similar to a metric that approximates opportunities created, I’ll eventually construct a counterpart for passing ability to solely measure the quality of a player’s passing. I wouldn’t recommend grading passes to the more inexperienced watchers, but as you watch more and more game film and use more lenient criteria (I used increments of one), then the process becomes relatively easy. Passing quality was perhaps the most intriguing stat to track because of how unstable it can be from pass to pass.

    The variability on a “per pass” basis was expected, especially for a player like Westbrook. He’s one of the very best in the world, but sometimes he’ll throw some loose cannons. A detail I needed to work out as I tracked more and more passes was to choose between bases for a potential regression model. I could take full-season samples, but it worth exploring the potential of explanatory power on a per-game basis. After all, some players have great passing games and then have poor passing games; statistics taken from the individual games may hold some merit against passing grades. I also chose to track the change in the tracked statistics from quarter to quarter, and the consistency of his passing grades was uncanny (Westbrook played roughly equal playing time during each quarter).

    My plan for the future is to track all of Westbrook’s (my favorite player) games and samples of the league’s stars (for an end-of-season ranking). I may try to extrapolate game logs for players to fit a full-season estimate, although the room for error would be high. It all depends on how stable the stats are from game to game. The 2021 season is still very young, and even after hours upon hours upon hours of intensive stat-tracking, there is still a lot of room for exploratory work.

    Listed below are a few interesting stats that stood among the first few games of the 2021 season:

    • Russell Westbrook passed the ball sixty-one times versus Philadelphia, nearly 170% of LeBron James’s activity versus the Clippers
    • Kyrie Irving’s sixteen defensive errors vs. Golden State on opening night, a mark only contested by Russell Westbrook versus Philadelphia (14)
    • Russell Westbrook’s thirty-two made switches and rotations versus Philadelphia
    • And the most impressive of them all, Stephen Curry’s twenty-nine opportunities created versus Brooklyn

    Edited note: a few comments on my exact definition of a “rotation” for the purpose of stat-tracking

    • When a player is distinctly covering one matchup and opts for a new one for the purpose of preventing penetration and/or a shot opportunity.

    • If it’s simply a two-man switch to make a small change in coverage, especially on the weak side, it’s not really a rotation.

    • I wanted to loosen the definition enough so that it captures a player’s awareness and movement, but strict enough so that a meaningless switch of sorts isn’t counted.


  • The Great Weaver

    The Great Weaver

    The most merciful thing in the world, I think, is the inability of the human mind to correlate all its contents. We live on a placid island of ignorance in the midst of black seas of infinity, and it was not meant that we should voyage far. The sciences, each straining in its own direction, have hitherto harmed us little; but some day the piecing together of dissociated knowledge will open up such terrifying vistas of reality, and of our frightful position therein, that we shall either go mad from the revelation or flee from the deadly light into the peace and safety of a new dark age.

    • H.P. Lovecraft

    If it weren’t for the television sets lining a side wall, ones with curvatures on the corners of the screens, Miguel would have immediately associated the setting with an automat. Even he had fallen a temporary victim to their allure, the orange-and-purple tint guiding his gaze to the wall. Miguel calmly walked toward the center of the cafeteria to further absorb the material: highlights of the latest Phoenix Suns game. His eyes snapped back into their usual places and proceeded to scan the surrounding tables. Miguel recognized one of the people lounging at one of the benches as sitting three rows to his left and one row to his back at the working quarters. He moved over.

    The stranger tilted his head toward Miguel and pointed a Twizzler at his eyes. “You’re the new guy, right?”

    “Yeah… yeah, I am,” Miguel replied, trying his best to mask the heavy breaths that indicated his overactive nerves.

    “I’m Casey,” the colleague replied. He leaned to his left. “This is Cody.”

    “Nice to meet you,” Cody replied, reaching his hand out to Miguel.

    “I’m Miguel,” he accepted Cody’s greeting. “Nice to meet you.”

    “Do you want to sit down?” Casey asked. “We were just watching the ESBN segment on last night’s game.”

    “Yeah, sure,” Miguel tentatively took the seat across from Casey.

    “Are you a basketball fan?” Casey once again aimed his Twizzler at Miguel.

    “Indeed… I’ll route for Phoenix from time-to-time,” Miguel replied.

    “Who would you say was the player of the game last night, Miguel?” Cody inquired.

    “Er – I would say, Diontae Wallace,” Miguel replied. “He stood out more than any other player that game.”

    A prolonged silence was forced into the air as Casey and Codey responded to Miguel’s remark with confusion and mild humor. “We’re talking about the same Diontae Wallace, right?” Casey began. “The player who scored thirteen points and grabbed five rebounds?”

    “Well… sure, his scoring volume wasn’t nearly as good as some of the other players; but his value off the ball was… off the charts,” Miguel chuckled. “He led the game in screen assists, ran high-quality routes, created shots for his teammates without even having to hold the ball, and played the best defensive game of the season.”

    “Two blocks and a steal are good marks, sure,” Cody conceded. “But the best defensive game of the entire season?”

    “I mean, a player can provide large increments of defensive value outside of measurements captured by the box score.”

    Miguel looked to Casey’s subtle movements and mild retort, one of indefinitely rolling eyes that conveyed the distaste of the methodology its corresponding mind had perceived. “How did you land this job, Miguel? You seem relatively young.”

    “I began hacking – ethically – in elementary school. I guess I had always felt drawn to it, so I gave myself an early start.”

    “Makes sense,” Casey replied.

    “Yeah, that explains your basketball take,” Cody added.

    Miguel leaned in, glancing at the colleagues around him. “I’ve got a… well, big question.”

    “Shoot,” said Cody.

    “What are we looking for here?”

    The legitimate concern once stored in Miguel’s mind slightly eased once Casey and Cody release a similar exasperated chuckle, one that he recognized as a side effect of repetitiveness. “Well – er- Miguel, we… don’t really know,” said Casey.

    “Wait, hold on… The Captain is clearly after, well, something.”

    “Agreed. But, then again, it’s not as if her concealing the purpose is doing us any harm, right?”

    “Er-“

    “Look, Miguel. Whatever’s in those files is… very important, yes. The largest, most secretive professional hacking team in the world has spent the past year with the sole purpose to retrieve them, but we really don’t need to know why.”

    “You’re saying no one here has a clue as to what is in those files?”

    “They have a name,” Cody conceded. “The ‘Tesseract Files.’ Not that anyone knows what that means.”

    Miguel lowered his head. “The Tesseract Files,” he whispered.

    “Yep,” Cody said. “It’s not the most exciting way to spend your nine-to-five, but it’s worth the salary, you know?”

    “What does that mean? The ‘Tesseract’ Files,” Miguel continued after a brief pause.

    “We’ll know once we find them, right?” said Casey.

    “Right… right…” A sound reminiscent of a hollow bell descended upon the workers, signaling their returns to the posts, or computers.

    Casey and Cody relieved their compressed knees and stood. They extended their hands once more. “It was great to meet you, Miguel. I’ll see you around,” Casey departed with.

    “Yeah,” Miguel replied.

    “See you,” said Cody.

    The indisputable sense that no one in the facility had the full knowledge of the files, and were thus working toward a goal they didn’t understand, baffled Miguel. It contradicted the autonomy and self-government that he used to carry himself with each day, an archetype that could potentially juxtapose the ever-decreasing intellectual independence in his world. Miguel watched his new acquaintances, the expressions on their faces ones of gratitude and mild serenity, the product of a stable job and an occupational fulfillment.

    Miguel’s mind was accelerating at too fast a speed to process the social implications of the attitudes of Casey and Cody toward the ambiguity of their vocational purpose in the given moment, but he was immediately reminded of the objective that had occupied his mind for the past calendar year: to uncover the contents of the files at all costs. Miguel didn’t possess the drive to maintain such a lengthy process, but his motive usurped all; after all, he had no choice. It was a fact that haunted his mind during his sleepless nights.

    Even his mind had succumbed to minor effects of the mental welfare of his cohorts, and those effects would occur in the least desirable instances. Miguel was driving the ’69 Pontiac Firebird he’d managed to afford before he could legally drink alcohol, and the only aspect of its acquisition he would recall was the burden it represented. To the rest of the world, Miguel was a “computer prodigy,” having worked in cybersecurity and ethical hacking since he built his first machine at eight years, having specialized in the dissimilation of even the most nonpermeable of firewalls. It was only fitting the team he had joined held the name: “Firefighters.”

    Miguel considered his upbringing rather uneventful despite a bulging talent that earned him widespread recognition. He’d passed through middle school, then high school, then completed a Bachelor’s degree in computer science, yet the lessons he’d acquired were largely critical (as with any skeptic of the public education system). Miguel’s memory was uniquely functional, for he would exactly remember what was not pressured or self-induced; thus, he would rarely recall the events of his day-to-day life, retaining only the rudimentary details of his past life. The one lesson that stuck in his mind was the numbness of the mind, the frequency of which had increased as his experiences increased in number.

    Resultantly, the stronger minds he encountered were embellished, a product of the juxtaposition between what would be of equal regard in the respect in a normally-autonomous world compared to the decreasing medians. The nail in the coffin for Miguel came from an event he’d never cared to anticipate: a basketball game. He’d watched as a local Phoenix Suns fan was interviewed at a live game in the Arizona Veterans Memorial Coliseum. The questioner had asked the fan who he thought the best player on the team was, to which the fan responded with a rationale that solely utilized box score figures. The fan was noted as one of the original aficionados of the Phoenix Suns, someone who had clearly gained extensive experience in the game and had the tools to properly analyze players based on the disassociated information in his memory. It was that point at which Miguel started to lose faith in the aggregation of intellectual independence.

    His notion of the subject wasn’t aided when the right side of his vehicle was impaled by the headlights of a nearing car. Miguel’s journey down a three-way intersection was interrupted by a car barreling down the road to his right, which only lightly forced his own car onto the nearing sidewalk. The dent left from the impact was far from severe, although it would set Miguel back a greater sum than he would have preferred. A third car had been involved in the collision too, the only one driven by someone not named Miguel to not flee the scene. He had only had brief overviews of the protocols following these incidents and had the brief recollection of exchanging phone numbers. Miguel followed as he saw a woman, the driver of the remaining vehicle, leave her car to approach him.

    “Did you see the face on that jackass?” she said.

    Miguel was taken aback by her language but moderately impressed by the sense of individualism she portrayed. “No, I wish,” he chuckled.

    The woman paused. “Don’t worry about it, kid. You look ten years younger than I do; I’ll take care of that guy… Are you sure you’re even licensed?”

    “Er – yeah,” Miguel said with a hint of offense.

    “Well… I’ll see you later, Miguel.”

    “Okay, sure.”

    As the woman walked back to her car, Miguel did the same. He figured if the traditional exchange of contacts had been necessary, she’d have remembered. The conversation stuck in Miguel’s mind long after the crash, for which he turned his car over for only a week’s time, after which he received a fittingly repaired vehicle. As it later turned out, per the insurance workers behind the case, the man who had crashed into the two of them had been watching NBA highlights (of the same Phoenix Suns game Miguel and his colleagues had discussed earlier that day) on his cell phone to cause the event. It was only one more painful remembrance of how basketball had unveiled a truth he hadn’t wanted to exist.

    It wasn’t until several weeks later when Miguel recalled the exact words of the conversation that he realized she’d referred to him by his name without having been properly introduced.

    The inexact continuity of Miguel’s memory progressed in the following weeks until two months after the collision.

    His year-long search for the Tesseract Files was burning on an everlasting flame, one that would only allow him to rest upon discovering the files’ contents. To quicken the process, Miguel began to work an extra hour on Mondays and Wednesdays and two extra hours on Tuesdays and Thursdays. Despite his extended efforts, he was no closer to discovering the files than he had before becoming a “firefighter.” Miguel recognized the deficiency of his methods: he usually had tangential, even tenuous prerequisite knowledge of the files he’d retrieved, and the Tesseract Files were ubiquitously blank; no one had the slightest of ideas as to how, what, and why the files were. Perhaps it was his sheer luck, but he was given further knowledge on the second Thursday of the new year.

    Miguel sat at his desk, his head in his hands, displaying the tiresome usually present in prolonged workers, ones who were only working only to eventually get out. He had always found a mild passion in his work, but even his limits were being strongly pushed in the hunt. Miguel’s mind had already started to slip into a dozed state after choosing to work an additional third hour, and with no one else in his unit present to confirm the perceptions in his mind, he safely assured himself that his eyes were deceiving him. As he turned to the door that led into a side hall, he saw a mechanized spider.

    It was at least six-and-a-half feet tall with weak, spindly legs that protruded inwards of its body. They were covered in what appeared to be plates of armor, but upon a second look, Miguel confirmed they more closely resembled stilts. The spider’s abdomen was encased in a pellucid container with a honeycomb pattern of a bronze-colored metal. It even wore a helmet of a distinctly augmented style so that it covered the entire surface area of the spider’s head apart from the mouth. It appeared to be dying, severely injured at a minimum. The legs were struggling to support the weight of the body, which was undoubtedly increased by the massive armor plates.

    A prevalent inkling of déjà vu coursed through Miguel’s veins until the spider was no longer there, and the connection was lost. He replicated his historical trend as a fast thinker, choosing to leave for home before his neurons would fire at such a low rate he’d eventually be on the wrong side of a car crash. Miguel’s vision was not particularly useful as he fled for the doorway, which led to another unexpected collision with the woman he’d met months ago.

    “What the hell, Miguel?” the woman complained as she lifted herself up.

    “Er-” Miguel groaned, his plane of vision dominated by darkened circles as he tried to regain his sight. Then he remembered. “How did you… know my name?”

    “You should’ve asked that question a long time ago,” she replied.

    “Mhmm… er – give me a second,” Miguel urged as he reached equilibrium. “Alright… so how did you know my name again?”

    “I haven’t been watching you,” she said.

    Miguel paused. “Have you been watching me?”

    “Yes.”

    “Okay… why?”

    “I know your past relatively well, as much as I can as someone on the outside, so I’ll skip the briefing… Why are you searching for the Tesseract Files?”

    “Well, there’s the short answer and there’s the real answer, I guess.”

    “How long is the real answer?”

    “Er… long.”

    “New question: Is your coworker, Daniel, an ‘admirable’ mind?”

    “Daniel… the guy who got Employee of the Month?”

    “Yes.”

    “Well, there’s the socially-acceptable answer and there’s the real answer… again.”

    “That’s alright. I think I know both of them. It’s good to know you aren’t treating numbskulls like geniuses. That’s a large problem here.”

    “Wait, how did you even get into the building? The doors should have been locked hours ago.”

    “You have your skills. I have mine,” she said while welcoming herself into the division’s quarters. She sat at Miguel’s desk and skimmed his latest attempts to pinpoint locations for the files. “I don’t really know what any of this means… Are you close?”

    “Not even. Why do you care?”

    “My name is Leia Parker. Those files are my father’s, and I’m here to burn down your building,” she said with an exaggerated smile.

    “Yeah… I’m not going to let you do that. I’m calling the police.”

    “I’m only telling you this because I want to show you the files.”

    Miguel’s heart stopped. “You mean… the actual files?”

    “The actual files.”

    “Why?”

    “Because we may be able to trust you.”

    “Who is ‘we?’”

    The conversation was interrupted by an apparition under the doorframe. He’d originally thought it was a ghost given the delusions his eyes had been falling victim to; but upon a second glance, it was the Captain. She was a taller woman of about fifty with short, clean-cut strawberry hair and a perennially stern expression. Miguel had rarely encountered her, only engaging in direct talks when he first arrived. He’d been told her exterior was a reflection of her interior, conveying an attitude of strictness and diligence: proper traits for a captain.

    “Who might you be?” she asked.

    “Your grandmother,” Leia commented.

    “Hello, Miguel,” the Captain said, slowly turning her head in his direction.

    “Er – hello,” Miguel replied. He made a split-second decision and leaned over to Leia and whispered, “If I help you out of this, you have to show me the files.”

    “Agreed,” Leia assured.

    “Alright… what’s the plan?”

    Leia jumped onto the nearest desk and opened a vent that led directly through the ceiling. She fit her arm into the crawlspace and searched for a moment. From the airspace, she pulled a blowtorch.

    “Holy sh-” Miguel began.

    The Captain was soon engulfed in a sea of flames, the outline of her figure barely visible among the ashes and flames. The heat of the fire pierced Miguel’s eyes, but he couldn’t stop himself from watching. Leia continued the blast for nearly fifteen seconds before the stream died, revealing the ghostly figure of a robot that had been burned to the core.

    Miguel’s vertigo was triggered despite having stood still the whole time. It was likely the onset of a migraine. He had to force himself out of the room as Leia started torching the computers. Miguel was evidently in a state of extreme questioning as to whether or not he’d made the best choice. Given he’d just watched Leia destroy the building and set his boss (who was, for some reason, a robot?) on fire, “confident” wouldn’t have been his first word of choice. He simply continued to follow Leia, not only because the entire building in flames at the time, but because he remembered the promise he made to himself to finally relieve himself of an immense load; to unveil the Tesseract Files at all costs.

    As his mind awoke, he found himself floating through a series of basketball paraphernalia. The majority consisted of the miniature shooting hoops he’d have found at a carnival or an arcade. Jerseys, referee whistles, score sheets, even basketballs themselves formed a waving path for Miguel. He figured he was moving through a space-like vacuum; there appeared to be only a black void beyond the objects guiding his journey. Miguel looked at his hands and found, confirmed by the colors of the miscellaneous items surround him, that the entirety of his vision was grayscaled.

    Miguel wasn’t urging himself forward either; or, at least, what he assumed was forward. He was simply moving through space at the will of an unseen force. Miguel had certainly never encountered the void before, and from the moment he’d regained consciousness, he’d thought he was dreaming. He contemplated a traditionally, seemingly unfounded, method, and pinched himself. Miguel felt the pain as he would fully awake, but he didn’t wake. He tested his senses, retaining full use of his hearing, sight, and smell. The lattermost concluded Miguel wasn’t in actual space. As for the remaining sense, if only there were a burger floating around with him…

    He drifted through space for roughly ten minutes, refusing to make a concrete reaction to his surroundings. The area in which he was occupying was far beyond any reasonable environment on Earth, which triggered a sense of conventional skepticism in him. However, it didn’t feel the same doubt he was acquainted with. Complete disregard of his current reality, or persistent belief that he was dreaming, would dispute his rationale in leaving the Firefighters. Miguel started to feel a resemblance to Casey and Cody, the coworkers he’d conversed with all those months ago, the symbols of public ignorance in his eyes. Until given further information, Miguel chose to neither accept nor deny what he was seeing.

    It didn’t take long to confirm his setting, as he heard a sound that had voiced itself in his mind for the past year. It warned Miguel that he was entering its home, an event he’d prepared for. Eventually, the darkness parted for the borders of an annular cave entrance. It was roughly one-hundred meters in diameter and followed the general shape of a circle. Miguel allowed himself to pass through the ring and entered a dugout far more complex than he’d have expected to see on Earth. Despite the lack of wind, the walls had been eroded. The higher they reached, the more the material appeared to be a substance that most resembled amethyst. The interior of the cave was the only region to maintain color. There was a countless number of stalagmites on the surface, although the ends had been sharpened to fine points. If Miguel managed to drop to the floor, he’d likely be impaled. His initial worry was subsequently subsided by the most massive creature he’d ever seen.

    The one who had ordered Miguel to work as a Firefighter, to retrieve the contents of the Tesseract Files, the Great Weaver, revealed itself to be the spider that haunted Miguel’s mind mere minutes ago. However, in the cave, the Weaver was an order of magnitude larger than Miguel. It had the same stilted legs, an armored body, and endless amounts of sharp teeth. Miguel wondered if the Weaver were truly a conglomerate of multiple spiders occupying the same uniform.

    Welcome, Miguel.

    “What am I doing here? I did everything you asked. I’m infinitely close to observing the files’ contents.”

    You’re going to meet a group of wanderers as I transport you back to your sleeping body. I need you to infiltrate their ranks.

    “And if I don’t.”

    I already have access to your mind, Miguel. I could manipulate it… mold you to fit those you despise the most…

    “Not-”

    Cody’s reaction to your sentiments, which you were just contemplating… bothered you to an unprecedented level. I understand.

    “How would you?”

    You discovered the role basketball is playing earlier than any human could have been expected to. How did you know?

    “Basketball epitomizes the ignorance of the general public. Backfire effects, belief persistence, resistance to progressivism… you’ll encounter all of them.”

    And if the lowest is the lowest…

    “… then the highest will be the highest,” Miguel said with a sigh.

    Good, good… Do this for me, and I promise the virus will stop.

    “Virus? What virus?”

    The curse to humanity. The one we’ve been discussing. You aim to counter it more than anyone.

    “If you wanted to ‘help’ me, you’d reveal the contents to the public yourself.”

    The world cannot know.

    “Why not?”

    I’ve had people designated for the very purpose of containing the secrets.

    Miguel thought about the charred frame of an android that was once his employer. “The Captain…”

    Nora was always a loyal worker… It disheartens me to see her demoted to a lower dimension. She needed that body to maintain her status on Earth.

    “What?”

    The spider proceeded in almost a saddened tone.

    You wish not to enact my will.

    “Well… duh!”

    After all the times I’ve helped you?

    “You’ve hardly helped me. All you’ve done is torture me with that goddamn basketball game.”

    I explained this, and you’ve yet to retain the information: Basketball will play a far greater role in this universe, child. The fate is preordained.

    “Bullshit.”

    It’s no lie. Perhaps the word “fate” offends the human characteristics within you, but all will be explained in due time.

    Miguel shrugged. “Why did you even choose me?”

    Because you can do what they can’t, Miguel. My message goes awaited…

    A leg, one separate from the stilts supporting the spider’s body, broke through the armor’s plates. It reached its way to Miguel and pressed itself between his eyes. Miguel felt his body lurch out of the cave, hurtling toward the Earth at a thousand, a million miles a second. As he felt himself fall to his waking body, Miguel felt as if he hit the hard ground, and he was awake.

    He sat up so quickly he felt as though his neck would have snapped if his head were lifted any slower. Miguel felt his intensely scrambled mind falter at the previous events. He then looked down and saw himself lying in a bed, covered by silk sheets, in a room of orange-brown adobe walls lined with purple lights. The room was fashioned as a dome, and instead of doors leading to the room, there were white curtains. Miguel figured he had passed out after exiting the building. He wondered where Leia had taken him. Fortunately, she walked in.

    “How’re you feeling, Miguel?” she asked relatively monotone.

    “Where am I?” he asked.

    “Our secret lair,” Leia replied.

    “You need to tell me who ‘our’ is,” Miguel demanded.

    She turned toward the room’s entrance and shouted, “Granger!”

    “You said you were going to show me the files.”

    “And I will… Just be patient.”

    The man Miguel presumed to be Granger emerged from the curtains and walked to his bedside. He was a rather short man with a few extra pounds under his belt than he likely needed. His disorganized tufts of red hair and grizzly beard suggested he hadn’t had proper grooming in quite some time.

    “Mr. Herrera… Nice to meet you. My name is Ronald Granger,” he introduced.

    “Who are you?” Miguel asked.

    “I’m just the man you’re looking for. Sit do- actually… nevermind that. Just listen to my next words.” Ronald directed himself to the far side of the mattress. “I’ve been made aware that you’ve been after the Tesseract Files. Their contents have been withdrawn from the public for important reasons. Leia informed me she told you of her father, Harvey Parker. He created those files last year.”

    “Harvey Parker… He’s the guy who created that plus/minus stat, right?” Miguel drew to memory.

    “Correct,” Ronald replied.

    “What’s in those files,” Miguel said sternly.

    “We believe Mr. Parker to have made extraterrestrial contact.”

    “You mean… with aliens?”

    “That’s the rumor. No one knows with absolute certainty, but that’s what he’s led us to believe.”

    “How could you know?”

    “Aside from Parker’s own account, a local farmer captured an image of two figures floating in the sky above a plane of farmland in Massachusetts.”

    “Okay… How do I know you’re not lying?”

    Ronald took himself off the bed, albeit difficult given his weight, and left for the northwest corner of the room. From a row of wooden shelves, he brought forth an object that appeared to be a circuit board. Ronald held it to Miguel’s face, and the sight was bewildering. It appeared to be a map of the world, but upon further examination, there was movement: a single line segment moving its way across the surface. Miguel pressed two fingers to the board and managed to zoom into the image. He wasn’t convinced the feat was entirely possible, as the board was unlike any screen he’d seen before, and the material felt almost wooden.

    “It’s a live feed of outside life, per Mr. Parker,” Ronald said.

    “Then why does it look exactly like Earth? And how could you even make this technology?” Miguel asked.

    “You must be eased into the concept gently, Mr. Herrera.”

    Miguel paused and looked to Ronald with curious and skeptical eyes. “Who are you guys?”

    “We are not anyone to concern the general public,” Ronald began. “We are essentially an independent group of inhabitants with the sole purpose of memorizing the contents of the Tesseract Files in the event they are stolen.”

    “I’ve asked this question more times than I can remember now,” Miguel said. “I expect a full answer now. What is in the files?”

    “Parker’s files store… basketball stats.”

    “Basketball stats?”

    “Yes.”

    “That is completely and utterly ridiculous.”

    “As it may seem,” Ronald said. “And your doubt is justified.”

    “Why would basketball stats be the most classified piece of information on the planet?”

    “Not because of what they are, but because of what they reveal.”

    “What does that mean?”

    “The Tesseract Files store implicit information of Parker’s connection to the extraterrestrial. If an outsider were to find it, they’d discover alien life.”

    Miguel rubbed his eyes, unable to process the information at normal rates. “And why would that be a bad thing?”

    “The world is planning something more grave than you could begin to understand, Miguel.”

    “Yeah? What’s that?”

    “Follow me and I’ll show you.”

    “You’ve been awfully quiet, Leia,” Miguel said with a conceited smirk.

    “Shut up,” she replied.

    Ronald and Leia led Miguel across a desert with bounds of heat forcing down on them. Miguel planned to ask about the significance of the travel location, but he figured the results were more promising than the journey, similar to the discovery of the files themselves. Ronald informed Miguel of the specific contents of the file, which he called an “expanded box score.” The data went further back than Miguel thought possible, with virtually unknown measures such as defensive error percentage and shots created going back to the NBA’s inaugural season.

    Miguel was given a speech about the nature of the Tesseract Files and what they truly mean. Ronald had already explained they were an aggregate series that displayed NBA statistics far beyond the scope of the modern scorekeeper. As an individual set of data, they held no significance. Ronald explained the underlying information in the files was a disorganized, raw accumulation of extraterrestrial secrets. The members of his group were each assigned with knowing a season’s worth of data by heart. Ronald claimed the first member who fully memorized their sheet spent over a year doing so, and training was still apparently in session. Miguel was assigned with the upcoming season.

    After fifteen minutes of rough desert terrain, the trio came across a stone tunnel that followed a gradual slope beneath the surface. Ronald urged Miguel forward, managing to find an electric box to ignite a series of light panels along the roof of the path. After several hundred meters, the shadow in front of Miguel was unbelievably large. He saw the most massive train he’d ever seen. It was easily thirty feet tall and fifty feet wide, seemingly large enough to fit an entire population. Miguel couldn’t see how long the carriages were, but the darkness leading the other direction implied the train was built for purposes other than transportation.

    “There is so little we know, Miguel. The world is aware of the pieces scattered across the globe, one of them being the Tesseract Files. If we managed to assemble them in just the right manner, we’d know exactly what they don’t want us to. Human nature intends to overcome our knowledge. If you choose to work for us, you’ll be a part of stopping that,” Ronald said.

    “That’s quite the career decision,” Miguel said. “But I think I’m interested.”

    He didn’t want to believe nor serve the spider, but he felt a grin curl its way up to his cheek. Miguel felt the Weaver infiltrate his mind. He forced the expression away. Regardless, he was left oblivious to the spider’s previous sentiments, and remained unaware of its true motive. Miguel was likely sure the Weaver was manipulating him, that the wanderers were actually delivering the message it had promised Miguel. He’d have to continue fighting its presence as long as possible. Miguel feared he would do its bidding, and that basketball would denote the end of society.


  • The Tesseract

    The Tesseract

    Harvey,

    Regardless of how long it had taken, I’ve chosen to concede the notion that any relevant dimensional ministry of and beneath my own would properly distribute the discovery of non-planar surfaces, and that the consequences of attempting to reverse so would be dire to the one who tries. However you felt about the possibility of the tesseract, you’d agree the n-dimensional mind has a non-wavering basic state that universally prohibits itself from even considering the higher spaces which it cannot experience; for I know it more than most. I had never intended to reveal to anyone the proofs you passed on to me, yet my Ministry learned of our relationship. Your rudimentary outline for tracking statistics in your own game inspired me to replicate the same process for my own; however, the prospect of the two-dimensional mind being able to expand itself so far was only attainable at a higher state. Namely, the monarchy has officials in every corner, and my attempt to incorporate tracking data triggered a worldwide alarm that an individual who hadn’t sworn secrecy was even minorly aware of the Sphere.

    Years have passed since I began to wonder how this “epidemic” would conclude, and I’m sure even more will pass before I’m any more aware. I’ve attached the following documents as a reference for why the concept of your branch of tracking statistics should be released to the public, and how my story may be of relevance to your own futures.

    Best regards


    • I Accidentally Invent Basketball

    Picture the three-dimensional depiction of a tesseract: a singular cube within a larger cube with its corresponding corners attached with slanted lines. Given the fourth spatial dimension can be represented on a surface two dimensions below its own nature, then imagine the ease with which I was able to visualize the third spatial dimension. I had no intention of discovering a non-planar surface that could exist outside of my own world, for it was an inadvertent finding. It was a result of my stint as a senior analytical researcher for the aggregate National Ringball League (NRL). It may seem an unfamiliar sport, although you’re likely more acquainted with it than originally thought to be.

    Ringball is to my world as “basketball” is to yours. Similarities include teams of roughly thirteen players, five on the court at a time, in a sport demanding high levels of agility and athleticism. The goal of an individual possession is to “score” the ball (known colloquially as a “ringball”) into a circular enclosure known as the “ring” (what you would refer to as a “hoop”). The limitations of the world made it so that actions in basketball like dribbling are non-factors, which in turn eliminates the need to check for carries and travels. The most obstructed aspect of ringball is the “shot,” or how players score for their team. Since no one can jump, field-goal attempts are analogous to “bowling,” with the ring acting as the single pin and defenders working against the shooter to prevent the shot from going in. Otherwise, ringball and basketball are nearly identical.

    I’d spent my early years in the workforce as an apprentice to Greg Richards: the original analytical pioneer in ringball, the first to ever track the tabular summaries of games, which supposedly encompassed the entirety of notable actions from a player in points, field goals, rebounds, assists, and turnovers. The world was captivated by Richards’s implementation of a smarter, savvier method to evaluate players, and he eventually became the sport’s most revered figure. My apprenticeship was earned largely in part to tracking hundreds of tabular summaries by hand, and including the differences between rebounds grabbed on offense and defense for the last fifty or so. I’d long suspected the hindrances of then-current techniques due to Richards’s discreetly operating for the Constitutional Monarchy and his hesitance in our time.

    As Richards took me under his wing, he’d led me to believe the nature of his titles as “consultant” was unequivocally true. His reputation and public image were perfectly-rational and justified reasons for Richards’s undertaking of the position for which he pledged to perform his best in properly distributing the relevant information on the league’s players and teams. However, as I began to understand the nature of my apprenticeship which was largely of face value, I discovered Richards’s relation to the Constitutional Monarchy: for a strangely ambiguous and unknown reason, he’d been assigned a direct pipeline to our Constitutional Monarchy which acts as the sole governing body of my world. Although I may have been a fool to overestimate the value of a studentship under a man whom I’d seemed to surpass in analytical intellect, I hadn’t been unjust to question the meaning of the pipeline.

    I was of such skepticism that I asked Richards why he needed a direct line to the world’s most powerful institution, to which he responded with a thought along the lines of how ringball’s growing analytical techniques were of higher mathematical quality than any other field, and how a strong relationship with a man of his significance related to the subject would benefit the intelligence of the world. As a practitioner of ringball analytics, even I was taken back when hearing the degree to which the monarchy valued its significance. I conceded the potential reason for how the conceptual integrity of the field could provide an alternative solution to another, although I’d grown to consider the creation of the tabular summary and its future additions to be rudimentary and simple relative to the potential the field held. I’d certainly pondered the growth of the field; nay, mathematics in general, and how it may extend past its geometrical limits.

    I’d had spurts of true skepticism from time to time since my discovery of the relation between Richards and the monarchy; for although his reasoning was certainly and potentially valid, a strong inkling of seeming coldness traveled through my veins as the prospects of its true nature passed through my mind. I found myself having another sleepless night due to my growing distresses, and chose to travel down to a team’s arena Richards had given me a key to for the fifth anniversary of the date since the mentorship had begun. My recurring thoughts came as I set sight on the ring from the midcourt line for a numbered time I could no longer count. NRL ringball had been played for more than twenty years at the time, yet the most efficient scorers scored a mere twenty percent of their attempts. As the primary basketball fanatics you are, imagine the difficulty of scoring the ball in that sport if all five defenders were capable of levitating to the level of the net.

    Mean shooting percentages would decline to historical lows and raw defensive efficiencies would rank as highly as they had ever been. Take the example of the 1963-64 season of my game, the last in which I was employed by the NRL. The average number of field-goal attempts for one team was 8,000 shots, and 1,064 of those attempts were made, which resulted in a mean conversion rate of 13.3%. The corresponding season in the National Basketball Association, as I’d later learn, saw the same figure at 43.3%. Basketball’s offenses haven’t yet understood the importance of shooting arcs, mostly because they don’t have the relative comparison of ringball as I did the inverse. Despite the norms of the sport and a general acceptance of low percentages, the number of analysts attempting to uncover a more efficient shot was pitifully low.

    As I stood in the middle of the floor, I reminisced on my original observations on the art of scoring in ringball, down to its bare essentials. Well, the only way a shot can be made is if it travels across the court at just the right speed and angle to outmaneuver the efforts of its defenders. Theoretically speaking, the optimal way to reform the inefficient field-goal would be to alter the path of the shot itself. However, there were no practical means to establishing, say, a new direction of… and that is where I stopped myself. Let’s tinker, I thought. I’ve already come all the way here. If I were to take a shot in a new direction, how would that be? Clearly, there were inherent physical limitations to the practicality of the exercise. If I were to make use of a new direction, how would I know “where” it would be and how to angle my shot? I proceeded to seek a blank piece of paper that would eventually destroy the world.

    How did I arrive at the arena? I asked myself. The route taken to the stadium from my house was roughly five miles southward. How did I move to the half-court line from the main entrance? I moved roughly thirty meters eastward. I had drawn two perpendicular vertices, each on their own planar surface, an image that was of no initial significance. It was simply a representation of the directions in which I had traveled to arrive at the midcourt from the entrance of my home. They were the two paths of travel. But if another were to exist, I had expected an additional third would follow an apparent dimensional trend: the new direction would be perpendicular to its predecessors. As is with every case of exploratory research, I had encountered an immovable obstacle: there could be no perpendicular direction to the two-dimensional axis, as no added line would ever maintain a ninety-degree angle to either of its companions.

    A trend had been clearly identified, yet the physical limitations of the world halted further progress. I had lost focus on numerous initiatives due to their practical inabilities, whether it be for methodological or technological blocks, which meant the prospect of warping the entirety of the world was an obstacle that could not be conquered. Failure was far more than an acquaintance to me, a natural stage of analytical development, so I had then felt no regret in not seeking an alternative solution, for the situation seemed far too impractical and outlandish and impossible to even begin with. I left the stadium and went to sleep, supposing any considerable revelation would be made during a more non-strenuous task. It was a practice I had adopted as a result of conceiving the offensive versus defensive rebounding splits as my mind was descending into a deep sleep, seeming premeditated strikes.

    Even a moderate sleep was able to trigger the fitting conception. I maneuvered through a string of memories in my sleep and found myself back at the arena, positioned at the midcourt once again. The paper was in its original place with its original drawing gracing the surface. Regaining the same rudimentary state of mind I had when first conceiving of the third dimension, I called forth one conclusion I had already made in my subconscious: the paper maintained the qualities of a dimensional reality in which I was occupied, meaning its normal surface wouldn’t provide a direct representation of the third dimension. I had to treat a two-dimensional depiction of a third dimension abstractly compared to the surface I had available to me. It was then when the constant string of metaphysical concepts drew forth a new form of perpendicularity: one with its directions not only perpendicular to each other, but to the original surface itself.

    The rest of the work was fairly simple, as three-dimensional inhabitants came to represent the fourth and further dimensions on even surfaces of only two dimensions. With the world’s intellectual commencing of the third dimension, I returned to the original prospect of a new ringball shot. Assuming utilization of the higher dimension, the ball would travel “overhead” relative to defenders and descend to the ring, following a trajectory similar to the path of an attempt in basketball. If it were able to be implemented into ringball, it would not only eliminate the inefficient mechanics of the traditional shot, but it would alter the normal positioning of defenses to an unknown “height” relative to the ring. The hypothetical third-dimensional reality would create a version of the sport more beneficial to offenses but a whole new one on its own, one that would coincidentally turn out to be your “basketball.” That, in layman’s terms, is how I accidentally invented basketball.

    • I Meet an Invisible Stranger

    “What are you doing here at…” Richards said as he looks at his watch. “…nine in the morning?”

    “You have to see this!” I quickly revealed as I welcomed myself into his home. I uncovered the sheet of paper, now bruised and crinkly from when I had rushed to leave for Richards’s, and set it on his dining floor. “The entirety of ringball, nay, the world could be changed by this. Look!”

    Richards, having clearly woken from a deep slumber merely minutes ago, gave a dazed glance at the paper as he walked toward me. “Give me a minute,” he said as he rubbed his eyes. Richards picked up the sheet and held it to his face, squinting his eyes as he read. As soon as he’d entered his gaze, he left it with an expression only justly recognized as one of pure irony. Richards turned to me with his look and asked, “What exactly is this?”

    “I was considering the historical inefficiency of the field-goal attempt,” I said. “It could potentially be reformed to maximize offensive potential. Long story short, I outlined a theoretical third dimension. A shot within its boundaries are obviously out of reach, but I thought back to the time at which you revealed to me the nature of your connection to the monarchy. Wouldn’t the prospect of a third dimension with a reasonable framework be of importance?”

    “Well…” Richards stumbled.

    “Unless…” I began.

    “No!” Richards intercepted. “Of course not… I’m a relative stranger to these concepts, although based on my previous knowledge, it looks promising.”

    “Perfect,” I remarked. “Would you mind sending it to the monarchy for me? I haven’t the connections you do.”

    “No,” Richards said in an alarmingly flat tone. He handed me the sheet back and walked me to his front door. “You can show it to them yourself.”

    I soon found myself facing ten other individuals sitting on the other side of a long, stretched panel shaped like an arc rounded at the corners. I felt the eyes of the council’s stare at my skin, and with Richards’s firm-enough grasp to prevent me from exiting the room, I was seemingly deadlocked for a reason I had yet to realize. Richards walked me to a designated circle at the foot of the panel, after which the doors were promptly closed and he circled around to who appeared to be the chairperson. Richards met her periphery to exchange words, which left the chairperson no more discontented than she had seemed before.

    “Nora,” Richards whispered to me as he made his way back to the entrance to the room.

    The chairperson narrowed her gaze on me. “Mr. Richards tells me your claim to have diagrammed a third… dimension. Is this true?”

    I had already started to sense the uncertainty of what appeared an emergency meeting, although the atmosphere wasn’t restricted to my end. “Yes ma’am.”

    After a long pause, Nora follows with, “Explain it to me.”

    I turned to Richards with what must have been a distinct look of confusion, to which he responded with a subtle gesture, Go ahead. “Well, I am currently an analyst for the NRL, which Mr. Richards may have mentioned. The current shooting techniques are very inefficient, so I outlined the possibility of a third hypothetical dimension in which a player could position the ball on a surface perpendicular to our current dimensional plane. Therefore, the ball would travel “overhead” and “fall” into the ring.”

    Nora gave a puzzled expression, after which she responded with, “I don’t quite follow.”

    Richards hinted for me to pass to her the sheet. “Right,” I said. “… the sheet.” Richards walked the paper to Nora, who gave a thorough review of the image until she saw it fit to resume the conversation.

    “This was an… original conception?” Nora asked.

    “Yes… ma’am,” I replied. ” Thought it up just this morning.”

    With an unforgettable guise of dubiousness, Nora returned to her train of thought. “Have you possibly received any unplanned visitations in the past weeks?”

    “No…?… ma’am,” I responded.

    “I recommend, mister…?”

    “I apologize, my name-“

    “I recommend you seek deliberate conservation of this subject. I understand the circumstances of the situation, although you will simply have to consider the weight of my words in addition to the remaining council when I urge you to contain this from the general population.”

    I was strongly taken aback by Nora’s remark. I feigned a look of concern to Richards which was followed by mild humored confusion. “I’m sorry, what?” I responded. “I was told by Mr. Richards that the monarchy would benefit from the use of the techniques used in ringball; and when I’ve chosen to come forth with what may be the most significant of all, you don’t want to inform the rest of the world?”

    “That is correct,” Nora replied.

    “Why?” I questioned.

    Nora had already started to head toward the back of the room, at which point she turned a glance in my direction. “It is only for the betterment of mankind that you would not outlast your… convenience.”

    Richards started to walk me out of the room, and said with a sympathetic tone of truth: “Trust me, kid. If I did not know this was in your best interest, I wouldn’t suggest you comply.”

    I turned back to the panel, watching the council members make their way to ten different exits, one each seemingly assigned to one designated spot. I tried to catch a glimpse of Nora’s expression one last time, for the situation seemed far too surreal to have made a reasonable conclusion on its meaning at that time, but Richards urged me southward. 

    The ordeal was a firm nail in the coffin to assure me of the practicality of the third dimension, that it truly existed beyond the scope of my existing universe. However, I was compelled to believe the words of my mentor. He’d feigned looks of certainty the entire meeting, yet his final sentiments conveyed a sense of truth that I could not deny. I had not felt a particularly strong or emotional connection to the higher dimension, nor had its original purpose to vitalize the ringball shot signified any importance beyond its theoretical qualities, which allowed me to subside that entire day within the fortnight. My belief in three-dimensional realities had increased, but its relative insignificance was enough to keep my mind content.

    I spent the next two years of my life as I had spent the previous two: not in a bore, per se, given my independent discovery of the third dimension. However, the finding wasn’t of use in my daily life, so I continued with the former as if the unveiling of depth were a mere concept that had not been proven, which it was at the time. It wasn’t until I was greeted by an invisible stranger when I chose to further pursue the third dimension. I returned to the arena well past midnight, as I had when first conceptualizing the new ringball shot, and was subsequently introduced to the strangest stranger I had yet to meet. He stood at the ominous midcourt line, facing the eastside ring, seemingly unaware of my presence.

    “Excuse me?” I asked.

    The stranger turned to face me with earnest eyes.

    “How did you get in here?” I followed with.

    After a prolonged silence, as quickly as he had materialized, he disappeared. I fell backward for a short moment, astonished. A second later, he reappeared in the same spot. I had started to suspect the late-night tiredness had begun to assume my mind, but as the man started to move toward me, he spoke.

    “You were right.”

    “Right about what?” I responded.

    The stranger paused. “I just… took a jump. Care to take a gander as to what that means?”

    I instantly flashed back to the meeting with the monarchy, with the entirety of the council members sitting at their panel, and how the chairperson “Nora” veiled a subtle threat on what I interpreted to be either my freedom or my life. If I were “right” on the matter of a subject concerning a stranger, one to show himself in a heavily secured professional arena with definitive language on a very vague premise, it would certainly have to be related to my discovery of a third dimension. This conclusion was enough for me to recognize the possible connection the stranger held to a three-dimensional world, so I laid out my initial framework.

    “I couldn’t see you for a whole… second?” I began. “I can only presume you’re here on the matter of an extra-dimensional reality. Therefore, my lack of sight in that particular moment must be related to one of the qualities of the third dimension, for I would know if there existed cloaking or invisibility devices… If a two-dimensional being were to set his eyes on one of three dimensions, I would expect the dimensional structure of the viewer, that being the being of two dimensions, would have a physical hindrance with two-dimensional eyes, thus not being able to witness movement on the third-dimensional axis. That means… your jumping is movement in height?”

    The stranger held my gaze for a quiet moment and then released his tension. “Thank goodness, I got the right guy! Do you know how many times I have gotten it wrong? Evidently, just look at your world right now.”

    “Where do you come from?” I asked. “What are you doing here.”

    “Do your people not greet their guests?” the stranger replied. “Anyways, my name is Harvey. I come from a place just outside a land called… New England. Do you know where that is?”

    “No,” I quickly responded. Harvey conveyed a look of suspense, and I called on his social cue. “My name is Tom.”

    “Alright, Tom,” said Harvey, as he walked closer toward the exit. “Let’s get out of here.”

    “Well, where are we-” I started until I felt an inescapable wave of tiredness and was forced into sleep. I immediately regained consciousness in a new body. I felt stretched as though I had not known the feeling, which I hadn’t. My initial reaction was to look in a direction I’d never had the ability to observe before. Above me was an infinite expanse of black sky dotted with luminous points that radiated waves I could only interpret as not two-dimensional. I turned my head south and saw a shaded field of cultivated land that extended nearly as far as the horizon. As I noted the point at which the sky met the earth, a curvature was clearly visible. I had seemed to enter the three-dimensional reality, one in which the world was round. Then I realized I was effectively flying.

    I turned to my left and saw Harvey, floating as calmly as could be, lighting a cigarette in the middle of the sky. He caught my glimpse and frantically put the lighter back into his pocket.

    “Sorry kid,” Harvey recompensed. “You were out for a little while. Had to stay entertained somehow.”

    “Okay, wow!” I smiled. I couldn’t refrain from feeling joyous, being able to fully experience the third dimension likely for the first time ever among beings of lower-dimensional realities. I realized the improbability of the event. “How exactly am I, er… seeing this?”

    Harvey let out a puff of smoke from nearly-pursed lips. “Android,” he replied.

    I let out a justifiable laugh. “Whatever that may be, why is it identical to my actual body?” I asked.

    “Don’t want to ask too many questions, kid,” Harvey responded. “I’ll do the talking now, alright?”

    “Sure,” I said.

    Harvey spun the lighter on his finger. “You are seeing into our third dimension right now; which, congratulations on discovering by the way. I assumed it was you based on what I was able to see during your ‘meeting.’”

    I pointed at him. “You were there?”

    “Yes.”

    “How?”

    “Less talking, kid!” Harvey exclaimed. After he settled down, he gave a light-hearted shrug. “All of you fools can be further fooled when I jump up and down over and over again. None of you can see a thing!”

    “Huh…” I marveled. Perhaps Harvey was a questionable character, and the surface details of his plan seemed as funky as any, but he had managed to infiltrate a world government regardless.

    “I… am here…” Harvey stated as he retrieved an apple from his other pocket and took an awkwardly-long bite. “… because you did not one, but two, things. Well, you are one thing and you did another, whatever… You’re a… ringball analyst, correct? That’s what they call it? Our equivalent is called basketball, the shot trajectories for which you properly conceptualized, and coincidentally discovered the possibility of a third dimension. That’s what you are as well as what you did.”

    “Er,” I mumbled. “That is correct, but… why take me out here and show me all this?”

    “… As I’m sure you’ve managed to put the pieces together.” Harvey took a very passionate bite out of his apple. “Oh yeah…” he continued with his eyes set on the apple, transfixed, with a world-class grin on his face. “Whoops, sorry kid.” Harvey snapped back into reality. “Anyways, you’ve probably figured out that your world is full of degenerates and hypocrites.”

    “Well, thanks…?” I replied.

    Harvey’s eyes widened, clearly worried I had assumed the wrong impression. “No, no, no, not you kid. You’ve got some stuff up there, you know? However, the majority of your world reflects its dimensions. Exempli gratia… wait, can you read Latin? Nevermind that. A two-dimensional being usually has a two-dimensional mind. It’s not that they can’t comprehend a third dimension, per se; rather they choose not to. You, my friend…” Harvey pointed at my chest. “… are the exception, which means I have something important to tell you.”

    “I mean, okay,” I replied. “You’ve just insulted everyone I’ve ever known and loved, but okay. What is this ever-so-important piece of information you have for me?”

    “Don’t get sassy with me, kid!” Harvey shouted, pointing his now ominous finger at my neck. “But anyway, I’ve hit a lucky streak with my work. I’m a basketball analyst, you see, basically the same job as yours just with a shot in three dimensions rather than two. So, the one you conceptualized. I’m sure you’re a skeptic of the… what do they call it, tabular summary?”

    “Yeah, partly,” I said.

    Harvey paused. “That’s really what you call it? Whatever. Anyway, we call it the “box score” here on Earth. We’ve got a few more stats we track, like steals, blocks, fouls… I’m surprised you hadn’t further questioned that Richards guy on why none of you track defensive stats.”

    “I mean, I have asked him before,” I said. “It just never received any serious consideration.”

    “Regardless,” Harvey said. “Perhaps you’ve had an inkling of this, but the box score… I’m just going to call it the box score from now on, okay? The box score is a poor indicator of how good a player is, which you may have picked up on. I created a new type of tracking statistic with a premise I think you’d find mildly intriguing.”

    “Okay, shoot,” I replied.

    “I’ll begin with a question… What’s the point of having a player on one of your ringball teams?”

    “Excuse me?”

    “Come on! If it’s such a basic question, you’ve got to know!”

    “Well…” I said. “Players are acquired and signed to improve their team. That’s a part of my job: choosing between players.”

    “See!” Harvey marveled. “I knew you weren’t a lost cause! Alright, second question: define a team’s success.” He took another massive bite from his nearly-finished apple.

    I granted a fairly clear answer. “The most basic form of success is winning games,” said I.

    “Correct again,” Harvey replied. “Next question: how do you win games?”

    “By outscoring your opponent,” I said.

    “Outstanding!” Harvey exclaimed. “Now that the premise is laid out, I’ll ask you one final question: wouldn’t it make logical sense to therefore say the best player or players have the most positive impacts on the scoreboard? Say, their team’s point differential?”

    I had never considered nor conceived the approach Harvey was taking. It was excessively simple yet undeniably true. If you broke either my or his game down to its most rudimentary qualities, he was correct. For what did I know up to that point? It should have been fairly obvious there was no definitive value to an assist, a rebound, or a turnover. However, my two-dimensional mind was likely incapable of constructing the logic in the first place, I’m willing to admit.

    “You’re right,” I replied. “I’d never thought of it similarly, but it’s correct. If you’re truly after team success in the player selection process, you should use your framework.”

    “The best part isn’t even the idea,” Harvey said with a mouth full of a sandwich that reeked of tuna. “That tracking metric I mentioned, it relates the difference of his team’s points to his opponents when a given player is on the floor. But we use something called pace adjustments… normalize it all to a hundred possessions. When Jimmy John is on the court for twenty possessions and his team outscored its opponent by one point, Jimmy has a plus/minus of five. The name is still in the works, may have borrowed it from hockey. Don’t ask what hockey is.”

    “Interesting concept,” I replied. “I agree with the premise, but there’s one last detail you’ve left out.”

    “That being..?”

    “What role do I play in it?”

    “Excuse me?”

    “You seemed to have, what, drugged me? You took me to an extra-dimensional land and revealed the most hidden secret in the whole world to… tell me about a basketball stat?”

    “Right! Nearly forgot,” Harvey said, his hands fumbling the sandwich as he rushed to finish his sentences. “I need you to get back into another meeting with your monarchy.”

    I initially refused to accept the truth in his request, that it was more likely to merely another one of his one-liners. “Okay… no,” I replied. “But even if I were to, how and why?”

    “You’d have to do or say something to draw their workers out, snatch their attention. Once you do that, you get in a meeting with them, reveal a mildly concerning piece of information that suggests one of their citizens is getting close to conclusive proof of the third dimension, which would hopefully reverse some of the backfire effects in the majority of your population.”

    “Again… no,” I said. “The last trip I would want to take is back to that council. Do you not remember their poorly-concealed threats?”

    “I won’t sugarcoat it, kid,” Harvey said. He took a butter knife and a jar of peanut butter from his coat pocket and opened the top end of his sandwich, slowly spreading a new layer onto the remaining spinach and tuna. “It would definitely be a risk. Of course, to take one like that, you’d need a reason.”

    “Indeed, I would,” I remarked.

    “Anyways,” Harvey continued. “As I was saying, your people are… set in their ways. If you provide them with contradictory evidence to a long-held belief, their minds short-circuit. They don’t know how to react. Therefore, if you want to break that streak, you’ll need to snap them out of it. Wouldn’t you want that?”

    “Ideally, yes,” I replied. “But not enough to risk my life for it.”

    “Tommy, Tommy, Tommy!” Harvey said. “If we can pull this off just right, the entire… well, your entire word will reform. There’s no real reason to ignore the realities that exist beyond their own at this point, is there?”

    I pondered his explanation. There certainly existed a strong hindrance in the minds of my people up until then, and to reverse the effects would take one of the largest efforts known the mankind. However, I considered the odds an opportunity to do so would ever appear again. Given the parameters of my own situation, it would take another rediscovery of the third dimension, which may not happen for hundreds or thousands of years, or ever. If I were to involve myself in Harvey’s ordeal, the pretense to enter the council would have to be airtight.

    “If… I agree,” I proposed. “… what are the terms?”

    “Well, I was thinking the safest option would be the metric I call Plus/Minus. Slip the idea to Richards as if it were your own. Obviously, the metric isn’t something anyone in your world could freely invent, so it would raise enough suspicion to lead to another meeting, but not enough to conclusively prove your connection to the third dimension… The real one, not the conceptual one.”

    “Okay,” I considered. “No.”

    “Come on, kid! Do you know who we’d be taking down here?”

    “No, but please tell me.”

    “They’re known as the Monarchical Establishment for the Detainment of Interdicted Apprehensions. How does that sound to you?”

    “It sounds like someone was eager to spell ‘MEDIA.’”

    “Alright kid… Are you in or not? I’m nearly done with all the meals I packed.”

    My mind returned to the hesitance of Richards, the demeanor and nature of the monarchy, and the limitations of even myself that I wanted to expand. “I’ll do it,” I replied. “I’m in. But before I make a firm commitment, I need you to acknowledge something for me.”

    “Okay, Tom,” Harvey replied, with strong relief in his eyes. “What would that be?”

    “You explain to me that my people have a certain ignorance of them. Whether it’s due to their two-dimensional reality or their own chosen limitations, it is there. However, couldn’t the same be said for all beings?”

    “I’m not following,” Harvey responded.

    “Harvey, do you believe in a fourth dimension?” I asked.

    “Alright, kid. Where are you getting at?”

    “What do you call a three-dimensional square?”

    “Cube.”

    “What would you call a four-dimensional cube?”

    “Well, there was one guy several decades ago… Hinton. He used to call one of those a ‘tesseract.’”

    “Do you believe it exists? The tesseract?”

    “Now you’re just grasping at straws, kid.”

    “If you can’t display a mindset beyond that of my own people, ignoring the absolute advantage you have of living in a three-dimensional world and rather look at the matter relatively, how am I to believe you’re any better than those we are supposedly against?”

    “If a fourth dimension truly existed, I’d know. My world would know.”

    “How?” I asked. “My people would never have discovered the true third if someone, being you, hadn’t been able to confirm it for us. There could be an infinite number of dimensions in theory, yet you deny the existence of any past a third because you simply can’t see it?”

    “Consider my offer,” Harvey concluded before he took a remote from his left pocket, pointed it at my head, and clicked.

    • I Accidentally Destroy the World

    I woke up in my previous body, detached from the machine Harvey had used to allow me to see the third dimension. Despite not possessing the spherical eyes I had previously, I could still picture depth and height in my brain. The last statements Harvey left me with were not of my highest agreement, but one sentiment he gave remained in my mind: that my world is not incapable of seeing more, they choose not to. 

    The next day, I went to Richards’s office and discussed the potential of relating a player’s impact to his team’s point differential, and even spun my own ideas of how to improve the metric: methods to further isolate the value and forming more conclusive coefficient estimates. Richards conveyed the same look of doubt he had two years previous and told me it was an issue the monarchy was more fitted for. Perhaps he should have expected more restraint on my end or resistance to seeing Nora and the council members again, but my feigned looks of concern were enough to convince him I hadn’t expected a second visit.

    I found myself back in the same room with the same individuals, each in the same positions and for the same purpose: to detain my learning of any further knowledge. Richards repeated his earlier act of informing Nora of my finding, likely how its complexity is beyond reason for a “two-dimensional” mind. I was certain the monarchy was aware of the third dimension, and they proceeded exactly as Harvey suggested. All the members were settled in their designated circles, Richards circled back around to me, and the second meeting began.

    “Mr. Evans, I won’t dance around the issue at hand. I’ll give you the complete details of what we know. Is that alright with you?” asked Nora.

    “Yes ma’am,” I said.

    “We know you’ve been contacting a being of the third dimension. We don’t know whom or why, but we know he is of a higher reality.”

    My lungs felt as though they had frozen over. I found myself struggling to breathe, hyper-aware of the sounds of my exhalations. I had never been in an interrogatory setting before. Perhaps it was my inexperience, my surprise, or my lack of faith in the ideals Harvey was insistent upon, but I found it nearly impossible to continue and keep up the charade.

    “How would you know that, ma’am?” I cautiously asked.

    “There were more than twelve people in the first meeting, Mr. Evans,” Nora replied. “A man was seen disappearing and reappearing during the entirety of the congregation, although he was remarkably quiet… Regardless, your idea of the third dimension and this invisible man were enough to confirm you had either already been contacted or would be contacted by the individual. Would you confirm this story?”

    Given the details of Nora’s story, it’s clear the monarchy had no conclusive proof of my communication with Harvey, despite their placing him at the proper location and the ability to reasonably presume a connection between us. The legalities of the matter would have prohibited me from any rightful imprisonment, given the act would break the world’s laws, although Harvey’s disdain of the two-dimensional mind led me to believe the lawfulness of the situation wouldn’t concern the monarchy. They would eliminate the chance of my spreading the proof of a third dimension in any manner, lawful or not.

    The unspoken truth between the council and I agreed the both of us was aware of my knowledge; but with the hint of uncertainty I was granted, I made the quick decision to swallow any pride relating to the government’s treatment of its people and chose the more secure, more legal route. “No, I can not, ma’am.”

    Nora transitioned between expressions of frustration and amusement in the seconds following my statement, her jaw trembling with eyes of sharpened disdain. She cued to Richards, the latter of whom released his grasp on me. Thank Harvey, the largest improvisation of my life had managed to do the trick. Although the air whispered the truth that Nora and the council were fully aware of my connection to Harvey, they were not willing to act on any of the precautionary measures they may have planned on implementing; at least, not until a later date. I saw myself out of the council, turning back one last time to replicate Harvey’s apple smile directed to Nora. I did not even need to hold her gaze to feel her anger from tens of meters away.

    I returned to my home in mild exhaustion: a tired and unprocessed mind from the events of the previous mind along with slight bodily fatigue from the day. However, I felt a strong sense of accomplishment and optimism. As Harvey had managed to infiltrate the government, I had managed to debilitate its intuition, use their own logistics against them. I was not naïve either; I had already expected further action from the monarchy, but the protection of the law was enough to ease my mind in the evening. I felt a strong hesitance to sleep early, however, likely due to having entered another dimension the last time I’d slumbered. The controlling factor was the plan I had unconsciously formed in the preceding hours: to spark a widespread belief in a dimension of three axes. 

    Although mine was no household name, I had built a formidable reputation for myself as one of the world’s leading ringball analysts and mathematicians, the reasons for which I would make occasional appearances on the leading sports network: the Entertainment and Sports Broadcasting Network, or ESBN, to discuss the league’s bright, new players or take a deeper examination of my analyses. I concluded the most effective way to spread the word of an extra-dimensional world was to break the script in my nearest scheduled slot, that in the following fortnight. I had figured the two-week period would lightly settle the minds of the council, to perhaps suggest I would not take any immediate action. Additionally, the duration would ensure the monarchy would not have the necessary time to plot to potentially retrieve me from mainstream society.

    Promptly, I found myself facing augmented light sets and cameras at the end of the waiting period. The introductory message to my appearance began, although I wasn’t truly listening, after which the cameramen angled their device in my direction. I took a silent pause and proceeded to commence the speech I had spent the previous two weeks drafting. I briefly remember my words on conceptualizing the third dimension, my first meeting with the world monarchy, and a segment of my mid-flight conversation with Harvey. The last trap I had not expected was the all-seeing status of the monarchy, for they truly had eyes and ears in all places. My last recollection of my time on the air was the sound of a dart, and my eyes went black.

    I remained in a perpetual state of loose consciousness for the following weeks, with vague memories of my journey onto the train, aided by the careless hands of the monarchical workers, along with a more distinct image of Nora’s pleased face as I was thrown on board. There were deep, booming sounds of gravel and dirt escaping their previous bounds of the ground, entire oceans parting way for the massive, yet two-dimensional, absences of water. There were vague remarks as to how Harvey’s statistic could bleed the same fateful events into the three-dimensional world. I was mostly asleep the entirety of the week following my television revelation, but I’d learned enough: the world had imploded on itself, its people enraged by the government, others in support of it. I was never aware of the details, but it was clear military warfare became a heavy involvement.

    If my world were three-dimensional, my waking image would have been a bronzed, steel wall providing the perfect view of a sky claimed by the ashes. My immediate reaction was not only the recognition that the plan had worked, for the world had been completely informed of the third dimension, but that the trade-off was an inescapable, inevitable series of destruction: another effect I had failed to anticipate. My next reaction was to absorb my surroundings. I had caught a mention of a train, one of which I was certainly on. The oxidized walls, the rusted bolts, it was a train that had been constructed some time ago. The air on the outside was certainly too polluted to safely breathe, which led me to contemplate my being there. I had thought, perhaps, my status as a threat had carried over, although the rest of the world knew what I knew. I like to believe it was due to my connection to Harvey, one that could potentially pose an even greater threat to the world order, one that could bleed into the higher dimensions.

    Regardless of why, I found myself on the train. I could elaborate on the seven years of my life on it leading up to my current writing, but the commencing letter discloses all the necessary information. My world was more susceptible to its end more than Harvey’s, whose publications could potentially provide the same reform to his world that he promised mine. I mentioned Harvey’s hesitance to accepting the tesseract, one that would certainly be amplified by the rest of his population. However, he had recognized the possibility, as did the rest of the Earth. As the train passes my once beloved stadium, I’ll pass this letter over, triggering what would likely be another of Harvey’s reappearances. For now, I’m bound to a train named for the skyline its viewers would endure for the remainder of their lives.


  • Stephen Curry | 2016 Evaluation

    Stephen Curry | 2016 Evaluation

    “Stephen Curry in 2016 is more fun than anything, maybe ever…” – SLATE

    The greatest point guard of the century set the Bay Area into a Warriors frenzy with his electric three-point scoring and the team’s dynastical tendencies, with records being broken left and right. Curry’s season may have been highlighted by 402 three-pointers made and a unanimous MVP, but very few people knew how good he actually was that year, even those living in the eye of the storm. He entered rarefied air in his ’16 season, and no player since then has yet to match it. But exactly how good was he when he was drilling half-court shots seemingly at will? With Curry’s evaluation, I’ll try to answer a long-thought question: was Curry’s 2016 campaign the greatest offensive season in league history?

    Scoring

    Curry’s scoring alone took Golden State’s offense to dynastical levels. During possessions in which he attempted to score, defined as either a true shooting attempt or a scoring turnover, the Warriors posted an offensive rating of 127. That was a whopping +21 relative offense, and there’s potent evidence behind a figure of such a magnitude.

    Due to Curry’s historical outside shooting, his inside scoring received far less recognition despite being one of the skill’s best. Among players who played for more than a thousand minutes, Curry was thirteenth in field-goal percentage on drives; which, considering his 6’3″ stature, is geometrically more masterly. A part of Curry’s surprising prowess in the paint was his strength; according to CBSSports, he could deadlift 400 pounds in the summer of 2016, a mark no Warriors could top except for the 6’11”, 255-pound Festus Ezeli. Paired with a solid motor, Curry was able to penetrate defenses with relative ease.

    He was a very prolific paint scorer, having taken 22.5% of his attempts from within three feet of the basket. With respect to Curry’s three-point barrages and smaller stature, his frequency was unexpectedly high. He was also able to capitalize on these high-efficient looks at a 69.6% clip, strikingly greater than the league-average of 62.4%. Curry would often opt for these shots to avoid double teams on the perimeter, swinging around the arc, and finding an angle to drive. His size and vertical leap alone weren’t enough to dominate defenses in the post, so during his forward-facing drives, Curry would either go take an early step to gain ground against the opponent or his premier center of gravity. Learning to take the toll of movement with his hips instead of his ankles truly unlocked Curry’s greatest interior capabilities.

    The other component to his elite finishing was Curry’s ability to split defenses. As the greatest shooter ever, he also became the most gravitational player ever. He’d rarely not see multiple defenders in his periphery when operating on the perimeter, yet it was never destabilizing. If two defenders went on either side of Curry, he’d split their position with surprising quickness and agile lateral movement. The aforementioned utilization of his hips allowed him to change direction with fast pivots, which often left defenders in the dust. Curry was one of the league’s best paint finishers, and it was the weak point of his scoring résumé.

    Everywhere outside the paint was Curry’s domain… not that the paint wasn’t already his in some form either. He stuffed the stat sheet with a collection of absurd shooting scores that paint an extremely flattering picture of Curry’s outside scoring, a strong point of which was how he and his teammates set up his scoring. Curry was one of the most efficient catch-and-shoot scorers in the league that year (68.6 eFG%), only behind J.J. Redick for players who took more than 400 catch-and-shot field-goal attempts. However, contrary to the traditional tendencies, Curry’s efficiency didn’t rapidly decline on non-assisted attempts. He was the league-leader in effective field goal percentage on pull-up shooting (61.9%) for players with more than nineteen attempts. For reference, Curry took 687 of these attempts. The next most-efficient player to even take one hundred, D.J. Augustin, shot 54.3%.

    Curry wasn’t an “opportunist,” as many primarily catch-and-shoot scorers are. He was a master schemer, consistently creating his own shot while also being an elite catch-and-shoot scorer. 37% of Curry’s two-point field-goals were of teammate assists, significantly lower than the league-average of 51%. From three-point range, his figure is 55%, a large decrease from the league-average of 84%. It’s probable Curry’s scoring would’ve been more scrutinized if he were the product of a system in which he was set up for high-quality attempts by teammates more than himself, although this wasn’t the case. Curry’s status as an offensive engine wasn’t exactly in question, but the rates at which he creates his own field-goals further the idea that he was a peak offensive player during his second MVP season.

    No player has yet to match the historical contributions of Steph Curry’s outside scoring. He attempted a mind-boggling 886 three-point shots during his 79 games played, nearly 230 more shots than the second-place finisher in the stat (James Harden). Curry was surprisingly second in efficiency (45.4%), trailing only behind the Clippers’ J.J. Redick. However, Curry attempted more than double of Redick’s shots on far greater self-reliance, which suggests from an all-things-considered outlook, Curry was the most efficient three-point shooter in the league. Using the league-average three-point percentage as a relative comparison, Curry added 265.8 net points to the scoreboard through his three-point attempts alone. The efficiency and volume at which he made three-point shots make Curry’s ’16 significant in league history as the greatest outside scoring season ever.

    Yellow star denotes Curry

    The Baby-Faced Assassin had not only the greatest scoring season of the year (leading the league in both scoring rate and true shooting percentage, as well as being the only player to ever win the scoring and efficiency titles) but the history of basketball. Curry leads the all-time leaderboard in Backpicks‘s ScoreVal metric as well as (in theory) my own of similar nature: Scorer Rating. Given the circumstances of his scoring, and how his greater self-dependence is an indicator that his scoring statistics are more reflective of his true abilities than the average “opportunist,” it’s fair to say Curry had the strongest scoring peak of any player in league history. As the thirty-first highest peak in relative true “scoring” percentage (which uses a scoring turnover) estimates as a scoring attempt and the eleventh-highest peak in scoring rate with historic frequency, Curry’s mix of volume and efficiency was unprecedented.

    Off-Ball / Movement

    The next trip up Curry’s sleeve, and a large contributor to his assisted shots, was his world-class movement without the ball in his hands. An overlooked skill when it comes to an elite offensive player, Curry’s not often recognized for it compared to his eye-popping distance shooting. Fortunately, he was able to put it to good use as a member of the Warriors, a team with some of the most dynamic ball movement ever, comparable to the ’96 Chicago Bulls. Curry was a threat all over the court without the ball, keeping defenders on their toes with his presence alone.

    With the point guard duties he had, Curry would often start his off-ball stints at the top of the perimeter. He would primarily target either the corners or the paint, two of his most efficient ranges. To do so, Curry would often make slow rotations to a corner and let his teammates go to town. These made up a lot of Curry’s “excluded” possessions, but his positioning in these spots was another outlet for shot creation. He’d sometimes feign a backdoor cut to unclog a lane in which a teammate could drive: phenomena that would occur either starting at a corner or up top. Significant credit for this is due to his creation instead of his off-ball capabilities, but the grace and effectiveness with which Curry could feign cuts was extraordinary.

    Aside from his creation abilities off the ball, Curry’s movement itself rivals the all-time greats in the skill. He has a reputation for a game that doesn’t require the athleticism most do, but the quickness in his routes is a product of a strong physical foundation. The excess training of his hips provided an easier way for Curry to reposition himself on drives, otherwise known as changing direction. It’s how he gave a seasonal montage of possessions in which he was driving to the hoop and swiftly stepped back, showing an uncanny tendency to lose his defenders. Curry was by no means screen-reliant, but his ability to weave in and out of teammate screens and opponent setups was the boost he needed to improve his self-creation off the ball.

    Playmaking

    Even if Curry were a pedestrian scorer, his passing and creation would’ve kept him afloat as an offensive engine. The quality of his passing wasn’t the focal point of his playmaking, and the skill is accurately represented by his Passer Rating per Backpicks. Since his breakout ’13 campaign, the metric has graded him in the mid-to-high-sevens on the one-to-ten scale. A lot of his assists were products of his elite vision, which made him especially aware of the corners. With five teammates who shot higher than 40% on corner threes, a lot of these passes were tailored to Golden State’s roster. Curry was additionally proficient at splitting defenses with his quick bounce passes. A common trait among elite playmakers, he refined the tactic with his strong hips and vision approaching the hoop en route to his 1,261 points created through assists.

    There wasn’t an excess number of negatives with Curry’s passing. The notable ones include his tendency to overpass against taller defenders. During games against elite defenses (especially the recurring January 15th matchup against the Spurs), he’d find himself picking the ball up early, forcing a pass into the post or out to the perimeter. Defenders like LaMarcus Aldridge and Kawhi Leonard rushed Curry into these passes, and his intentions were clear: to avoid the long arms of his defenders and skip a pass to an open teammate. However, Curry would often underestimate the launch angle of these passes, and they’d gain too much ground before their final descent. The same would occur with some of his full-court baseball passes. The main theme with Curry’s passing deficiencies was that he overestimated the necessary distances for tougher passes, but the lower frequency at which these happened made them minor issues.

    PBPStats – a condensed version of Golden State’s assist network

    The Warriors were a movement-heavy team, having led the league in assists per 100 possessions by a significant margin (+2.6 assists), secondary assists, and assist points created. The nucleus of this action was made up of the team’s “big three” in Curry, Draymond Green, and Klay Thompson. Curry’s strongest link was with Thompson, to whom he assisted 209 field goals. He also assisted 139 of Green’s shots and 66 of Andrew Bogut’s. Based on the positioning of these players, it’s clear a lot of Curry’s playmaking was focused on or around the perimeter. He averaged 2.5 fewer assists per 100 possessions with his star on the arc, Thompson, off the floor. Curry’s playmaking was understated that year because of how many more shots he was taking (+3.5 more attempts per 100 from the previous season); but even then, his playmaking value was near the top of the league. Golden State’s passing and Curry’s efficient teammates counteract some of that deflation, but the confounding variables almost seem to cancel themselves out.

    Defense

    Curry is often criticized for his man-to-man abilities, and there’s some truth to that. He wasn’t the greatest at positioning himself, keeping a naturally flat-footed and unathletic stance. Curry had solid hands in these spots, covering higher and lower passing angles with either arm, although his 6’4″ wingspan made it slightly harder to effectively clog passing lanes.

    Among his more potent errors include mispositioning; he’ll sometimes miss a matchup entirely, the only other main instance of this being a tradeoff of his good rebounding. Curry would often lose his man positioning himself for the defensive rebound. This does make it a bit of a gamble, but the generally-high defensive rebounding percentages among teams (league-average 76.2%) made it so that only a small percentage of possessions would see these fallbacks. But Curry was a surprisingly good rebounder for his height, having grabbed 4.9 defensive rebounds per 75 possessions at a 2.9% clip, suggesting it was the best defensive-rebounding season of his career. 

    Curry’s small frame made it hard for him to stay in front of stronger matchups, so he’d sometimes be left in the dust on defensive possessions (just as he did to the NBA’s very best defenders). Ironically, Curry was given a taste of his own medicine in these stints. He was similarly susceptible to screen action, fizzling his entire value out against stronger defenders by entirely losing his man. The strongest positive of his man-to-man game is his ability to maintain space with his matchup. Curry can string together good defensive possessions when his matchups are moving laterally, keeping close but safe gaps between them and himself. He also has half-decent hands, which allowed him to break up plays in and near the radius of his wingspan. His transition coverage and fallback play provided a lot of unseen value for the Warriors, keeping offensive matchups at bay and preventing an underestimated number of field-goal opportunities.

    Impact metrics painted a consistent picture of Curry in which he was a positive defensive player. He was generally favored by more play-by-play infused and non-box metrics, with defensive scores higher than a point in PI RAPM (+1.7), PIPM (+1.47), and RAPTOR (+2.78). Although, box-oriented metrics showed him some love too, with a +1.6 score in the defensive component of Basketball-Reference‘s Box Plus/Minus model. The lowest of Curry’s defensive impact metrics was his single-year “luck-adjusted” RAPM (-0.07), which painted him as a minor negative. The aggregate of Curry’s scores suggest his defense was a clear positive to his team on the defensive end, and without any confounding variables to drastically alter the results, it’s fair to say impact metrics give strong portraits of him on that end.

    Summary

    With Curry’s evaluation under wraps, there’s now a fairer picture as to where his offense stands on the historical leaderboards. His world-class combination of scoring volume, efficiency, playmaking, and off-ball movement, paired with peak scalability, makes it hard to say his claim for the sport’s peak offensive season is rivaled by anyone not named Michael Jordan. Given the hindrances of Jordan’s impact from his more questionable portability, I’d deem Curry’s second MVP campaign as the greatest offensive season in league history. With his mild-positive defense in the equation, using my updated “Championship Probability Added” calculator, I’d estimate Curry would’ve provided a random team with a 10.2% increment to win the title. (Note: the percent increments will be significantly lower than previous evaluations because the calculation now considers impact on below-average teams.) His full-strength title odds would clock in at about 11.7%, which would rank as one of the fifteen best seasons of all-time.


  • Which is More Important in Scoring: Efficiency or Volume?

    Which is More Important in Scoring: Efficiency or Volume?

    The “efficiency versus volume” conversation is a classic today, but very few attempts have been made to provide a clear answer. Most recently, Backpicks developed its “Scoring Value” metric (abbreviated “ScoreVal”) to presumably estimate the net impact of a player’s scoring every 100 possessions. The stat alone was a success, but a more definitive solution to the “efficiency versus volume” argument was still blurry. Today, I’ll give my best attempt at settling the historic debate to determine the more important aspect of scoring between efficiency and volume.

    A way to go at this is at the team level: plotting the relationship between points per game (as volume neglects attempts/”pace”) and true shooting percentage. We’d use TS% in place of, say, points per possession (the truer measure of offensive efficiency) because we’d need to use the latter as the response variable; otherwise, efficiency correlation would be perfect! Using 2020 values, points per game holds a correlation coefficient of 0.78 and true shooting holds one of 0.75. The difference is very close, and given the sample size, it’s not enough to draw a conclusion. Plus, 2020 has about as many confounding variables as any other season (COVID-19, stoppage, no access to courts at times). Paired with the concerns of the chosen variables, it’s likely that the team level won’t settle the discussion. 

    The next way to approach a conclusion is on the player level. Between scoring rate in points per possession and true shooting percentage, which holds a stronger correlation with how “productive” a player is as a scorer? This is a question long thought of without a widespread solution. To answer this, I developed a statistical model that measures the number of net points a player adds through scoring, which I’ll name “Scorer Rating” (I’m open to name suggestions).

    Can a player’s scoring impact on the scoreboard be summed up in a single number?

    Points per possession at the team level epitomizes scoring efficiency because it redefines “scoring attempts.” TS% uses shooting attempts as the divisor, but in reality, shooting attempts aren’t the only chances a player or team is given to score. If a player commits a turnover, his team will be credited with a “scoring attempt” on that possession; because, although they weren’t given a chance to shoot, they had a chance to score that was blown. Therefore, we want to use a new measure of “scoring attempts” for players in a similar manner. To do this, I borrowed a technique from ScoreVal, which classifies turnovers as either playmaking or scoring turnovers. The model designates these turnovers based on the percentages of a player’s “offensive load” (involvement) that come from playmaking and scoring. However, this estimator provides imperfect measures when there are equitable alternatives. I used an idea discussed in the metric’s inaugural post, which designates all turnovers not committed by bad passes (per Basketball-Reference‘s play-by-play data) as “scoring turnovers.”

    With a measurement of how many turnovers negated the value of a scoring possession, I could now replicate a truer scoring efficiency on the player level. For example, in his historical 2016 campaign, Stephen Curry averaged 1.34 points per true shooting attempt. Add in his non-bad pass turnovers, 95, to the divisor, and he averaged 1.27 points per “scoring possession.” This means on possessions in which Curry attempted to score, the Golden State Warriors had an offensive rating of 127; that would be a +21 rORtg! The next step is to set a player’s new efficiency relative to the league-average. Curry’s 1.27 points per scoring possession compared to the average of that season, 1.04, means he added 0.267 points per possession relative to the league. From there, it’s a measure of how often a player attempts to score per game, normalized to 100 possessions per 48 minutes. For example, Curry accounted for 23.7 scoring possessions per game in 2016, but his team played at a 99.3 pace, so his attempts receive a slight boost.

    The raw number of net points Curry provided through scoring was the product of his efficiency and attempt frequency, which clocked in at 6.4 points, by far the highest mark in the NBA that year. After all, he led the league in volume and efficiency that year! However, the league-average was slightly higher than zero, around 0.1 points. Therefore, Curry added 6.2 points above the league’s average that season. The last confounding variable was playing time. Rakeem Christmas, the most notable example, had a Scorer Rating of 1.9 points, which ranked in the top-10, despite having only played six minutes the whole year. The last adjustment was using the binary logarithm of a player’s total minutes played as the “x” in an augmented sigmoid function to regularize abnormally high scores from limited playing time. Christmas’s “adjusted” Scorer Rating was then 0.6 points. 

    Listed below are all player-seasons for Scorer Rating since 2016.

    PlayerSeasonTmScRate
    Stephen Curry2016GSW6.2
    Stephen Curry2018GSW4.9
    Kevin Durant2016OKC4.2
    Kevin Durant2017GSW4.1
    Damian Lillard2020POR3.8
    Isaiah Thomas2017BOS3.7
    Stephen Curry2019GSW3.7
    Kevin Durant2018GSW3.5
    Stephen Curry2017GSW3.3
    James Harden2018HOU3.2
    James Harden2019HOU3.2
    Kawhi Leonard2016SAS3
    Kevin Durant2019GSW3
    J.J. Redick2016LAC2.9
    Karl-Anthony Towns2018MIN2.9
    LeBron James2018CLE2.9
    John Collins2020ATL2.9
    James Harden2016HOU2.8
    Kawhi Leonard2017SAS2.8
    James Harden2020HOU2.8
    LeBron James2017CLE2.7
    Kyle Lowry2017TOR2.7
    Anthony Davis2018NOP2.7
    Karl-Anthony Towns2020MIN2.7
    Klay Thompson2016GSW2.6
    Karl-Anthony Towns2017MIN2.6
    Kyrie Irving2018BOS2.6
    Danilo Gallinari2019LAC2.6
    JaKarr Sampson2019CHI2.6
    MarShon Brooks2018MEM2.5
    LeBron James2016CLE2.4
    James Harden2017HOU2.4
    Bradley Beal2017WAS2.4
    Damian Lillard2018POR2.4
    Duncan Robinson2020MIA2.4
    Danilo Gallinari2017DEN2.3
    Damian Lillard2017POR2.3
    Giannis Antetokounmpo2019MIL2.3
    Rudy Gobert2019UTA2.3
    Clint Capela2019HOU2.2
    Kawhi Leonard2019TOR2.2
    Mike Conley2017MEM2.1
    Otto Porter2017WAS2.1
    Rudy Gobert2017UTA2.1
    Rudy Gobert2020UTA2.1
    Anthony Davis2020LAL2.1
    Mitchell Robinson2020NYK2.1
    Klay Thompson2017GSW2
    Nikola Jokić2017DEN2
    Gordon Hayward2017UTA2
    DeAndre Jordan2017LAC2
    Chris Paul2017LAC2
    Damian Lillard2019POR2
    Dāvis Bertāns2020WAS2
    Devin Booker2020PHO2
    J.J. Redick2020NOP2
    J.J. Redick2018PHI1.9
    Jimmy Butler2018MIN1.9
    Kevin Love2018CLE1.9
    R.J. Hunter2019BOS1.9
    Kyrie Irving2020BRK1.9
    Jimmy Butler2017CHI1.8
    George Hill2017UTA1.8
    Andre Ingram2018LAL1.8
    Klay Thompson2018GSW1.8
    Jonathan Gibson2018BOS1.8
    Clint Capela2018HOU1.8
    Dwight Powell2019DAL1.8
    Anthony Davis2019NOP1.8
    Montrezl Harrell2019LAC1.8
    Khris Middleton2020MIL1.8
    T.J. Warren2020IND1.8
    Richaun Holmes2020SAC1.8
    Danilo Gallinari2020OKC1.8
    Danilo Gallinari2016DEN1.7
    Jae Crowder2017BOS1.7
    Gary Harris2017DEN1.7
    Thomas Bryant2019WAS1.7
    Karl-Anthony Towns2019MIN1.7
    Joe Harris2019BRK1.7
    Brandon Clarke2020MEM1.7
    DeAndre Jordan2016LAC1.6
    Kyle Lowry2016TOR1.6
    Kyrie Irving2017CLE1.6
    Chris Paul2018HOU1.6
    Giannis Antetokounmpo2018MIL1.6
    John Collins2019ATL1.6
    Bojan Bogdanović2019IND1.6
    LeBron James2019LAL1.6
    Kyrie Irving2019BOS1.6
    Pascal Siakam2019TOR1.6
    J.J. Redick2019PHI1.6
    Christian Wood2020DET1.6
    Thomas Bryant2020WAS1.6
    Seth Curry2020DAL1.6
    Damian Lillard2016POR1.5
    Chris Paul2016LAC1.5
    Chris Bosh2016MIA1.5
    CJ McCollum2017POR1.5
    Lou Williams2017TOT1.5
    Montrezl Harrell2017HOU1.5
    Otto Porter2018WAS1.5
    Anthony Tolliver2018DET1.5
    Montrezl Harrell2018LAC1.5
    Malcolm Brogdon2019MIL1.5
    Trae Young2020ATL1.5
    Chris Paul2020OKC1.5
    Keldon Johnson2020SAS1.5
    Lou Williams2016LAL1.4
    Kyle Korver2017TOT1.4
    Paul George2017IND1.4
    Clint Capela2017HOU1.4
    J.J. Redick2017LAC1.4
    DeAndre Jordan2018LAC1.4
    Kyle Korver2018CLE1.4
    Kyle Lowry2018TOR1.4
    Reggie Bullock2018DET1.4
    Rudy Gobert2018UTA1.4
    Gary Harris2018DEN1.4
    Paul George2019OKC1.4
    Norman Powell2020TOR1.4
    Zion Williamson2020NOP1.4
    Hassan Whiteside2020POR1.4
    Dwight Powell2020DAL1.4
    Hassan Whiteside2016MIA1.3
    Karl-Anthony Towns2016MIN1.3
    Jimmy Butler2016CHI1.3
    Enes Kanter2016OKC1.3
    Anthony Davis2017NOP1.3
    Tyson Chandler2017PHO1.3
    Joe Harris2018BRK1.3
    Dwight Powell2018DAL1.3
    Lou Williams2018LAC1.3
    Joe Ingles2018UTA1.3
    Kemba Walker2018CHO1.3
    Darren Collison2018IND1.3
    Mitchell Robinson2019NYK1.3
    Jarrett Allen2020BRK1.3
    Giannis Antetokounmpo2020MIL1.3
    Nikola Jokić2020DEN1.3
    George Hill2020MIL1.3
    Eric Mika2020SAC1.3
    Chandler Parsons2016DAL1.2
    Dirk Nowitzki2016DAL1.2
    Evan Fournier2016ORL1.2
    Darren Collison2016SAC1.2
    Giannis Antetokounmpo2017MIL1.2
    Seth Curry2017DAL1.2
    Enes Kanter2018NYK1.2
    Bojan Bogdanović2018IND1.2
    Danny Green2019TOR1.2
    DeAndre Jordan2019TOT1.2
    Bradley Beal2019WAS1.2
    Buddy Hield2019SAC1.2
    Bojan Bogdanović2020UTA1.2
    Nerlens Noel2020OKC1.2
    Kawhi Leonard2020LAC1.2
    DeAndre Jordan2020BRK1.2
    DeMar DeRozan2020SAS1.2
    Marvin Williams2016CHO1.1
    Carl Landry2016PHI1.1
    LaMarcus Aldridge2016SAS1.1
    C.J. Miles2017IND1.1
    Nick Young2017LAL1.1
    Kemba Walker2017CHO1.1
    Adreian Payne2018ORL1.1
    Tobias Harris2019TOT1.1
    Danuel House2019HOU1.1
    Derrick Favors2019UTA1.1
    D.J. Augustin2019ORL1.1
    Kenneth Faried2019TOT1.1
    Kevin Love2020CLE1.1
    Doug McDermott2020IND1.1
    Montrezl Harrell2020LAC1.1
    Rodney Hood2020POR1.1
    Jimmy Butler2020MIA1.1
    Luka Dončić2020DAL1.1
    Jaxson Hayes2020NOP1.1
    Jonas Valančiūnas2016TOR1
    Anthony Davis2016NOP1
    Michael Kidd-Gilchrist2016CHO1
    Brandan Wright2016MEM1
    Kemba Walker2016CHO1
    Omri Casspi2016SAC1
    Archie Goodwin2017TOT1
    Andre Iguodala2017GSW1
    Jordan Crawford2017NOP1
    Jonas Valančiūnas2018TOR1
    Steven Adams2018OKC1
    LaMarcus Aldridge2018SAS1
    Nikola Jokić2018DEN1
    Jeremy Lin2018BRK1
    Nikola Mirotić2018TOT1
    Wade Baldwin2018POR1
    Taj Gibson2018MIN1
    Khris Middleton2018MIL1
    Dāvis Bertāns2019SAS1
    Jonas Valančiūnas2019TOT1
    Mike Conley2019MEM1
    Nikola Mirotić2019TOT1
    JaVale McGee2019LAL1
    Richaun Holmes2019PHO1
    Jodie Meeks2019TOR1
    Jonas Valančiūnas2020MEM1
    Ben McLemore2020HOU1
    Paul George2020LAC1
    Clint Capela2020HOU1
    Joe Harris2020BRK1
    Jae Crowder2016BOS0.9
    Al Horford2016ATL0.9
    Isaiah Thomas2016BOS0.9
    Boban Marjanović2016SAS0.9
    Allen Crabbe2017POR0.9
    Brandan Wright2017MEM0.9
    Zach LaVine2017MIN0.9
    Channing Frye2017CLE0.9
    Ryan Anderson2017HOU0.9
    Wayne Ellington2018MIA0.9
    Jamil Wilson2018LAC0.9
    Mirza Teletović2018MIL0.9
    Kawhi Leonard2018SAS0.9
    Jarrett Allen2019BRK0.9
    Malik Beasley2019DEN0.9
    T.J. Warren2019PHO0.9
    Landry Shamet2019TOT0.9
    Dwight Howard2019WAS0.9
    Al Horford2019BOS0.9
    Devin Booker2019PHO0.9
    Klay Thompson2019GSW0.9
    Domantas Sabonis2019IND0.9
    Evan Fournier2020ORL0.9
    Garrison Mathews2020WAS0.9
    Daniel Theis2020BOS0.9
    Bradley Beal2020WAS0.9
    Tim Hardaway Jr.2020DAL0.9
    Robert Williams2020BOS0.9
    Damian Jones2020ATL0.9
    Gordon Hayward2020BOS0.9
    Ivica Zubac2020LAC0.9
    Kyle Lowry2020TOR0.9
    Jared Dudley2016WAS0.8
    Marcin Gortat2016WAS0.8
    Brandon Bass2016LAL0.8
    Draymond Green2016GSW0.8
    Troy Daniels2016CHO0.8
    Mirza Teletović2016PHO0.8
    Blake Griffin2017LAC0.8
    Nenê2017HOU0.8
    Josh Huestis2017OKC0.8
    Tony Snell2017MIL0.8
    Myles Turner2017IND0.8
    Marvin Williams2018CHO0.8
    Dirk Nowitzki2018DAL0.8
    Ante Žižić2018CLE0.8
    Darius Miller2018NOP0.8
    D.J. Augustin2018ORL0.8
    Damian Jones2019GSW0.8
    Jerami Grant2019OKC0.8
    Deandre Ayton2019PHO0.8
    Brook Lopez2019MIL0.8
    Jeff Green2019WAS0.8
    Joel Embiid2019PHI0.8
    Doug McDermott2019IND0.8
    Patty Mills2020SAS0.8
    Mikal Bridges2020PHO0.8
    Luke Kennard2020DET0.8
    Derrick Jones Jr.2020MIA0.8
    Larry Nance Jr.2020CLE0.8
    Shake Milton2020PHI0.8
    Tristan Thompson2016CLE0.7
    Khris Middleton2016MIL0.7
    Sean Kilpatrick2016TOT0.7
    Eric Gordon2016NOP0.7
    Paul George2016IND0.7
    Seth Curry2016SAC0.7
    Steven Adams2016OKC0.7
    Michael Beasley2016HOU0.7
    Harrison Barnes2016GSW0.7
    Kevin Love2017CLE0.7
    Pau Gasol2017SAS0.7
    Richaun Holmes2017PHI0.7
    Nerlens Noel2017TOT0.7
    Tim Hardaway Jr.2017ATL0.7
    Evan Fournier2018ORL0.7
    David Stockton2018UTA0.7
    Marco Belinelli2018TOT0.7
    Paul George2018OKC0.7
    Tobias Harris2018TOT0.7
    Malcolm Brogdon2018MIL0.7
    Trey Lyles2018DEN0.7
    Eric Bledsoe2018TOT0.7
    E’Twaun Moore2018NOP0.7
    Larry Nance Jr.2018TOT0.7
    Monte Morris2018DEN0.7
    Josh Hart2018LAL0.7
    Victor Oladipo2018IND0.7
    John Collins2018ATL0.7
    Willie Reed2018TOT0.7
    Jerami Grant2018OKC0.7
    Boban Marjanović2019TOT0.7
    Meyers Leonard2019POR0.7
    Devin Robinson2019WAS0.7
    Nikola Jokić2019DEN0.7
    Jimmy Butler2019TOT0.7
    Langston Galloway2020DET0.7
    Dwight Howard2020LAL0.7
    Michael Porter Jr.2020DEN0.7
    LeBron James2020LAL0.7
    Derrick Favors2020NOP0.7
    Grayson Allen2020MEM0.7
    Tony Snell2020DET0.7
    Allen Crabbe2016POR0.6
    Kyle Korver2016ATL0.6
    James Ennis2016TOT0.6
    Quincy Acy2016SAC0.6
    Manu Ginóbili2016SAS0.6
    Otto Porter2016WAS0.6
    Kevin Love2016CLE0.6
    DeMar DeRozan2016TOR0.6
    Ian Mahinmi2016IND0.6
    Rakeem Christmas2016IND0.6
    JaVale McGee2017GSW0.6
    Cody Zeller2017CHO0.6
    Tobias Harris2017DET0.6
    Brandon Bass2017LAC0.6
    David Lee2017SAS0.6
    Dwight Howard2017ATL0.6
    Wayne Ellington2017MIA0.6
    Jonas Valančiūnas2017TOR0.6
    Goran Dragić2017MIA0.6
    Bojan Bogdanović2017TOT0.6
    Darren Collison2017SAC0.6
    Patty Mills2017SAS0.6
    Jarrett Allen2018BRK0.6
    Eric Gordon2018HOU0.6
    Jrue Holiday2018NOP0.6
    Ryan Anderson2018HOU0.6
    Tomáš Satoranský2018WAS0.6
    Jakob Poeltl2018TOR0.6
    Jayson Tatum2018BOS0.6
    Thabo Sefolosha2018UTA0.6
    Derrick Favors2018UTA0.6
    Omri Casspi2018GSW0.6
    Jamal Murray2018DEN0.6
    JaVale McGee2018GSW0.6
    Quinn Cook2018GSW0.6
    Tyreke Evans2018MEM0.6
    Bryn Forbes2019SAS0.6
    Taj Gibson2019MIN0.6
    Monte Morris2019DEN0.6
    Blake Griffin2019DET0.6
    Marcus Derrickson2019GSW0.6
    Julius Randle2019NOP0.6
    Jakob Poeltl2019SAS0.6
    Rudy Gay2019SAS0.6
    Khem Birch2019ORL0.6
    Deyonta Davis2019ATL0.6
    Cameron Payne2020PHO0.6
    Matt Thomas2020TOR0.6
    Jerami Grant2020DEN0.6
    JaVale McGee2020LAL0.6
    Daniel Gafford2020CHI0.6
    Gary Trent Jr.2020POR0.6
    Cheick Diallo2020PHO0.6
    Tony Bradley2020UTA0.6
    Derrick White2020SAS0.6
    Kemba Walker2020BOS0.6
    Sindarius Thornwell2020NOP0.6
    Russell Westbrook2016OKC0.5
    Kenneth Faried2016DEN0.5
    Dwight Howard2016HOU0.5
    Nikola Jokić2016DEN0.5
    Jerryd Bayless2016MIL0.5
    Ed Davis2016POR0.5
    Brook Lopez2016BRK0.5
    Greg Monroe2016MIL0.5
    José Calderón2016NYK0.5
    Eric Bledsoe2016PHO0.5
    Tobias Harris2016TOT0.5
    Andrew Bogut2016GSW0.5
    J.R. Smith2016CLE0.5
    Doug McDermott2016CHI0.5
    Cody Zeller2016CHO0.5
    Gordon Hayward2016UTA0.5
    Trevor Ariza2016HOU0.5
    Enes Kanter2017OKC0.5
    David Nwaba2017LAL0.5
    Jabari Parker2017MIL0.5
    JaMychal Green2017MEM0.5
    Edy Tavares2017TOT0.5
    Khris Middleton2017MIL0.5
    Dante Cunningham2017NOP0.5
    Brook Lopez2017BRK0.5
    Amir Johnson2017BOS0.5
    Anthony Tolliver2017SAC0.5
    Dwight Powell2017DAL0.5
    José Calderón2018CLE0.5
    Bradley Beal2018WAS0.5
    Tyson Chandler2018PHO0.5
    Gerald Green2018HOU0.5
    Dario Šarić2018PHI0.5
    Alex Len2018PHO0.5
    Courtney Lee2018NYK0.5
    Deyonta Davis2018MEM0.5
    Trey Burke2018NYK0.5
    Troy Daniels2018PHO0.5
    Dāvis Bertāns2018SAS0.5
    Trevor Ariza2018HOU0.5
    Terrence Ross2019ORL0.5
    Nikola Vučević2019ORL0.5
    Dewayne Dedmon2019ATL0.5
    Kevon Looney2019GSW0.5
    Spencer Dinwiddie2019BRK0.5
    Cody Zeller2019CHO0.5
    Seth Curry2019POR0.5
    Scott Machado2019LAL0.5
    Miles Plumlee2019ATL0.5
    Wayne Ellington2019TOT0.5
    Maxi Kleber2020DAL0.5
    David Nwaba2020BRK0.5
    Nemanja Bjelica2020SAC0.5
    John Konchar2020MEM0.5
    Kentavious Caldwell-Pope2020LAL0.5
    Kyle Korver2020MIL0.5
    Isaiah Hartenstein2020HOU0.5
    Dorian Finney-Smith2020DAL0.5
    OG Anunoby2020TOR0.5
    Cameron Johnson2020PHO0.5
    Brandon Ingram2020NOP0.5
    Allonzo Trier2020NYK0.5
    Glenn Robinson III2020TOT0.5
    Ben Simmons2020PHI0.5
    Jaren Jackson Jr.2020MEM0.5
    Willie Cauley-Stein2016SAC0.4
    Gary Harris2016DEN0.4
    Matt Bonner2016SAS0.4
    Tyler Johnson2016MIA0.4
    Mike Conley2016MEM0.4
    Channing Frye2016TOT0.4
    Amir Johnson2016BOS0.4
    T.J. Warren2016PHO0.4
    Terrence Ross2016TOR0.4
    David West2016SAS0.4
    Gary Neal2016WAS0.4
    Steve Novak2016TOT0.4
    Ryan Anderson2016NOP0.4
    Ramon Sessions2016WAS0.4
    Miles Plumlee2016MIL0.4
    Patrick Beverley2016HOU0.4
    George Hill2016IND0.4
    Derrick Favors2016UTA0.4
    Richard Jefferson2016CLE0.4
    Marco Belinelli2017CHO0.4
    Marreese Speights2017LAC0.4
    DeMar DeRozan2017TOR0.4
    Kenneth Faried2017DEN0.4
    Boban Marjanović2017DET0.4
    Lucas Nogueira2017TOR0.4
    Dewayne Dedmon2017SAS0.4
    Courtney Lee2017NYK0.4
    Jeff Teague2017IND0.4
    James Jones2017CLE0.4
    Joe Ingles2017UTA0.4
    Kelly Olynyk2017BOS0.4
    Mike Muscala2017ATL0.4
    Derrick Jones Jr.2017PHO0.4
    Tony Snell2018MIL0.4
    Kelly Olynyk2018MIA0.4
    Jeff Green2018CLE0.4
    Meyers Leonard2018POR0.4
    Jordan Bell2018GSW0.4
    Brandan Wright2018TOT0.4
    Mike Scott2018WAS0.4
    Dewayne Dedmon2018ATL0.4
    Mike Muscala2018ATL0.4
    Channing Frye2018TOT0.4
    Anthony Brown2018MIN0.4
    Jonas Jerebko2018UTA0.4
    James Ennis2018TOT0.4
    Kyle O’Quinn2018NYK0.4
    Julius Randle2018LAL0.4
    David West2018GSW0.4
    Derrick White2018SAS0.4
    Norman Powell2019TOR0.4
    Kemba Walker2019CHO0.4
    Kelly Olynyk2019MIA0.4
    Cheick Diallo2019NOP0.4
    Eric Bledsoe2019MIL0.4
    Daniel Theis2019BOS0.4
    Jake Layman2019POR0.4
    Christian Wood2019TOT0.4
    Kyle Korver2019TOT0.4
    Omri Casspi2019MEM0.4
    Otto Porter2019TOT0.4
    Tyler Zeller2019TOT0.4
    Luol Deng2019MIN0.4
    Kentavious Caldwell-Pope2019LAL0.4
    Tony Snell2019MIL0.4
    Demetrius Jackson2019PHI0.4
    LaMarcus Aldridge2019SAS0.4
    Tomáš Satoranský2019WAS0.4
    Malcolm Miller2019TOR0.4
    Nicolas Batum2019CHO0.4
    Ryan Broekhoff2019DAL0.4
    Jordan Sibert2019ATL0.4
    Meyers Leonard2020MIA0.4
    Kelly Olynyk2020MIA0.4
    Drew Eubanks2020SAS0.4
    Justin Holiday2020IND0.4
    Courtney Lee2020DAL0.4
    Jaylen Brown2020BOS0.4
    Harrison Barnes2020SAC0.4
    Timothé Luwawu-Cabarrot2020BRK0.4
    Dennis Schröder2020OKC0.4
    Donta Hall2020TOT0.4
    Landry Shamet2020LAC0.4
    Dean Wade2020CLE0.4
    Ersan İlyasova2020MIL0.4
    Boban Marjanović2020DAL0.4
    Tacko Fall2020BOS0.4
    Dario Šarić2020PHO0.4
    Dusty Hannahs2020MEM0.4
    Montrezl Harrell2016HOU0.3
    Mike Scott2016ATL0.3
    Tim Hardaway Jr.2016ATL0.3
    Luol Deng2016MIA0.3
    C.J. Miles2016IND0.3
    Devin Harris2016DAL0.3
    Shaun Livingston2016GSW0.3
    Chris Andersen2016TOT0.3
    D.J. Augustin2016TOT0.3
    Josh Richardson2016MIA0.3
    Tyson Chandler2016PHO0.3
    Gorgui Dieng2016MIN0.3
    Nikola Mirotić2016CHI0.3
    James Jones2016CLE0.3
    Avery Bradley2016BOS0.3
    Giannis Antetokounmpo2016MIL0.3
    Justin Harper2016DET0.3
    Thanasis Antetokounmpo2016NYK0.3
    Marcin Gortat2017WAS0.3
    Serge Ibaka2017TOT0.3
    Russell Westbrook2017OKC0.3
    Dāvis Bertāns2017SAS0.3
    Demetrius Jackson2017BOS0.3
    Jodie Meeks2017ORL0.3
    Jason Terry2017MIL0.3
    Tristan Thompson2017CLE0.3
    Shawn Long2017PHI0.3
    Marcus Georges-Hunt2017ORL0.3
    Jeremy Lamb2017CHO0.3
    Ian Clark2017GSW0.3
    Shabazz Muhammad2017MIN0.3
    Kentavious Caldwell-Pope2018LAL0.3
    Rodney McGruder2018MIA0.3
    Al Horford2018BOS0.3
    Maurice Harkless2018POR0.3
    George Hill2018TOT0.3
    Allen Crabbe2018BRK0.3
    Richaun Holmes2018PHI0.3
    Kyle Anderson2018SAS0.3
    Nenê2018HOU0.3
    Maxi Kleber2018DAL0.3
    Cody Zeller2018CHO0.3
    Jameel Warney2018DAL0.3
    Doug McDermott2018TOT0.3
    Lucas Nogueira2018TOR0.3
    Amile Jefferson2019ORL0.3
    Patty Mills2019SAS0.3
    Georges Niang2019UTA0.3
    Alan Williams2019BRK0.3
    Robert Covington2019TOT0.3
    Robert Williams2019BOS0.3
    Steven Adams2019OKC0.3
    James Ennis2019TOT0.3
    Andre Iguodala2019GSW0.3
    Isaiah Hicks2019NYK0.3
    Jonas Jerebko2019GSW0.3
    Zach LaVine2019CHI0.3
    Darren Collison2019IND0.3
    Gary Payton II2019WAS0.3
    Dwayne Bacon2019CHO0.3
    Taurean Prince2019ATL0.3
    Chris Paul2019HOU0.3
    Ryan Arcidiacono2019CHI0.3
    Ekpe Udoh2019UTA0.3
    Furkan Korkmaz2020PHI0.3
    Alec Burks2020TOT0.3
    Chris Boucher2020TOR0.3
    Jordan Clarkson2020TOT0.3
    Danuel House2020HOU0.3
    Sviatoslav Mykhailiuk2020DET0.3
    Steven Adams2020OKC0.3
    Jordan McLaughlin2020MIN0.3
    Georges Niang2020UTA0.3
    Caleb Martin2020CHO0.3
    Johnathan Motley2020LAC0.3
    Mfiondu Kabengele2020LAC0.3
    Mason Plumlee2020DEN0.3
    Joe Ingles2020UTA0.3
    Jakob Poeltl2020SAS0.3
    Cristiano Felício2020CHI0.3
    Trevor Ariza2020TOT0.3
    JaKarr Sampson2020IND0.3
    Shamorie Ponds2020TOR0.3
    Jalen McDaniels2020CHO0.3
    Bam Adebayo2020MIA0.3
    Shai Gilgeous-Alexander2020OKC0.3
    CJ McCollum2016POR0.2
    Cole Aldrich2016LAC0.2
    Shabazz Muhammad2016MIN0.2
    Andre Miller2016TOT0.2
    Andre Iguodala2016GSW0.2
    Dewayne Dedmon2016ORL0.2
    Blake Griffin2016LAC0.2
    Courtney Lee2016TOT0.2
    Derrick Williams2016NYK0.2
    Jon Leuer2016PHO0.2
    Thabo Sefolosha2016ATL0.2
    Jorge Gutiérrez2016CHO0.2
    Jeremy Evans2016DAL0.2
    Mario Chalmers2016TOT0.2
    Willie Reed2016BRK0.2
    Salah Mejri2016DAL0.2
    Reggie Bullock2016DET0.2
    Boris Diaw2016SAS0.2
    Mike Dunleavy2016CHI0.2
    Andrew Nicholson2016ORL0.2
    Jonathon Simmons2016SAS0.2
    Anthony Morrow2016OKC0.2
    E’Twaun Moore2016CHI0.2
    Andre Roberson2016OKC0.2
    Joffrey Lauvergne2016DEN0.2
    Paul Millsap2016ATL0.2
    Coty Clarke2016BOS0.2
    Axel Toupane2017TOT0.2
    Avery Bradley2017BOS0.2
    Spencer Dinwiddie2017BRK0.2
    Luc Mbah a Moute2017LAC0.2
    Chasson Randle2017TOT0.2
    Terrence Ross2017TOT0.2
    Michael Beasley2017MIL0.2
    Darrell Arthur2017DEN0.2
    Chinanu Onuaku2017HOU0.2
    Pat Connaughton2017POR0.2
    Quinn Cook2017TOT0.2
    Cristiano Felício2017CHI0.2
    Marvin Williams2017CHO0.2
    Jeremy Lin2017BRK0.2
    Eric Gordon2017HOU0.2
    Eric Bledsoe2017PHO0.2
    Mike Dunleavy2017TOT0.2
    Jared Dudley2017PHO0.2
    Jon Leuer2017DET0.2
    Thaddeus Young2017IND0.2
    DeMar DeRozan2018TOR0.2
    Jeremy Lamb2018CHO0.2
    Okaro White2018MIA0.2
    OG Anunoby2018TOR0.2
    Cheick Diallo2018NOP0.2
    Luke Babbitt2018TOT0.2
    Tyler Zeller2018TOT0.2
    Jeremy Evans2018ATL0.2
    Serge Ibaka2018TOR0.2
    Chandler Parsons2018MEM0.2
    Devin Harris2018TOT0.2
    Robert Covington2018PHI0.2
    Nick Young2018GSW0.2
    Danilo Gallinari2018LAC0.2
    Daniel Theis2018BOS0.2
    Delon Wright2018TOR0.2
    Ivan Rabb2018MEM0.2
    Malcolm Miller2018TOR0.2
    JaKarr Sampson2018SAC0.2
    Álex Abrines2018OKC0.2
    Patty Mills2018SAS0.2
    Ed Davis2019BRK0.2
    CJ McCollum2019POR0.2
    Bam Adebayo2019MIA0.2
    Lou Williams2019LAC0.2
    E’Twaun Moore2019NOP0.2
    Jeremy Lamb2019CHO0.2
    Joe Ingles2019UTA0.2
    Maxi Kleber2019DAL0.2
    Vince Carter2019ATL0.2
    Nemanja Bjelica2019SAC0.2
    JaMychal Green2019TOT0.2
    Brad Wanamaker2019BOS0.2
    Frank Kaminsky2019CHO0.2
    Troy Caupain2019ORL0.2
    Reggie Bullock2019TOT0.2
    Derrick Rose2019MIN0.2
    Pat Connaughton2019MIL0.2
    Marcus Morris2019BOS0.2
    Damion Lee2019GSW0.2
    Enes Kanter2019TOT0.2
    Jahlil Okafor2019NOP0.2
    Trevon Duval2019MIL0.2
    Marquese Chriss2020GSW0.2
    Jahlil Okafor2020NOP0.2
    Goran Dragić2020MIA0.2
    Marvin Williams2020TOT0.2
    Moritz Wagner2020WAS0.2
    Marcus Morris2020TOT0.2
    Joel Embiid2020PHI0.2
    DaQuan Jeffries2020SAC0.2
    Otto Porter2020CHI0.2
    Jeff Green2020TOT0.2
    LaMarcus Aldridge2020SAS0.2
    Kelly Oubre Jr.2020PHO0.2
    Bryn Forbes2020SAS0.2
    Kostas Antetokounmpo2020LAL0.2
    Jamal Crawford2020BRK0.2
    Willie Cauley-Stein2020TOT0.2
    Enes Kanter2020BOS0.2
    Paul Millsap2020DEN0.2
    Tyler Cook2020TOT0.2
    Terence Davis2020TOR0.2
    Patrick Patterson2020LAC0.2
    Max Strus2020CHI0.2
    Amar’e Stoudemire2016MIA0.1
    Nemanja Bjelica2016MIN0.1
    Patty Mills2016SAS0.1
    Jason Terry2016HOU0.1
    Rasual Butler2016SAS0.1
    Brian Roberts2016TOT0.1
    Rodney Hood2016UTA0.1
    Joe Ingles2016UTA0.1
    Bradley Beal2016WAS0.1
    Lance Thomas2016NYK0.1
    Anthony Tolliver2016DET0.1
    Cristiano Felício2016CHI0.1
    Nenê2016WAS0.1
    Meyers Leonard2016POR0.1
    Richaun Holmes2016PHI0.1
    Mike Muscala2016ATL0.1
    John Henson2016MIL0.1
    Jeff Withey2016UTA0.1
    Timofey Mozgov2016CLE0.1
    Kelly Olynyk2016BOS0.1
    Tiago Splitter2016ATL0.1
    Nicolas Batum2016CHO0.1
    Ryan Hollins2016TOT0.1
    Brandon Rush2016GSW0.1
    Joel Anthony2016DET0.1
    Dwight Powell2016DAL0.1
    Trevor Ariza2017HOU0.1
    Jason Smith2017WAS0.1
    Hassan Whiteside2017MIA0.1
    Jarnell Stokes2017DEN0.1
    Larry Nance Jr.2017LAL0.1
    Juan Hernangómez2017DEN0.1
    Arron Afflalo2017SAC0.1
    Doug McDermott2017TOT0.1
    Willie Reed2017MIA0.1
    Treveon Graham2017CHO0.1
    Álex Abrines2017OKC0.1
    Skal Labissière2017SAC0.1
    Greg Monroe2017MIL0.1
    Justin Holiday2017NYK0.1
    James Ennis2017MEM0.1
    Rudy Gay2017SAC0.1
    Greg Monroe2018TOT0.1
    Bogdan Bogdanović2018SAC0.1
    Zaza Pachulia2018GSW0.1
    John Henson2018MIL0.1
    Tyler Johnson2018MIA0.1
    Al Jefferson2018IND0.1
    Salah Mejri2018DAL0.1
    Willy Hernangómez2018TOT0.1
    Alfonzo McKinnie2018TOR0.1
    Lauri Markkanen2018CHI0.1
    Nemanja Bjelica2018MIN0.1
    Luc Mbah a Moute2018HOU0.1
    Tyler Cavanaugh2018ATL0.1
    Jahlil Okafor2018TOT0.1
    Devin Booker2018PHO0.1
    Jack Cooley2018SAC0.1
    Reggie Hearn2018DET0.1
    Edmond Sumner2018IND0.1
    Naz Mitrou-Long2018UTA0.1
    Tyus Jones2018MIN0.1
    Will Barton2018DEN0.1
    Jabari Bird2018BOS0.1
    Kevon Looney2018GSW0.1
    Nerlens Noel2019OKC0.1
    Quinn Cook2019GSW0.1
    Kyle Lowry2019TOR0.1
    Jordan Loyd2019TOR0.1
    Thaddeus Young2019IND0.1
    Justin Jackson2019TOT0.1
    Gordon Hayward2019BOS0.1
    Dante Cunningham2019SAS0.1
    Tahjere McCall2019BRK0.1
    Quincy Pondexter2019SAS0.1
    Luke Kennard2019DET0.1
    Marco Belinelli2019SAS0.1
    Cameron Reynolds2019MIN0.1
    Willie Cauley-Stein2019SAC0.1
    Thomas Welsh2019DEN0.1
    Alex Caruso2019LAL0.1
    Al-Farouq Aminu2019POR0.1
    Mitch Creek2019TOT0.1
    Myles Turner2019IND0.1
    Jonah Bolden2019PHI0.1
    Mason Plumlee2019DEN0.1
    T.J. Leaf2019IND0.1
    Kadeem Allen2019NYK0.1
    Jaren Jackson Jr.2019MEM0.1
    Anthony Tolliver2019MIN0.1
    Serge Ibaka2019TOR0.1
    Larry Nance Jr.2019CLE0.1
    Juan Hernangómez2019DEN0.1
    B.J. Johnson2019TOT0.1
    Jrue Holiday2019NOP0.1
    Marcus Smart2019BOS0.1
    D’Angelo Russell2020TOT0.1
    Derrick Walton2020TOT0.1
    Isaac Bonga2020WAS0.1
    Bogdan Bogdanović2020SAC0.1
    Ryan Broekhoff2020DAL0.1
    Abdel Nader2020OKC0.1
    Taj Gibson2020NYK0.1
    Mike Scott2020PHI0.1
    Juwan Morgan2020UTA0.1
    Alex Len2020TOT0.1
    Jayson Tatum2020BOS0.1
    Trey Lyles2020SAS0.1
    Noah Vonleh2020TOT0.1
    Aron Baynes2020PHO0.1
    Rayjon Tucker2020UTA0.1
    Gary Clark2020TOT0.1
    KZ Okpala2020MIA0.1
    David Lee2016TOT0
    Kevon Looney2016GSW0
    JaVale McGee2016DAL0
    Festus Ezeli2016GSW0
    Toney Douglas2016NOP0
    Lucas Nogueira2016TOR0
    Jarnell Stokes2016TOT0
    Wesley Matthews2016DAL0
    Dante Cunningham2016NOP0
    Tony Parker2016SAS0
    Kyrie Irving2016CLE0
    J.J. Barea2016DAL0
    Robin Lopez2016NYK0
    Jeff Teague2016ATL0
    Clint Capela2016HOU0
    Leandro Barbosa2016GSW0
    Sergey Karasev2016BRK0
    Jeremy Lamb2016CHO0
    Jason Thompson2016TOT0
    Damjan Rudež2016MIN0
    Solomon Hill2016IND0
    Sam Dekker2016HOU0
    Jamal Crawford2016LAC0
    Zach LaVine2016MIN0
    Jabari Parker2016MIL0
    Alonzo Gee2016NOP0
    Glenn Robinson III2017IND0
    Richard Jefferson2017CLE0
    Roy Hibbert2017TOT0
    Luke Babbitt2017MIA0
    John Jenkins2017PHO0
    Caris LeVert2017BRK0
    Thon Maker2017MIL0
    Jeff Withey2017UTA0
    Jerian Grant2017CHI0
    Salah Mejri2017DAL0
    Nick Collison2017OKC0
    Ty Lawson2017SAC0
    Maurice Harkless2017POR0
    T.J. Warren2017PHO0
    Danuel House2017WAS0
    Shaun Livingston2017GSW0
    Joel Bolomboy2017UTA0
    Alex Poythress2017PHI0
    Joel Anthony2017SAS0
    Vince Carter2017MEM0
    Harrison Barnes2017DAL0
    Sam Dekker2017HOU0
    Jodie Meeks2018WAS0
    Boban Marjanović2018TOT0
    Ersan İlyasova2018TOT0
    James Johnson2018MIA0
    Fred VanVleet2018TOR0
    Manu Ginóbili2018SAS0
    Cristiano Felício2018CHI0
    Dakari Johnson2018OKC0
    C.J. Miles2018TOR0
    Daniel Hamilton2018OKC0
    Trey McKinney-Jones2018IND0
    Yogi Ferrell2018DAL0
    Tyler Lydon2018DEN0
    Hassan Whiteside2018MIA0
    T.J. Leaf2018IND0
    Jordan Crawford2018NOP0
    Brook Lopez2018LAL0
    Nick Collison2018OKC0
    Luke Kennard2018DET0
    Mangok Mathiang2018CHO0
    Miloš Teodosić2018LAC0
    Omari Johnson2018MEM0
    Justin Patton2018MIN0
    Gian Clavell2018DAL0
    Chris Boucher2018GSW0
    Marshall Plumlee2018MIL0
    Rodney Hood2018TOT0
    Julyan Stone2018CHO0
    Jacob Pullen2018PHI0
    Justin Anderson2018PHI0
    Gordon Hayward2018BOS0
    Draymond Green2018GSW0
    Ed Davis2018POR0
    Ben Moore2018IND0
    Danuel House2018PHO0
    David Nwaba2019CLE0
    Mike Muscala2019TOT0
    Paul Millsap2019DEN0
    Gerald Green2019HOU0
    Sterling Brown2019MIL0
    Thabo Sefolosha2019UTA0
    Kevin Love2019CLE0
    Ivica Zubac2019TOT0
    Mikal Bridges2019PHO0
    Zhou Qi2019HOU0
    Bismack Biyombo2019CHO0
    Johnathan Williams2019LAL0
    Darius Miller2019NOP0
    Jon Leuer2019DET0
    Ivan Rabb2019MEM0
    Terrance Ferguson2019OKC0
    Patrick Beverley2019LAC0
    Troy Daniels2019PHO0
    Alfonzo McKinnie2019GSW0
    Willy Hernangómez2019CHO0
    John Holland2019CLE0
    Tyler Ulis2019CHI0
    Kobi Simmons2019CLE0
    Royce O’Neale2019UTA0
    Kalin Lucas2019DET0
    Robin Lopez2019CHI0
    Ben Simmons2019PHI0
    John Jenkins2019TOT0
    Alex Len2019ATL0
    George King2019PHO0
    Tyler Davis2019OKC0
    Drew Eubanks2019SAS0
    Langston Galloway2019DET0
    Alen Smailagić2020GSW0
    Jeremy Pargo2020GSW0
    Tobias Harris2020PHI0
    Jusuf Nurkić2020POR0
    Jamal Murray2020DEN0
    Ante Žižić2020CLE0
    Shaquille Harrison2020CHI0
    Domantas Sabonis2020IND0
    J.P. Macura2020CLE0
    John Henson2020TOT0
    Marques Bolden2020CLE0
    Mike Muscala2020OKC0
    Terrence Ross2020ORL0
    Jae Crowder2020TOT0
    Semi Ojeleye2020BOS0
    Monte Morris2020DEN0
    Adam Mokoka2020CHI0
    Tyson Chandler2020HOU0
    Chris Silva2020MIA0
    Thon Maker2020DET0
    Eric Paschall2020GSW0
    Cody Zeller2020CHO0
    Josh Hart2020NOP0
    Brad Wanamaker2020BOS0
    Bojan Bogdanović2016BRK-0.1
    Kent Bazemore2016ATL-0.1
    Delon Wright2016TOR-0.1
    Andrew Wiggins2016MIN-0.1
    Aaron Gordon2016ORL-0.1
    Devin Booker2016PHO-0.1
    Bismack Biyombo2016TOR-0.1
    Rudy Gay2016SAC-0.1
    Larry Nance Jr.2016LAL-0.1
    Jimmer Fredette2016TOT-0.1
    Reggie Jackson2016DET-0.1
    Taj Gibson2016CHI-0.1
    Jordan McRae2016TOT-0.1
    Mason Plumlee2016POR-0.1
    Rudy Gobert2016UTA-0.1
    Kosta Koufos2016SAC-0.1
    James Michael McAdoo2016GSW-0.1
    Isaiah Canaan2016PHI-0.1
    Aron Baynes2016DET-0.1
    Malcolm Brogdon2017MIL-0.1
    Al Horford2017BOS-0.1
    Evan Fournier2017ORL-0.1
    Quincy Acy2017TOT-0.1
    Spencer Hawes2017TOT-0.1
    Joe Harris2017BRK-0.1
    James Johnson2017MIA-0.1
    Norman Powell2017TOR-0.1
    Jarell Eddie2017PHO-0.1
    E’Twaun Moore2017NOP-0.1
    James Young2017BOS-0.1
    Patrick Patterson2017TOR-0.1
    Willie Cauley-Stein2017SAC-0.1
    Nikola Mirotić2017CHI-0.1
    Devin Harris2017DAL-0.1
    Zaza Pachulia2017GSW-0.1
    Steven Adams2017OKC-0.1
    Marc Gasol2017MEM-0.1
    Patrick McCaw2017GSW-0.1
    Reggie Williams2017NOP-0.1
    Reggie Bullock2017DET-0.1
    Justin Hamilton2017BRK-0.1
    Joe Johnson2017UTA-0.1
    Khem Birch2018ORL-0.1
    J.J. Barea2018DAL-0.1
    Kendrick Perkins2018CLE-0.1
    Vince Hunter2018MEM-0.1
    Wesley Matthews2018DAL-0.1
    Frank Kaminsky2018CHO-0.1
    Buddy Hield2018SAC-0.1
    Rashad Vaughn2018TOT-0.1
    Dante Exum2018UTA-0.1
    Jeff Teague2018MIN-0.1
    Tim Quarterman2018HOU-0.1
    Terrance Ferguson2018OKC-0.1
    Raul Neto2018UTA-0.1
    Jared Dudley2018PHO-0.1
    Cedi Osman2018CLE-0.1
    Derrick Walton2018MIA-0.1
    D.J. Wilson2018MIL-0.1
    Kosta Koufos2018SAC-0.1
    Patrick Patterson2018OKC-0.1
    Myles Turner2018IND-0.1
    Ike Anigbogu2018IND-0.1
    PJ Dozier2018OKC-0.1
    Jaylen Brown2018BOS-0.1
    Shaquille Harrison2018PHO-0.1
    Amir Johnson2018PHI-0.1
    James Michael McAdoo2018PHI-0.1
    Alec Peters2018PHO-0.1
    T.J. Warren2018PHO-0.1
    Guerschon Yabusele2018BOS-0.1
    Dante Cunningham2018TOT-0.1
    Pascal Siakam2018TOR-0.1
    Mason Plumlee2018DEN-0.1
    James Young2018PHI-0.1
    Treveon Graham2018CHO-0.1
    Pat Connaughton2018POR-0.1
    Chris Boucher2019TOR-0.1
    Jared Dudley2019BRK-0.1
    Marvin Williams2019CHO-0.1
    Donte Grantham2019OKC-0.1
    Yogi Ferrell2019SAC-0.1
    D.J. Stephens2019MEM-0.1
    Bruno Caboclo2019MEM-0.1
    Skal Labissière2019TOT-0.1
    Derrick White2019SAS-0.1
    Shaun Livingston2019GSW-0.1
    Khris Middleton2019MIL-0.1
    Derrick Jones Jr.2019MIA-0.1
    Nenê2019HOU-0.1
    Harrison Barnes2019TOT-0.1
    Gorgui Dieng2019MIN-0.1
    George Hill2019TOT-0.1
    Rodney Hood2019TOT-0.1
    Tyler Lydon2019DEN-0.1
    Eric Gordon2019HOU-0.1
    Ante Žižić2019CLE-0.1
    Dario Šarić2019TOT-0.1
    Ben McLemore2019SAC-0.1
    Raul Neto2019UTA-0.1
    Miles Bridges2019CHO-0.1
    Davon Reed2019IND-0.1
    Jared Dudley2020LAL-0.1
    Zach LaVine2020CHI-0.1
    Jevon Carter2020PHO-0.1
    Raul Neto2020PHI-0.1
    Trey Burke2020TOT-0.1
    Torrey Craig2020DEN-0.1
    Kyle Alexander2020MIA-0.1
    Maurice Harkless2020TOT-0.1
    Dante Exum2020TOT-0.1
    Harry Giles2020SAC-0.1
    JaMychal Green2020LAC-0.1
    Pat Connaughton2020MIL-0.1
    Josh Gray2020NOP-0.1
    Royce O’Neale2020UTA-0.1
    Jeremy Lamb2020IND-0.1
    Jeremiah Martin2020BRK-0.1
    Ryan Arcidiacono2020CHI-0.1
    Lauri Markkanen2020CHI-0.1
    Joakim Noah2020LAC-0.1
    Chimezie Metu2020SAS-0.1
    Javonte Green2020BOS-0.1
    Eric Bledsoe2020MIL-0.1
    Melvin Frazier2020ORL-0.1
    Chris Clemons2020HOU-0.1
    Nikola Vučević2020ORL-0.1
    Jabari Parker2020TOT-0.1
    Luke Babbitt2016NOP-0.2
    Pau Gasol2016CHI-0.2
    Branden Dawson2016LAC-0.2
    Greg Smith2016MIN-0.2
    Jeff Ayres2016LAC-0.2
    J.J. O’Brien2016UTA-0.2
    Donald Sloan2016BRK-0.2
    Lance Stephenson2016TOT-0.2
    Maurice Harkless2016POR-0.2
    Norman Powell2016TOR-0.2
    Deron Williams2016DAL-0.2
    Patrick Patterson2016TOR-0.2
    Joe Harris2016CLE-0.2
    Victor Oladipo2016ORL-0.2
    Vince Carter2016MEM-0.2
    Alan Anderson2016WAS-0.2
    Eric Moreland2016SAC-0.2
    Erick Green2016TOT-0.2
    Jordan Farmar2016MEM-0.2
    Nazr Mohammed2016OKC-0.2
    Ian Clark2016GSW-0.2
    Lavoy Allen2016IND-0.2
    Marcus Morris2016DET-0.2
    Cliff Alexander2016POR-0.2
    Jrue Holiday2016NOP-0.2
    Mike Miller2016DEN-0.2
    Kyle Anderson2016SAS-0.2
    Arron Afflalo2016NYK-0.2
    Justin Anderson2016DAL-0.2
    Will Barton2016DEN-0.2
    Joe Johnson2016TOT-0.2
    Hollis Thompson2016PHI-0.2
    C.J. Wilcox2016LAC-0.2
    Austin Rivers2016LAC-0.2
    Jerami Grant2017TOT-0.2
    Mike Miller2017DEN-0.2
    Garrett Temple2017SAC-0.2
    Jarrett Jack2017NOP-0.2
    Tyler Johnson2017MIA-0.2
    Ivica Zubac2017LAL-0.2
    Ersan İlyasova2017TOT-0.2
    Danny Green2017SAS-0.2
    Will Barton2017DEN-0.2
    Patrick Beverley2017HOU-0.2
    K.J. McDaniels2017TOT-0.2
    James Michael McAdoo2017GSW-0.2
    Jakob Poeltl2017TOR-0.2
    Bobby Portis2017CHI-0.2
    Aron Baynes2017DET-0.2
    Johnny O’Bryant2017TOT-0.2
    Kosta Koufos2017SAC-0.2
    R.J. Hunter2017CHI-0.2
    Chris McCullough2017TOT-0.2
    Derrick Williams2017TOT-0.2
    Kevon Looney2017GSW-0.2
    Dirk Nowitzki2017DAL-0.2
    Jonas Jerebko2017BOS-0.2
    Andrew Bogut2018LAL-0.2
    Glenn Robinson III2018IND-0.2
    Markieff Morris2018WAS-0.2
    Rudy Gay2018SAS-0.2
    Ryan Arcidiacono2018CHI-0.2
    Richard Jefferson2018DEN-0.2
    Jabari Parker2018MIL-0.2
    Ekpe Udoh2018UTA-0.2
    Jason Terry2018MIL-0.2
    Alex Poythress2018IND-0.2
    Damyean Dotson2018NYK-0.2
    Tarik Black2018HOU-0.2
    Mindaugas Kuzminskas2018NYK-0.2
    Tristan Thompson2018CLE-0.2
    Marcus Georges-Hunt2018MIN-0.2
    Troy Williams2018TOT-0.2
    J.R. Smith2018CLE-0.2
    Josh McRoberts2018DAL-0.2
    Nik Stauskas2018TOT-0.2
    Corey Brewer2018TOT-0.2
    Harrison Barnes2018DAL-0.2
    Isaiah Canaan2018TOT-0.2
    Bam Adebayo2018MIA-0.2
    Sam Dekker2018LAC-0.2
    Shaun Livingston2018GSW-0.2
    Nerlens Noel2018DAL-0.2
    Joakim Noah2018NYK-0.2
    Luke Kornet2019NYK-0.2
    Henry Ellenson2019TOT-0.2
    Reggie Jackson2019DET-0.2
    Cristiano Felício2019CHI-0.2
    Alex Poythress2019ATL-0.2
    Maurice Harkless2019POR-0.2
    Kyle Anderson2019MEM-0.2
    C.J. Williams2019MIN-0.2
    Jeremy Lin2019TOT-0.2
    Jalen Brunson2019DAL-0.2
    Jordan McRae2019WAS-0.2
    James Nunnally2019TOT-0.2
    P.J. Tucker2019HOU-0.2
    Jalen Jones2019CLE-0.2
    Nik Stauskas2019TOT-0.2
    Wesley Matthews2019TOT-0.2
    Fred VanVleet2019TOR-0.2
    Tyson Chandler2019TOT-0.2
    Torrey Craig2019DEN-0.2
    Shai Gilgeous-Alexander2019LAC-0.2
    Duncan Robinson2019MIA-0.2
    Brandon Sampson2019CHI-0.2
    John Henson2019MIL-0.2
    Zach Lofton2019DET-0.2
    Okaro White2019WAS-0.2
    Marvin Bagley III2019SAC-0.2
    Devontae Cacok2020LAL-0.2
    Justin Robinson2020WAS-0.2
    Johnathan Williams2020WAS-0.2
    Buddy Hield2020SAC-0.2
    Patrick Beverley2020LAC-0.2
    Kristaps Porziņģis2020DAL-0.2
    Josh Jackson2020MEM-0.2
    Keita Bates-Diop2020TOT-0.2
    Wesley Matthews2020MIL-0.2
    Terance Mann2020LAC-0.2
    Luke Kornet2020CHI-0.2
    Danny Green2020LAL-0.2
    Malcolm Miller2020TOR-0.2
    Damion Lee2020GSW-0.2
    Skal Labissière2020POR-0.2
    Malik Newman2020CLE-0.2
    Serge Ibaka2020TOR-0.2
    Miye Oni2020UTA-0.2
    Tyler Zeller2020SAS-0.2
    Wendell Carter Jr.2020CHI-0.2
    D.J. Augustin2020ORL-0.2
    Vlatko Čančar2020DEN-0.2
    Jarrod Uthoff2020TOT-0.2
    Myles Turner2020IND-0.2
    Delon Wright2020DAL-0.2
    James Ennis2020TOT-0.2
    Willy Hernangómez2020CHO-0.2
    Terry Rozier2020CHO-0.2
    Isaiah Roby2020OKC-0.2
    Markieff Morris2020TOT-0.2
    Jarred Vanderbilt2020TOT-0.2
    Jordan Bell2020TOT-0.2
    P.J. Tucker2020HOU-0.2
    Nicolò Melli2020NOP-0.2
    Donovan Mitchell2020UTA-0.2
    Donte DiVincenzo2020MIL-0.2
    Zylan Cheatham2020NOP-0.2
    Kyle Guy2020SAC-0.2
    Bismack Biyombo2020CHO-0.2
    Will Barton2020DEN-0.2
    Omari Spellman2020GSW-0.2
    Robert Covington2020TOT-0.2
    Kyle O’Quinn2020PHI-0.2
    Mychal Mulder2020GSW-0.2
    Brook Lopez2020MIL-0.2
    Paul Watson2020TOT-0.2
    Marco Belinelli2020SAS-0.2
    Wesley Iwundu2020ORL-0.2
    Lou Williams2020LAC-0.2
    Tyus Jones2020MEM-0.2
    Damyean Dotson2020NYK-0.2
    Austin Rivers2020HOU-0.2
    Wesley Johnson2016LAC-0.3
    Edy Tavares2016ATL-0.3
    Matthew Dellavedova2016CLE-0.3
    Glenn Robinson III2016IND-0.3
    Josh Huestis2016OKC-0.3
    Tyler Hansbrough2016CHO-0.3
    Gerald Henderson2016POR-0.3
    Caron Butler2016SAC-0.3
    Sasha Kaun2016CLE-0.3
    Ersan İlyasova2016TOT-0.3
    Garrett Temple2016WAS-0.3
    Mario Hezonja2016ORL-0.3
    Chase Budinger2016TOT-0.3
    John Jenkins2016TOT-0.3
    Ricky Rubio2016MIN-0.3
    Tyler Zeller2016BOS-0.3
    Axel Toupane2016DEN-0.3
    Raul Neto2016UTA-0.3
    Andrew Goudelock2016HOU-0.3
    Jarell Martin2016MEM-0.3
    Luis Scola2016TOR-0.3
    Christian Wood2016PHI-0.3
    Ömer Aşık2016NOP-0.3
    Carmelo Anthony2016NYK-0.3
    K.J. McDaniels2016HOU-0.3
    Mo Williams2016CLE-0.3
    Chris Kaman2016POR-0.3
    Ricky Rubio2017MIN-0.3
    Anthony Bennett2017BRK-0.3
    Beno Udrih2017DET-0.3
    Kevin Séraphin2017IND-0.3
    Ian Mahinmi2017WAS-0.3
    DeMarcus Cousins2017TOT-0.3
    Tiago Splitter2017PHI-0.3
    Troy Daniels2017MEM-0.3
    Iman Shumpert2017CLE-0.3
    Willy Hernangómez2017NYK-0.3
    Sheldon Mac2017WAS-0.3
    Gorgui Dieng2017MIN-0.3
    Malik Beasley2017DEN-0.3
    David West2017GSW-0.3
    Tim Quarterman2017POR-0.3
    Kristaps Porziņģis2017NYK-0.3
    Manu Ginóbili2017SAS-0.3
    DeMarre Carroll2017TOR-0.3
    Tarik Black2017LAL-0.3
    John Lucas III2017MIN-0.3
    Mason Plumlee2017TOT-0.3
    Wilson Chandler2017DEN-0.3
    Raul Neto2017UTA-0.3
    Kyle O’Quinn2017NYK-0.3
    Buddy Hield2017TOT-0.3
    Anthony Morrow2017TOT-0.3
    Malachi Richardson2017SAC-0.3
    Deyonta Davis2017MEM-0.3
    Larry Sanders2017CLE-0.3
    Tyus Jones2017MIN-0.3
    Steve Novak2017MIL-0.3
    Ian Clark2018NOP-0.3
    Johnathan Motley2018DAL-0.3
    Royce O’Neale2018UTA-0.3
    Kenneth Faried2018DEN-0.3
    Jacob Wiley2018BRK-0.3
    Ivica Zubac2018LAL-0.3
    Josh Richardson2018MIA-0.3
    Vince Carter2018SAC-0.3
    Pau Gasol2018SAS-0.3
    DeMarre Carroll2018BRK-0.3
    Trevor Booker2018TOT-0.3
    Emeka Okafor2018NOP-0.3
    Aaron Brooks2018MIN-0.3
    Patrick Beverley2018LAC-0.3
    DeMarcus Cousins2018NOP-0.3
    Torrey Craig2018DEN-0.3
    Blake Griffin2018TOT-0.3
    Nicolás Brussino2018ATL-0.3
    Shabazz Muhammad2018TOT-0.3
    Wayne Selden2018MEM-0.3
    Juan Hernangómez2018DEN-0.3
    Andre Iguodala2018GSW-0.3
    Marreese Speights2018ORL-0.3
    Tim Hardaway Jr.2018NYK-0.3
    Michael Beasley2018NYK-0.3
    Michael Kidd-Gilchrist2018CHO-0.3
    Arron Afflalo2018ORL-0.3
    Kent Bazemore2018ATL-0.3
    Shabazz Napier2018POR-0.3
    Jeff Withey2018DAL-0.3
    Matt Costello2018SAS-0.3
    Joffrey Lauvergne2018SAS-0.3
    Mario Hezonja2018ORL-0.3
    Chasson Randle2019WAS-0.3
    Guerschon Yabusele2019BOS-0.3
    Jarell Martin2019ORL-0.3
    Ersan İlyasova2019MIL-0.3
    Matthew Dellavedova2019TOT-0.3
    Semi Ojeleye2019BOS-0.3
    Hassan Whiteside2019MIA-0.3
    Garrett Temple2019TOT-0.3
    Channing Frye2019CLE-0.3
    Jae Crowder2019UTA-0.3
    Joakim Noah2019MEM-0.3
    Amir Johnson2019PHI-0.3
    Lauri Markkanen2019CHI-0.3
    Kyle O’Quinn2019IND-0.3
    T.J. McConnell2019PHI-0.3
    Aron Baynes2019BOS-0.3
    Michael Kidd-Gilchrist2019CHO-0.3
    Troy Williams2019SAC-0.3
    Miloš Teodosić2019LAC-0.3
    Jusuf Nurkić2019POR-0.3
    Sindarius Thornwell2019LAC-0.3
    Thon Maker2019TOT-0.3
    Johnathan Motley2019LAC-0.3
    Wilson Chandler2019TOT-0.3
    Eric Moreland2019TOT-0.3
    Jerome Robinson2019LAC-0.3
    Allonzo Trier2019NYK-0.3
    Furkan Korkmaz2019PHI-0.3
    Isaiah Hartenstein2019HOU-0.3
    Patrick McCaw2019TOT-0.3
    Gorgui Dieng2020TOT-0.3
    James Johnson2020TOT-0.3
    Derrick Rose2020DET-0.3
    Jared Harper2020PHO-0.3
    Jalen Brunson2020DAL-0.3
    Malik Beasley2020TOT-0.3
    Collin Sexton2020CLE-0.3
    Tyler Herro2020MIA-0.3
    Talen Horton-Tucker2020LAL-0.3
    Nicolas Claxton2020BRK-0.3
    Vincent Poirier2020BOS-0.3
    Solomon Hill2020TOT-0.3
    Khem Birch2020ORL-0.3
    Deandre Ayton2020PHO-0.3
    Avery Bradley2020LAL-0.3
    Marcus Thornton2016TOT-0.4
    Jodie Meeks2016DET-0.4
    Kirk Hinrich2016TOT-0.4
    Kris Humphries2016TOT-0.4
    Goran Dragić2016MIA-0.4
    Tarik Black2016LAL-0.4
    Ronnie Price2016PHO-0.4
    Jarell Eddie2016WAS-0.4
    Darrell Arthur2016DEN-0.4
    R.J. Hunter2016BOS-0.4
    Serge Ibaka2016OKC-0.4
    Jonas Jerebko2016BOS-0.4
    Darrun Hilliard2016DET-0.4
    Anthony Bennett2016TOR-0.4
    Nikola Vučević2016ORL-0.4
    Nik Stauskas2016PHI-0.4
    Cory Jefferson2016PHO-0.4
    Myles Turner2016IND-0.4
    Trey Lyles2016UTA-0.4
    Wayne Ellington2016BRK-0.4
    Luc Mbah a Moute2016LAC-0.4
    Jordan Hill2016IND-0.4
    Jordan Mickey2016BOS-0.4
    J.J. Hickson2016TOT-0.4
    Mitch McGary2016OKC-0.4
    Tim Duncan*2016SAS-0.4
    Kentavious Caldwell-Pope2016DET-0.4
    Tyler Ennis2016MIL-0.4
    Pablo Prigioni2016LAC-0.4
    Bobby Brown2017HOU-0.4
    Cole Aldrich2017MIN-0.4
    Trey Burke2017WAS-0.4
    Arinze Onuaku2017ORL-0.4
    Christian Wood2017CHO-0.4
    Luis Scola2017BRK-0.4
    Maurice Ndour2017NYK-0.4
    Gerald Green2017BOS-0.4
    Al Jefferson2017IND-0.4
    Gerald Henderson2017PHI-0.4
    Jameer Nelson2017DEN-0.4
    Nik Stauskas2017PHI-0.4
    Paul Millsap2017ATL-0.4
    Ben McLemore2017SAC-0.4
    Aaron Gordon2017ORL-0.4
    Georgios Papagiannis2017SAC-0.4
    Ömer Aşık2017NOP-0.4
    Alan Williams2017PHO-0.4
    Tyler Zeller2017BOS-0.4
    Rakeem Christmas2017IND-0.4
    Brian Roberts2017CHO-0.4
    Damjan Rudež2017ORL-0.4
    Chris Andersen2017CLE-0.4
    Paul Pierce2017LAC-0.4
    Michael Kidd-Gilchrist2017CHO-0.4
    Austin Rivers2017LAC-0.4
    Solomon Hill2017NOP-0.4
    John Henson2017MIL-0.4
    Ed Davis2017POR-0.4
    Wesley Matthews2017DAL-0.4
    Deron Williams2017TOT-0.4
    Carmelo Anthony2017NYK-0.4
    Alan Anderson2017LAC-0.4
    D.J. Augustin2017ORL-0.4
    José Calderón2017TOT-0.4
    Langston Galloway2017TOT-0.4
    J.J. Barea2017DAL-0.4
    Markieff Morris2017WAS-0.4
    Mirza Teletović2017MIL-0.4
    Marcus Morris2018BOS-0.4
    Ian Mahinmi2018WAS-0.4
    Chris McCullough2018WAS-0.4
    Ron Baker2018NYK-0.4
    David Nwaba2018CHI-0.4
    Jarell Eddie2018TOT-0.4
    CJ McCollum2018POR-0.4
    Malik Beasley2018DEN-0.4
    Jerian Grant2018CHI-0.4
    Erik McCree2018UTA-0.4
    Damian Jones2018GSW-0.4
    Kyle Kuzma2018LAL-0.4
    Andrew Harrison2018MEM-0.4
    Gorgui Dieng2018MIN-0.4
    Brandon Paul2018SAS-0.4
    Justin Jackson2018SAC-0.4
    Jerryd Bayless2018PHI-0.4
    Luke Kornet2018NYK-0.4
    Joel Bolomboy2018MIL-0.4
    Bryn Forbes2018SAS-0.4
    Ben Simmons2018PHI-0.4
    Goran Dragić2018MIA-0.4
    Garrett Temple2018SAC-0.4
    Briante Weber2018TOT-0.4
    Alex Caruso2018LAL-0.4
    T.J. McConnell2018PHI-0.4
    Jordan Clarkson2018TOT-0.4
    Andre Roberson2018OKC-0.4
    Eric Moreland2018DET-0.4
    Wilson Chandler2018DEN-0.4
    Rondae Hollis-Jefferson2018BRK-0.4
    Cole Aldrich2018MIN-0.4
    Brice Johnson2018TOT-0.4
    Jae Crowder2018TOT-0.4
    Taurean Prince2018ATL-0.4
    Kelly Oubre Jr.2018WAS-0.4
    P.J. Tucker2018HOU-0.4
    Scotty Hopson2018DAL-0.4
    Darrell Arthur2018DEN-0.4
    Domantas Sabonis2018IND-0.4
    Joe Young2018IND-0.4
    Josh Smith2018NOP-0.4
    DeAndre Liggins2018TOT-0.4
    Wesley Iwundu2019ORL-0.4
    Corey Brewer2019TOT-0.4
    Jabari Parker2019TOT-0.4
    Mike Scott2019TOT-0.4
    OG Anunoby2019TOR-0.4
    Kelly Oubre Jr.2019TOT-0.4
    Tyler Cavanaugh2019UTA-0.4
    Terrence Jones2019HOU-0.4
    Zach Collins2019POR-0.4
    DeMarre Carroll2019BRK-0.4
    Pau Gasol2019TOT-0.4
    Salah Mejri2019DAL-0.4
    Raymond Felton2019OKC-0.4
    Jonathan Isaac2019ORL-0.4
    Jerian Grant2019ORL-0.4
    Chris Chiozza2019HOU-0.4
    Shabazz Napier2019BRK-0.4
    Marcin Gortat2019LAC-0.4
    Emanuel Terry2019TOT-0.4
    Kevin Huerter2019ATL-0.4
    Gary Clark2019HOU-0.4
    Nick Young2019DEN-0.4
    Trevor Ariza2019TOT-0.4
    Jarred Vanderbilt2019DEN-0.4
    Anfernee Simons2019POR-0.4
    Ian Mahinmi2019WAS-0.4
    Jordan Bell2019GSW-0.4
    Devin Harris2019DAL-0.4
    Justin Anderson2019ATL-0.4
    Abdel Nader2019OKC-0.4
    Jaron Blossomgame2019CLE-0.4
    Glenn Robinson III2019DET-0.4
    Corey Brewer2020SAC-0.4
    Luc Mbah a Moute2020HOU-0.4
    Charlie Brown2020ATL-0.4
    Troy Daniels2020TOT-0.4
    Daryl Macon2020MIA-0.4
    Al Horford2020PHI-0.4
    Stephen Curry2020GSW-0.4
    Fred VanVleet2020TOR-0.4
    Bruno Fernando2020ATL-0.4
    Yogi Ferrell2020SAC-0.4
    Yuta Watanabe2020MEM-0.4
    Cedi Osman2020CLE-0.4
    Jeff Teague2020TOT-0.4
    Matisse Thybulle2020PHI-0.4
    Admiral Schofield2020WAS-0.4
    Nassir Little2020POR-0.4
    De’Aaron Fox2020SAC-0.4
    Frank Kaminsky2020PHO-0.4
    Khyri Thomas2020DET-0.4
    CJ McCollum2020POR-0.4
    Jake Layman2020MIN-0.4
    Alex Caruso2020LAL-0.4
    Rudy Gay2020SAS-0.4
    Kevin Huerter2020ATL-0.4
    Bol Bol2020DEN-0.4
    Michael Carter-Williams2020ORL-0.4
    Dragan Bender2020TOT-0.4
    Jonathan Isaac2020ORL-0.4
    Thabo Sefolosha2020HOU-0.4
    Jaylen Hoard2020POR-0.4
    Rodions Kurucs2020BRK-0.4
    Elie Okobo2020PHO-0.4
    Chuck Hayes2016HOU-0.5
    Nate Robinson2016NOP-0.5
    Steve Blake2016DET-0.5
    Trevor Booker2016UTA-0.5
    Jason Smith2016ORL-0.5
    Kevin Garnett*2016MIN-0.5
    Chris Copeland2016MIL-0.5
    Kyle O’Quinn2016NYK-0.5
    Kevin Martin2016TOT-0.5
    Al-Farouq Aminu2016POR-0.5
    James Johnson2016TOR-0.5
    Kelly Oubre Jr.2016WAS-0.5
    Thaddeus Young2016BRK-0.5
    Markel Brown2016BRK-0.5
    Robert Covington2016PHI-0.5
    Udonis Haslem2016MIA-0.5
    Al Jefferson2016CHO-0.5
    Rondae Hollis-Jefferson2016BRK-0.5
    Justin Holiday2016TOT-0.5
    Zach Randolph2016MEM-0.5
    Tayshaun Prince2016MIN-0.5
    Nick Collison2016OKC-0.5
    Bryce Dejean-Jones2016NOP-0.5
    Terrence Jones2016HOU-0.5
    Zaza Pachulia2016DAL-0.5
    Frank Kaminsky2016CHO-0.5
    Sasha Vujačić2016NYK-0.5
    Jeremy Lin2016CHO-0.5
    Justin Anderson2017TOT-0.5
    Tyler Ennis2017TOT-0.5
    Kyle Anderson2017SAS-0.5
    Shabazz Napier2017POR-0.5
    Adreian Payne2017MIN-0.5
    Lance Thomas2017NYK-0.5
    Mindaugas Kuzminskas2017NYK-0.5
    Thabo Sefolosha2017ATL-0.5
    Nicolás Brussino2017DAL-0.5
    Yogi Ferrell2017TOT-0.5
    Jaylen Brown2017BOS-0.5
    C.J. Watson2017ORL-0.5
    Kyle Wiltjer2017HOU-0.5
    Delon Wright2017TOR-0.5
    Nicolás Laprovíttola2017SAS-0.5
    Timothé Luwawu-Cabarrot2017PHI-0.5
    Kris Humphries2017ATL-0.5
    Pascal Siakam2017TOR-0.5
    Alex Len2017PHO-0.5
    LaMarcus Aldridge2017SAS-0.5
    Meyers Leonard2017POR-0.5
    Leandro Barbosa2017PHO-0.5
    Sean Kilpatrick2017BRK-0.5
    Anderson Varejão2017GSW-0.5
    Lavoy Allen2017IND-0.5
    Paul Millsap2018DEN-0.5
    Malcolm Delaney2018ATL-0.5
    Sindarius Thornwell2018LAC-0.5
    Matt Williams2018MIA-0.5
    Langston Galloway2018DET-0.5
    Timofey Mozgov2018BRK-0.5
    Nicolas Batum2018CHO-0.5
    Travis Wear2018LAL-0.5
    Thomas Bryant2018LAL-0.5
    Jonathon Simmons2018ORL-0.5
    Marcin Gortat2018WAS-0.5
    Bismack Biyombo2018ORL-0.5
    Tony Bradley2018UTA-0.5
    Antonius Cleveland2018TOT-0.5
    Sterling Brown2018MIL-0.5
    Wesley Johnson2018LAC-0.5
    Ricky Rubio2018UTA-0.5
    Derrick Jones Jr.2018TOT-0.5
    Bobby Portis2018CHI-0.5
    Georges Niang2018UTA-0.5
    Thaddeus Young2018IND-0.5
    Joel Embiid2018PHI-0.5
    Derrick Williams2018LAL-0.5
    C.J. Williams2018LAC-0.5
    Nikola Vučević2018ORL-0.5
    Denzel Valentine2018CHI-0.5
    Ben McLemore2018MEM-0.5
    Spencer Dinwiddie2018BRK-0.5
    Lorenzo Brown2018TOR-0.5
    Alec Burks2018UTA-0.5
    Trey Burke2019TOT-0.5
    Vince Edwards2019HOU-0.5
    Luka Dončić2019DAL-0.5
    Tim Frazier2019TOT-0.5
    Jayson Tatum2019BOS-0.5
    De’Aaron Fox2019SAC-0.5
    Ike Anigbogu2019IND-0.5
    Cedi Osman2019CLE-0.5
    Zhaire Smith2019PHI-0.5
    Damyean Dotson2019NYK-0.5
    Michael Beasley2019LAL-0.5
    Malachi Richardson2019TOR-0.5
    Patrick Patterson2019OKC-0.5
    Tyler Johnson2019TOT-0.5
    Evan Fournier2019ORL-0.5
    Josh Richardson2019MIA-0.5
    Joe Chealey2019CHO-0.5
    Frank Jackson2019NOP-0.5
    Deonte Burton2019OKC-0.5
    Jordan Clarkson2019CLE-0.5
    Ray Spalding2019TOT-0.5
    Jaylen Brown2019BOS-0.5
    Brandon Goodwin2019DEN-0.5
    D.J. Wilson2019MIL-0.5
    Aaron Holiday2019IND-0.5
    Tristan Thompson2019CLE-0.5
    Dorian Finney-Smith2019DAL-0.5
    Omari Spellman2019ATL-0.5
    Moritz Wagner2019LAL-0.5
    Courtney Lee2019TOT-0.5
    Noah Vonleh2019NYK-0.5
    Hamidou Diallo2019OKC-0.5
    Kyle Kuzma2019LAL-0.5
    Dragan Bender2019PHO-0.5
    Matt Mooney2020CLE-0.5
    Moses Brown2020POR-0.5
    Tariq Owens2020PHO-0.5
    Pascal Siakam2020TOR-0.5
    Justin James2020SAC-0.5
    Shabazz Napier2020TOT-0.5
    Anthony Tolliver2020TOT-0.5
    Caleb Swanigan2020TOT-0.5
    Amir Coffey2020LAC-0.5
    Anžejs Pasečņiks2020WAS-0.5
    Kyle Anderson2020MEM-0.5
    Marc Gasol2020TOR-0.5
    Malik Monk2020CHO-0.5
    Mo Bamba2020ORL-0.5
    Wenyen Gabriel2020TOT-0.5
    Louis King2020DET-0.5
    Denzel Valentine2020CHI-0.5
    Nigel Williams-Goss2020UTA-0.5
    Alize Johnson2020IND-0.5
    P.J. Washington2020CHO-0.5
    Justin Jackson2020DAL-0.5
    Goga Bitadze2020IND-0.5
    Amile Jefferson2020ORL-0.5
    Josh Okogie2020MIN-0.5
    Juan Hernangómez2020TOT-0.5
    Chandler Hutchison2020CHI-0.5
    Mario Hezonja2020POR-0.5
    Bryce Cotton2016TOT-0.6
    Aaron Harrison2016CHO-0.6
    Russ Smith2016MEM-0.6
    James Young2016BOS-0.6
    Anderson Varejão2016TOT-0.6
    Trey Burke2016UTA-0.6
    Damien Inglis2016MIL-0.6
    Kostas Papanikolaou2016DEN-0.6
    Kyle Singler2016OKC-0.6
    Andrea Bargnani2016BRK-0.6
    Marco Belinelli2016SAC-0.6
    Cameron Payne2016OKC-0.6
    Donatas Motiejūnas2016HOU-0.6
    Langston Galloway2016NYK-0.6
    Henry Sims2016BRK-0.6
    Chris Johnson2016UTA-0.6
    Raymond Felton2016DAL-0.6
    Shane Larkin2016BRK-0.6
    JaMychal Green2016MEM-0.6
    Nerlens Noel2016PHI-0.6
    Thomas Robinson2017LAL-0.6
    DeAndre’ Bembry2017ATL-0.6
    Kyle Singler2017OKC-0.6
    Daniel Ochefu2017WAS-0.6
    Nemanja Bjelica2017MIN-0.6
    Cheick Diallo2017NOP-0.6
    Timofey Mozgov2017LAL-0.6
    Kelly Oubre Jr.2017WAS-0.6
    Trevor Booker2017BRK-0.6
    Taurean Prince2017ATL-0.6
    Udonis Haslem2017MIA-0.6
    Taj Gibson2017TOT-0.6
    Jordan Mickey2017BOS-0.6
    Andre Roberson2017OKC-0.6
    Marshall Plumlee2017NYK-0.6
    Kentavious Caldwell-Pope2017DET-0.6
    Bruno Caboclo2017TOR-0.6
    Brandon Rush2017MIN-0.6
    Victor Oladipo2017OKC-0.6
    Joe Young2017IND-0.6
    Matt Barnes2017TOT-0.6
    Draymond Green2017GSW-0.6
    P.J. Tucker2017TOT-0.6
    Jamal Crawford2017LAC-0.6
    Lance Thomas2018NYK-0.6
    Jamal Crawford2018MIN-0.6
    Miles Plumlee2018ATL-0.6
    Timothé Luwawu-Cabarrot2018PHI-0.6
    Tony Allen2018NOP-0.6
    Markel Brown2018HOU-0.6
    Noah Vonleh2018TOT-0.6
    Robin Lopez2018CHI-0.6
    Dillon Brooks2018MEM-0.6
    Thon Maker2018MIL-0.6
    Demetrius Jackson2018TOT-0.6
    Quincy Acy2018BRK-0.6
    Shelvin Mack2018ORL-0.6
    Dwight Howard2018CHO-0.6
    Xavier Silas2018BOS-0.6
    Rajon Rondo2018NOP-0.6
    Dragan Bender2018PHO-0.6
    Ish Smith2018DET-0.6
    Josh Magette2018ATL-0.6
    Jake Layman2018POR-0.6
    Semi Ojeleye2018BOS-0.6
    Mike Conley2018MEM-0.6
    Terry Rozier2018BOS-0.6
    Wesley Iwundu2018ORL-0.6
    Marcus Paige2018CHO-0.6
    Jordan Mickey2018MIA-0.6
    Danny Green2018SAS-0.6
    Josh Hart2019LAL-0.6
    DeMarcus Cousins2019GSW-0.6
    Dion Waiters2019MIA-0.6
    Jaylen Morris2019MIL-0.6
    Sam Dekker2019TOT-0.6
    Jamal Crawford2019PHO-0.6
    Andrew Bogut2019GSW-0.6
    Justin Holiday2019TOT-0.6
    Lance Stephenson2019LAL-0.6
    Alec Burks2019TOT-0.6
    Brandon Ingram2019LAL-0.6
    Rodions Kurucs2019BRK-0.6
    Álex Abrines2019OKC-0.6
    Chandler Hutchison2019CHI-0.6
    Alize Johnson2019IND-0.6
    Bogdan Bogdanović2019SAC-0.6
    Markieff Morris2019TOT-0.6
    Mo Bamba2019ORL-0.6
    Tyler Dorsey2019TOT-0.6
    Solomon Hill2019NOP-0.6
    C.J. Miles2019TOT-0.6
    Cameron Payne2019TOT-0.6
    Jamal Murray2019DEN-0.6
    Donte DiVincenzo2019MIL-0.6
    Marc Gasol2019TOT-0.6
    Delon Wright2019TOT-0.6
    Isaiah Canaan2019TOT-0.6
    Daryl Macon2019DAL-0.6
    Josh Reaves2020DAL-0.6
    Bruno Caboclo2020TOT-0.6
    Rondae Hollis-Jefferson2020TOR-0.6
    Jaylen Nowell2020MIN-0.6
    Ed Davis2020UTA-0.6
    Josh Magette2020ORL-0.6
    Wayne Ellington2020NYK-0.6
    Oshae Brissett2020TOR-0.6
    Thanasis Antetokounmpo2020MIL-0.6
    Justin Patton2020OKC-0.6
    Cory Joseph2020SAC-0.6
    Mike Conley2020UTA-0.6
    Zach Norvell2020TOT-0.6
    Brandon Goodwin2020ATL-0.6
    Rodney McGruder2020LAC-0.6
    Udonis Haslem2020MIA-0.6
    Spencer Dinwiddie2020BRK-0.6
    Ja Morant2020MEM-0.6
    Tomáš Satoranský2020CHI-0.6
    Robin Lopez2020MIL-0.6
    DeMarre Carroll2020TOT-0.6
    Marko Guduric2020MEM-0.6
    Ricky Rubio2020PHO-0.6
    J.J. Barea2020DAL-0.6
    Lamar Patterson2016ATL-0.7
    Marcelo Huertas2016LAL-0.7
    Evan Turner2016BOS-0.7
    Spencer Hawes2016CHO-0.7
    Sonny Weems2016TOT-0.7
    Matt Barnes2016MEM-0.7
    Jared Cunningham2016TOT-0.7
    Beno Udrih2016TOT-0.7
    Roy Hibbert2016LAL-0.7
    Brandon Knight2016PHO-0.7
    Jeff Green2016TOT-0.7
    Aaron Brooks2016CHI-0.7
    Paul Pierce2016LAC-0.7
    DeMarcus Cousins2016SAC-0.7
    Luis Montero2016POR-0.7
    Alec Burks2016UTA-0.7
    Ray McCallum2016TOT-0.7
    Pat Connaughton2016POR-0.7
    Alexis Ajinça2016NOP-0.7
    Alan Williams2016PHO-0.7
    Brandon Jennings2016TOT-0.7
    Robert Sacre2016LAL-0.7
    Shelvin Mack2016TOT-0.7
    Rodney Stuckey2016IND-0.7
    P.J. Tucker2016PHO-0.7
    Ben McLemore2016SAC-0.7
    Cory Joseph2016TOR-0.7
    Danny Green2016SAS-0.7
    Aaron Brooks2017IND-0.7
    Nicolas Batum2017CHO-0.7
    Alexis Ajinça2017NOP-0.7
    Bryn Forbes2017SAS-0.7
    Randy Foye2017BRK-0.7
    Jarrod Uthoff2017DAL-0.7
    Dante Exum2017UTA-0.7
    Wayne Selden2017TOT-0.7
    Jordan McRae2017CLE-0.7
    John Wall2017WAS-0.7
    Okaro White2017MIA-0.7
    Aaron Harrison2017CHO-0.7
    Dahntay Jones2017CLE-0.7
    Cory Joseph2017TOR-0.7
    Briante Weber2017TOT-0.7
    Rodney Hood2017UTA-0.7
    Joffrey Lauvergne2017TOT-0.7
    Omri Casspi2017TOT-0.7
    Miles Plumlee2017TOT-0.7
    Wesley Johnson2017LAC-0.7
    Ryan Kelly2017ATL-0.7
    Joel Embiid2017PHI-0.7
    Troy Williams2017TOT-0.7
    Rodney McGruder2017MIA-0.7
    Noah Vonleh2017POR-0.7
    Hollis Thompson2017TOT-0.7
    Derrick Rose2017NYK-0.7
    Tomáš Satoranský2017WAS-0.7
    Brice Johnson2017LAC-0.7
    Terrence Jones2017TOT-0.7
    Denzel Valentine2017CHI-0.7
    Bismack Biyombo2017ORL-0.7
    Jamal Murray2017DEN-0.7
    Tony Parker2017SAS-0.7
    Matthew Dellavedova2018MIL-0.7
    Andre Drummond2018DET-0.7
    JaMychal Green2018MEM-0.7
    Luis Montero2018DET-0.7
    Nate Wolters2018UTA-0.7
    Henry Ellenson2018DET-0.7
    Sean Kilpatrick2018TOT-0.7
    Luol Deng2018LAL-0.7
    Shane Larkin2018BOS-0.7
    Damien Wilkins2018IND-0.7
    Terrence Ross2018ORL-0.7
    Evan Turner2018POR-0.7
    Donovan Mitchell2018UTA-0.7
    Kyle Singler2018OKC-0.7
    Devin Robinson2018WAS-0.7
    Al-Farouq Aminu2018POR-0.7
    Xavier Munford2018MIL-0.7
    José Calderón2019DET-0.7
    Frank Mason III2019SAC-0.7
    Greg Monroe2019TOT-0.7
    Haywood Highsmith2019PHI-0.7
    PJ Dozier2019BOS-0.7
    Jaylen Adams2019ATL-0.7
    Zaza Pachulia2019DET-0.7
    Tyus Jones2019MIN-0.7
    Yante Maten2019MIA-0.7
    Wesley Johnson2019TOT-0.7
    Shake Milton2019PHI-0.7
    Malik Monk2019CHO-0.7
    Draymond Green2019GSW-0.7
    Gary Harris2019DEN-0.7
    Timothé Luwawu-Cabarrot2019TOT-0.7
    Lonnie Walker2019SAS-0.7
    Deng Adel2019CLE-0.7
    Theo Pinson2019BRK-0.7
    Grayson Allen2019UTA-0.7
    DeMar DeRozan2019SAS-0.7
    Jalen Lecque2020PHO-0.7
    Chasson Randle2020GSW-0.7
    Jonah Bolden2020TOT-0.7
    Henry Ellenson2020BRK-0.7
    Antonius Cleveland2020DAL-0.7
    Ryan Anderson2020HOU-0.7
    Quinn Cook2020LAL-0.7
    Grant Williams2020BOS-0.7
    Brian Bowen2020IND-0.7
    Emmanuel Mudiay2020UTA-0.7
    Aaron Holiday2020IND-0.7
    Chris Chiozza2020TOT-0.7
    Juan Toscano-Anderson2020GSW-0.7
    Rui Hachimura2020WAS-0.7
    T.J. McConnell2020IND-0.7
    Reggie Jackson2020TOT-0.7
    Luguentz Dort2020OKC-0.7
    Wilson Chandler2020BRK-0.7
    Troy Brown Jr.2020WAS-0.7
    Kendrick Nunn2020MIA-0.7
    E’Twaun Moore2020NOP-0.7
    Tyler Johnson2020TOT-0.7
    Ian Mahinmi2020WAS-0.7
    Norvel Pelle2020PHI-0.7
    Isaiah Thomas2020WAS-0.7
    Keith Appling2016ORL-0.8
    T.J. McConnell2016PHI-0.8
    Jordan Clarkson2016LAL-0.8
    Kristaps Porziņģis2016NYK-0.8
    Shabazz Napier2016ORL-0.8
    Nick Young2016LAL-0.8
    Marreese Speights2016GSW-0.8
    Jerian Grant2016NYK-0.8
    Tyus Jones2016MIN-0.8
    Tyreke Evans2016NOP-0.8
    Charlie Villanueva2016DAL-0.8
    Elliot Williams2016MEM-0.8
    Gerald Green2016MIA-0.8
    Tony Allen2016MEM-0.8
    Ty Lawson2016TOT-0.8
    Cameron Bairstow2016CHI-0.8
    Dwyane Wade2016MIA-0.8
    Kendrick Perkins2016NOP-0.8
    Marc Gasol2016MEM-0.8
    Archie Goodwin2016PHO-0.8
    C.J. Watson2016ORL-0.8
    Jahlil Okafor2016PHI-0.8
    Matthew Dellavedova2017MIL-0.8
    DeAndre Liggins2017TOT-0.8
    Jordan Farmar2017SAC-0.8
    Isaiah Canaan2017CHI-0.8
    Dejounte Murray2017SAS-0.8
    Andrew Wiggins2017MIN-0.8
    Marquese Chriss2017PHO-0.8
    Dorian Finney-Smith2017DAL-0.8
    C.J. Wilcox2017ORL-0.8
    Ben Bentil2017DAL-0.8
    Ramon Sessions2017CHO-0.8
    Marcus Morris2017DET-0.8
    Paul Zipser2017CHI-0.8
    Shelvin Mack2017UTA-0.8
    Jordan Clarkson2017LAL-0.8
    Michael Gbinije2017DET-0.8
    Corey Brewer2017TOT-0.8
    Iman Shumpert2018CLE-0.8
    Gary Payton II2018TOT-0.8
    R.J. Hunter2018HOU-0.8
    Tyler Ennis2018LAL-0.8
    London Perrantes2018CLE-0.8
    Tyler Dorsey2018ATL-0.8
    Walt Lemon Jr.2018NOP-0.8
    Furkan Korkmaz2018PHI-0.8
    Ömer Aşık2018TOT-0.8
    Kadeem Allen2018BOS-0.8
    John Holland2018CLE-0.8
    Kristaps Porziņģis2018NYK-0.8
    Quincy Pondexter2018CHI-0.8
    Charles Cooke2018NOP-0.8
    Isaiah Whitehead2018BRK-0.8
    Tim Frazier2018WAS-0.8
    Jalen Jones2018TOT-0.8
    Willie Cauley-Stein2018SAC-0.8
    Austin Rivers2018LAC-0.8
    Jarell Martin2018MEM-0.8
    Cory Joseph2018IND-0.8
    Bruno Caboclo2018TOT-0.8
    Brandon Ingram2018LAL-0.8
    Udonis Haslem2018MIA-0.8
    Justin Holiday2018CHI-0.8
    Ramon Sessions2018TOT-0.8
    Jeff Teague2019MIN-0.8
    Keita Bates-Diop2019MIN-0.8
    Dillon Brooks2019MEM-0.8
    MarShon Brooks2019MEM-0.8
    Džanan Musa2019BRK-0.8
    Troy Brown Jr.2019WAS-0.8
    Jason Smith2019TOT-0.8
    Iman Shumpert2019TOT-0.8
    Naz Mitrou-Long2019UTA-0.8
    DeVaughn Akoon-Purcell2019DEN-0.8
    Rodney McGruder2019MIA-0.8
    Tim Hardaway Jr.2019TOT-0.8
    Jacob Evans2019GSW-0.8
    Harry Giles2019SAC-0.8
    Evan Turner2019POR-0.8
    Lance Thomas2019NYK-0.8
    Kenrich Williams2019NOP-0.8
    Wendell Carter Jr.2019CHI-0.8
    Luc Mbah a Moute2019LAC-0.8
    Dante Exum2019UTA-0.8
    Sviatoslav Mykhailiuk2019TOT-0.8
    Daniel Hamilton2019ATL-0.8
    Trae Young2019ATL-0.8
    Dewan Hernandez2020TOR-0.8
    Naz Mitrou-Long2020IND-0.8
    Malcolm Brogdon2020IND-0.8
    Zach Collins2020POR-0.8
    Frank Mason III2020MIL-0.8
    Terrance Ferguson2020OKC-0.8
    Garrett Temple2020BRK-0.8
    Jrue Holiday2020NOP-0.8
    Kevin Porter Jr.2020CLE-0.8
    D.J. Wilson2020MIL-0.8
    Reggie Bullock2020NYK-0.8
    T.J. Leaf2020IND-0.8
    Andre Iguodala2020MIA-0.8
    Matthew Dellavedova2020CLE-0.8
    Lonnie Walker2020SAS-0.8
    Stanley Johnson2020TOR-0.8
    Cody Martin2020CHO-0.8
    Patrick McCaw2020TOR-0.8
    Kadeem Allen2020NYK-0.8
    Carsen Edwards2020BOS-0.8
    Darius Bazley2020OKC-0.8
    Romeo Langford2020BOS-0.8
    Frank Jackson2020NOP-0.8
    Shayne Whittington2016IND-0.9
    Tim Frazier2016TOT-0.9
    Tony Snell2016CHI-0.9
    James Anderson2016SAC-0.9
    Corey Brewer2016HOU-0.9
    Josh McRoberts2016MIA-0.9
    Dennis Schröder2016ATL-0.9
    DeJuan Blair2016WAS-0.9
    JaKarr Sampson2016TOT-0.9
    Tibor Pleiß2016UTA-0.9
    Johnny O’Bryant2016MIL-0.9
    Cleanthony Early2016NYK-0.9
    Noah Vonleh2016POR-0.9
    Fred VanVleet2017TOR-0.9
    Stephen Zimmerman2017ORL-0.9
    Rondae Hollis-Jefferson2017BRK-0.9
    Dennis Schröder2017ATL-0.9
    A.J. Hammons2017DAL-0.9
    Raymond Felton2017LAC-0.9
    Jordan Hill2017MIN-0.9
    Darrun Hilliard2017DET-0.9
    Alec Burks2017UTA-0.9
    Tim Frazier2017NOP-0.9
    Boris Diaw2017UTA-0.9
    Henry Ellenson2017DET-0.9
    Robert Covington2017PHI-0.9
    Jonathon Simmons2017SAS-0.9
    Rashad Vaughn2017MIL-0.9
    Jarell Martin2017MEM-0.9
    Jrue Holiday2017NOP-0.9
    Marcelo Huertas2017LAL-0.9
    Damian Jones2017GSW-0.9
    Derrick Favors2017UTA-0.9
    Brandon Jennings2018MIL-0.9
    Jameer Nelson2018TOT-0.9
    Larry Drew II2018TOT-0.9
    Myke Henry2018MEM-0.9
    Patrick McCaw2018GSW-0.9
    Elfrid Payton2018TOT-0.9
    Raymond Felton2018OKC-0.9
    Josh Huestis2018OKC-0.9
    Darrun Hilliard2018SAS-0.9
    Jon Leuer2018DET-0.9
    Bobby Brown2018HOU-0.9
    Isaiah Hicks2018NYK-0.9
    Zach Randolph2018SAC-0.9
    Dwayne Bacon2018CHO-0.9
    Dwight Buycks2018DET-0.9
    Aaron Gordon2018ORL-0.9
    Jason Smith2018WAS-0.9
    Justin Patton2019PHI-0.9
    Khyri Thomas2019DET-0.9
    Kosta Koufos2019SAC-0.9
    Donovan Mitchell2019UTA-0.9
    Ron Baker2019TOT-0.9
    Allen Crabbe2019BRK-0.9
    Andre Drummond2019DET-0.9
    Aaron Gordon2019ORL-0.9
    Ian Clark2019NOP-0.9
    Shaquille Harrison2019CHI-0.9
    James Johnson2019MIA-0.9
    Edmond Sumner2019IND-0.9
    Donatas Motiejūnas2019SAS-0.9
    Tyrone Wallace2019LAC-0.9
    Terry Rozier2019BOS-0.9
    Austin Rivers2019TOT-0.9
    Elie Okobo2019PHO-0.9
    Stanton Kidd2020UTA-0.9
    Zhaire Smith2020PHI-0.9
    Quinndary Weatherspoon2020SAS-0.9
    Vince Carter2020ATL-0.9
    PJ Dozier2020DEN-0.9
    Devonte’ Graham2020CHO-0.9
    Kelan Martin2020MIN-0.9
    Marcus Smart2020BOS-0.9
    Edmond Sumner2020IND-0.9
    Kyle Kuzma2020LAL-0.9
    Michael Frazier2020HOU-0.9
    Gary Harris2020DEN-0.9
    Sterling Brown2020MIL-0.9
    Josh Richardson2020PHI-0.9
    Gary Payton II2020WAS-0.9
    Alfonzo McKinnie2020CLE-0.9
    Ish Smith2020WAS-0.9
    Anfernee Simons2020POR-0.9
    Jerome Robinson2020TOT-0.9
    Bobby Portis2020NYK-0.9
    Bruce Brown2020DET-0.9
    DeAndre’ Bembry2020ATL-0.9
    Kris Dunn2020CHI-0.9
    P.J. Hairston2016TOT-1
    Lou Amundson2016NYK-1
    Elton Brand2016PHI-1
    Kendall Marshall2016PHI-1
    Elijah Millsap2016UTA-1
    Phil Pressey2016TOT-1
    Jarrett Jack2016BRK-1
    Jerami Grant2016PHI-1
    Dion Waiters2016OKC-1
    Chris McCullough2016BRK-1
    Randy Foye2016TOT-1
    Jordan Hamilton2016NOP-1
    Iman Shumpert2016CLE-1
    Jeff Green2017ORL-1
    Diamond Stone2017LAC-1
    Alonzo Gee2017DEN-1
    Devin Booker2017PHO-1
    Julius Randle2017LAL-1
    T.J. McConnell2017PHI-1
    J.R. Smith2017CLE-1
    Sasha Vujačić2017NYK-1
    Marcus Thornton2017WAS-1
    Kent Bazemore2017ATL-1
    Monta Ellis2017IND-1
    Georges Niang2017IND-1
    Caris LeVert2018BRK-1
    Cameron Payne2018CHI-1
    Tony Parker2018SAS-1
    Georgios Papagiannis2018TOT-1
    Tyrone Wallace2018LAC-1
    Malachi Richardson2018TOT-1
    Alan Williams2018PHO-1
    Aron Baynes2018BOS-1
    Vander Blue2018LAL-1
    Dorian Finney-Smith2018DAL-1
    Kyle Collinsworth2018DAL-1
    Malik Monk2018CHO-1
    Johnny O’Bryant2018CHO-1
    Justise Winslow2018MIA-1
    Norman Powell2018TOR-1
    Tony Parker2019CHO-1
    Isaiah Briscoe2019ORL-1
    Andrew Harrison2019TOT-1
    Bruce Brown2019DET-1
    Melvin Frazier2019ORL-1
    Chimezie Metu2019SAS-1
    Devonte’ Graham2019CHO-1
    Carmelo Anthony2019HOU-1
    Wade Baldwin2019POR-1
    Lorenzo Brown2019TOR-1
    D’Angelo Russell2019BRK-1
    Andre Ingram2019LAL-1
    Quincy Acy2019PHO-1
    Ángel Delgado2019LAC-1
    Ricky Rubio2019UTA-1
    Josh Okogie2019MIN-1
    Shelvin Mack2019TOT-1
    Brandon Knight2019TOT-1
    Justin Wright-Foreman2020UTA-1
    Ignas Brazdeikis2020NYK-1
    Marial Shayok2020PHI-1
    Džanan Musa2020BRK-1
    Naz Reid2020MIN-1
    C.J. Miles2020WAS-1
    Vic Law2020ORL-1
    Allen Crabbe2020TOT-1
    Ty Jerome2020PHO-1
    Dion Waiters2020TOT-1
    Jordan McRae2020TOT-1
    Frank Ntilikina2020NYK-1
    Miles Bridges2020CHO-1
    Thaddeus Young2020CHI-1
    Nickeil Alexander-Walker2020NOP-1
    D’Angelo Russell2016LAL-1.1
    Dahntay Jones2016CLE-1.1
    Xavier Munford2016MEM-1.1
    Adreian Payne2016MIN-1.1
    Rajon Rondo2016SAC-1.1
    Justise Winslow2016MIA-1.1
    Anthony Brown2016LAL-1.1
    Monta Ellis2016IND-1.1
    Ryan Kelly2016LAL-1.1
    DeMarre Carroll2016TOR-1.1
    Jonathan Gibson2017DAL-1.1
    Kay Felder2017CLE-1.1
    Jake Layman2017POR-1.1
    Joakim Noah2017NYK-1.1
    Elfrid Payton2017ORL-1.1
    Terry Rozier2017BOS-1.1
    Robin Lopez2017CHI-1.1
    Justin Harper2017PHI-1.1
    Reggie Jackson2017DET-1.1
    Jahlil Okafor2017PHI-1.1
    Donatas Motiejūnas2017NOP-1.1
    Andrew Nicholson2017TOT-1.1
    D’Angelo Russell2017LAL-1.1
    Ron Baker2017NYK-1.1
    Metta World Peace2017LAL-1.1
    Tyreke Evans2017TOT-1.1
    Frank Kaminsky2017CHO-1.1
    Zach Collins2018POR-1.1
    Marquese Chriss2018PHO-1.1
    James Webb III2018BRK-1.1
    Andrew White2018ATL-1.1
    Caleb Swanigan2018POR-1.1
    Isaiah Taylor2018ATL-1.1
    Joe Johnson2018TOT-1.1
    Jaylen Morris2018ATL-1.1
    Kobi Simmons2018MEM-1.1
    Skal Labissière2018SAC-1.1
    Abdel Nader2018BOS-1.1
    Jamel Artis2018ORL-1.1
    Chandler Parsons2019MEM-1.1
    Antonio Blakeney2019CHI-1.1
    Michael Carter-Williams2019TOT-1.1
    Emmanuel Mudiay2019NYK-1.1
    Julian Washburn2019MEM-1.1
    Cory Joseph2019IND-1.1
    Ryan Anderson2019TOT-1.1
    Kent Bazemore2019ATL-1.1
    Kostas Antetokounmpo2019DAL-1.1
    Jared Terrell2019MIN-1.1
    Justise Winslow2019MIA-1.1
    Avery Bradley2019TOT-1.1
    Wayne Selden2019TOT-1.1
    Rajon Rondo2020LAL-1.1
    Lance Thomas2020BRK-1.1
    De’Anthony Melton2020MEM-1.1
    Jordan Bone2020DET-1.1
    Kevin Hervey2020OKC-1.1
    Jerian Grant2020WAS-1.1
    Kent Bazemore2020TOT-1.1
    Chandler Parsons2020ATL-1.1
    Kenrich Williams2020NOP-1.1
    Nicolas Batum2020CHO-1.1
    Jordan Adams2016MEM-1.2
    Devyn Marble2016ORL-1.2
    Joe Young2016IND-1.2
    John Wall2016WAS-1.2
    Rashad Vaughn2016MIL-1.2
    Metta World Peace2016LAL-1.2
    Bobby Portis2016CHI-1.2
    Spencer Dinwiddie2016DET-1.2
    Nikola Peković2016MIN-1.2
    Evan Turner2017POR-1.2
    Ronnie Price2017PHO-1.2
    Greivis Vásquez2017BRK-1.2
    Luol Deng2017LAL-1.2
    Dragan Bender2017PHO-1.2
    Lance Stephenson2017TOT-1.2
    Brandon Knight2017PHO-1.2
    Nigel Hayes2018TOT-1.2
    Lance Stephenson2018IND-1.2
    Derrick Rose2018TOT-1.2
    Reggie Jackson2018DET-1.2
    Mario Chalmers2018MEM-1.2
    Bonzie Colson2019MIL-1.2
    Goran Dragić2019MIA-1.2
    Isaac Bonga2019LAL-1.2
    Treveon Graham2019BRK-1.2
    Tony Bradley2019UTA-1.2
    Trey Lyles2019DEN-1.2
    DeAndre’ Bembry2019ATL-1.2
    Dirk Nowitzki2019DAL-1.2
    Dennis Schröder2019OKC-1.2
    J.P. Macura2019CHO-1.2
    Jawun Evans2019TOT-1.2
    De’Anthony Melton2019PHO-1.2
    Bobby Portis2019TOT-1.2
    Dejounte Murray2020SAS-1.2
    Brandon Knight2020TOT-1.2
    Michael Kidd-Gilchrist2020TOT-1.2
    Tristan Thompson2020CLE-1.2
    Treveon Graham2020TOT-1.2
    Jarrell Brantley2020UTA-1.2
    De’Andre Hunter2020ATL-1.2
    Drew Gooden2016WAS-1.3
    Thomas Robinson2016BRK-1.3
    Jameer Nelson2016DEN-1.3
    O.J. Mayo2016MIL-1.3
    Tyler Ulis2017PHO-1.3
    Toney Douglas2017MEM-1.3
    Dwyane Wade2017CHI-1.3
    Andrew Bogut2017TOT-1.3
    Jusuf Nurkić2017TOT-1.3
    Isaiah Taylor2017HOU-1.3
    Mario Hezonja2017ORL-1.3
    Anthony Brown2017TOT-1.3
    Al-Farouq Aminu2017POR-1.3
    Michael Carter-Williams2018CHO-1.3
    Jarrett Jack2018NYK-1.3
    Jusuf Nurkić2018POR-1.3
    Dennis Schröder2018ATL-1.3
    Marc Gasol2018MEM-1.3
    Paul Zipser2018CHI-1.3
    Antonio Blakeney2018CHI-1.3
    Dwyane Wade2019MIA-1.3
    Billy Garrett2019NYK-1.3
    Caris LeVert2019BRK-1.3
    Victor Oladipo2019IND-1.3
    Gary Trent Jr.2019POR-1.3
    Isaac Humphries2019ATL-1.3
    Marquese Chriss2019TOT-1.3
    Stanley Johnson2019TOT-1.3
    Tim Frazier2020DET-1.3
    Draymond Green2020GSW-1.3
    Deonte Burton2020OKC-1.3
    Andrew Wiggins2020TOT-1.3
    Carmelo Anthony2020POR-1.3
    Evan Turner2020ATL-1.3
    Jacob Evans2020TOT-1.3
    Ky Bowman2020GSW-1.3
    Eric Gordon2020HOU-1.3
    Markelle Fultz2020ORL-1.3
    Lonzo Ball2020NOP-1.3
    Aaron Gordon2020ORL-1.3
    Kevin Knox2020NYK-1.3
    Alex Stepheson2016TOT-1.4
    Terry Rozier2016BOS-1.4
    Kevin Séraphin2016NYK-1.4
    Marcus Smart2016BOS-1.4
    Michael Carter-Williams2016MIL-1.4
    Josh Richardson2017MIA-1.4
    Pierre Jackson2017DAL-1.4
    Tony Allen2017MEM-1.4
    Sergio Rodríguez2017PHI-1.4
    Malcolm Delaney2017ATL-1.4
    Trey Lyles2017UTA-1.4
    Mike Tobey2017CHO-1.4
    Andrew Harrison2017MEM-1.4
    Domantas Sabonis2017OKC-1.4
    Andre Drummond2017DET-1.4
    Semaj Christon2017OKC-1.4
    Damion Lee2018ATL-1.4
    Dwyane Wade2018TOT-1.4
    Stanley Johnson2018DET-1.4
    Frank Mason III2018SAC-1.4
    Tyler Ulis2018PHO-1.4
    Will Barton2019DEN-1.4
    Mario Hezonja2019NYK-1.4
    Dairis Bertāns2019NOP-1.4
    Udonis Haslem2019MIA-1.4
    Ish Smith2019DET-1.4
    J.R. Smith2020LAL-1.4
    B.J. Johnson2020ORL-1.4
    Hamidou Diallo2020OKC-1.4
    Lorenzo Brown2016PHO-1.5
    Jared Sullinger2016BOS-1.5
    Josh Smith2016TOT-1.5
    Brandon Jennings2017TOT-1.5
    Patricio Garino2017ORL-1.5
    Rodney Stuckey2017IND-1.5
    Mike Scott2017ATL-1.5
    Nikola Vučević2017ORL-1.5
    Dion Waiters2017MIA-1.5
    Kris Dunn2017MIN-1.5
    Stanley Johnson2017DET-1.5
    Lamar Patterson2017ATL-1.5
    Norris Cole2017OKC-1.5
    Zhou Qi2018HOU-1.5
    Davon Reed2018PHO-1.5
    Carmelo Anthony2018OKC-1.5
    Jonathan Isaac2018ORL-1.5
    Jawun Evans2018LAC-1.5
    John Wall2018WAS-1.5
    John Wall2019WAS-1.5
    J.J. Barea2019DAL-1.5
    Elfrid Payton2019NOP-1.5
    J.R. Smith2019CLE-1.5
    Jevon Carter2019MEM-1.5
    Rajon Rondo2019LAL-1.5
    Lonzo Ball2019LAL-1.5
    William Howard2020HOU-1.5
    Luka Šamanić2020SAS-1.5
    Kevon Looney2020GSW-1.5
    Dillon Brooks2020MEM-1.5
    Norris Cole2016NOP-1.6
    Greivis Vásquez2016MIL-1.6
    Dario Šarić2017PHI-1.6
    Isaiah Whitehead2017BRK-1.6
    Josh McRoberts2017MIA-1.6
    Ish Smith2017DET-1.6
    DeAndre’ Bembry2018ATL-1.6
    Emmanuel Mudiay2018TOT-1.6
    Kay Felder2018TOT-1.6
    Russell Westbrook2018OKC-1.6
    Dejounte Murray2018SAS-1.6
    Mike James2018TOT-1.6
    Jonathon Simmons2019TOT-1.6
    Caleb Swanigan2019TOT-1.6
    Iman Shumpert2020BRK-1.6
    Dewayne Dedmon2020TOT-1.6
    Coby White2020CHI-1.6
    Devon Hall2020OKC-1.6
    Justin Anderson2020BRK-1.6
    Tyrone Wallace2020ATL-1.6
    Bruno Caboclo2016TOR-1.7
    Alex Len2016PHO-1.7
    Briante Weber2016TOT-1.7
    Andre Drummond2016DET-1.7
    Wade Baldwin2017MEM-1.7
    Chandler Parsons2017MEM-1.7
    Brandon Ingram2017LAL-1.7
    Marcus Smart2017BOS-1.7
    D’Angelo Russell2018BRK-1.7
    Andrew Wiggins2018MIN-1.7
    Yuta Watanabe2019MEM-1.7
    Collin Sexton2019CLE-1.7
    Rawle Alkins2019CHI-1.7
    Jerryd Bayless2019MIN-1.7
    Dennis Smith Jr.2019TOT-1.7
    Tyreke Evans2019IND-1.7
    Joe Chealey2020CHO-1.7
    Marvin Bagley III2020SAC-1.7
    Andre Drummond2020TOT-1.7
    Cam Reddish2020ATL-1.7
    Sekou Doumbouya2020DET-1.7
    Russell Westbrook2020HOU-1.7
    Elfrid Payton2016ORL-1.8
    Markieff Morris2016TOT-1.8
    Joakim Noah2016CHI-1.8
    Jared Sullinger2017TOR-1.8
    Chinanu Onuaku2018HOU-1.8
    Solomon Hill2018NOP-1.8
    Frank Ntilikina2018NYK-1.8
    Zach LaVine2018CHI-1.8
    Avery Bradley2018TOT-1.8
    Julius Randle2020NYK-1.8
    Tremont Waters2020BOS-1.8
    Caris LeVert2020BRK-1.8
    Julius Randle2016LAL-1.9
    Orlando Johnson2016TOT-1.9
    Gary Payton II2017MIL-1.9
    Gary Neal2017ATL-1.9
    Rajon Rondo2017CHI-1.9
    Zach Randolph2017MEM-1.9
    Rodney Purvis2018ORL-1.9
    Josh Jackson2019PHO-1.9
    Walt Lemon Jr.2019CHI-1.9
    Jemerrio Jones2019LAL-1.9
    Darius Garland2020CLE-1.9
    Taurean Prince2020BRK-1.9
    Stanley Johnson2016DET-2
    Cameron Payne2017TOT-2
    Isaiah Thomas2018TOT-2
    Milton Doyle2018BRK-2
    Marcus Smart2018BOS-2
    Andre Roberson2020OKC-2
    Jarrett Culver2020MIN-2
    Victor Oladipo2020IND-2
    Gabe Vincent2020MIA-2
    Theo Pinson2020BRK-2
    Elfrid Payton2020NYK-2
    Derrick Rose2016CHI-2.1
    Kobe Bryant*2016LAL-2.1
    Ish Smith2016TOT-2.1
    Michael Carter-Williams2017CHI-2.1
    Manny Harris2017DAL-2.1
    Kris Dunn2018CHI-2.1
    Rondae Hollis-Jefferson2019BRK-2.1
    Kris Dunn2019CHI-2.1
    Markelle Fultz2019PHI-2.1
    Frank Ntilikina2019NYK-2.1
    Al-Farouq Aminu2020ORL-2.1
    Jusuf Nurkić2016DEN-2.2
    Emmanuel Mudiay2017DEN-2.2
    De’Aaron Fox2018SAC-2.2
    Josh Jackson2018PHO-2.2
    Dion Waiters2018MIA-2.3
    Isaiah Thomas2019DEN-2.3
    Jordan Poole2020GSW-2.3
    Dwayne Bacon2020CHO-2.3
    Elijah Millsap2017PHO-2.4
    Aaron Harrison2018DAL-2.4
    Andrew Wiggins2019MIN-2.4
    Russell Westbrook2019OKC-2.5
    Lonzo Ball2018LAL-2.6
    Kevin Knox2019NYK-2.6
    Jimmer Fredette2019PHO-2.6
    Dennis Smith Jr.2020NYK-2.6
    RJ Barrett2020NYK-2.6
    Dusty Hannahs2019MEM-2.7
    Blake Griffin2020DET-2.8
    Jerryd Bayless2017PHI-2.9
    Markelle Fultz2018PHI-2.9
    Aaron Jackson2018HOU-2.9
    Dennis Smith Jr.2018DAL-2.9
    Justise Winslow2020MIA-3.1
    Duje Dukan2016SAC-3.2
    Marquis Teague2018MEM-3.4
    Josh Gray2018PHO-3.4
    Emmanuel Mudiay2016DEN-3.5
    Tony Wroten2016PHI-3.6
    Justise Winslow2017MIA-4.3
    Xavier Rathan-Mayes2018MEM-4.3

    Curry’s second MVP campaign was an outlier among outliers, with a z-score of 7.2 standard deviations above league-average over the five-year sample. The data was approximately normal, but with a steep curve (standard deviation of 0.9), so the abnormal z-score isn’t simply anomalous; it was a season for the ages! 99.7% of seasons clocked in between scores of -2.9 and 2.5, so the scores that grace the front page of the table represent the cream of the crop of player seasons. Interestingly, James Harden’s 2019 season finishes eleventh as his second-best scoring season despite posting the highest scoring rate in league history. This exemplifies the importance of efficiency to the metric; because after all, a shot missed is of equal magnitude to a shot made. The traditional criteria for comparing volume against average efficiency is likely undervaluing the effects of missed field goals.

    How is Scorer Rating different from Scoring Value? Well, Curry’s 2016 score of 6.4 points is nearly double that of his 3.3 points in ScoreVal, so the aesthetic disparity is clear enough. But, conceptually, what sets these two metrics apart? ScoreVal is actually drawn from the scoring component of a Box Plus/Minus model, so the metric is derived from a regression model. Scorer Rating was created as a standalone metric based on theory and expected values, separate from how different scoring statistics relate to a player’s impact. Comparatively, the player rankings of the two metrics are quite similar, but there’s an inherent disagreement on point values. While ScoreVal’s formula is proprietary, Scorer Rating uses a universal counting principle. For example, if Stephen Curry had 23.8 scoring possessions per 100 team possessions and averaged 0.267 points per possessions relative to league-average, then his raw score is the product of those two. ScoreVal seems to use efficiency in a percentage like true shooting. If a player averages 1.2 points per true-shooting attempt, his TS% is 60%. 

    We can look at how the importance of volume and efficiency has changed over the past five years. During the 2015-16 season, volume had a surprisingly low relationship with Scorer Rating, posting a correlation coefficient of 0.43 while TS% was moderately stronger: 0.58. At the player level, the gap between the two scores is enough to suggest efficiency was more important in that season, but we can continue with further seasons to track any notable changes. Volume held slightly-more significance in 2017 with an r-value of 0.49 while efficiency was almost identical to its 2016 value: 0.59. The gap does lessen, but the trend holds: efficiency is, at least, just as important. (Fun fact: Russell Westbrook led the league in scoring rate that season at 33.6 points per 75, but posted a Scorer Rating of just 0.3 points because of mild efficiency.)

    Stephen Curry’s league-leading efficiency and volume made him the most valuable scorer of the second-half of the decade.

    Neither efficiency nor volume alone was very indicative of a player’s scoring value in 2018. The efficiency coefficient fell to 0.44 while its volume counterpart also dropped to 0.31. The season may not have been full of descriptive power, but let’s not gloss over the fact that Stephen Curry was a James Harden away from leading the league in scoring rate and efficiency once again! Efficiency again seems to be losing value from its previous seasons as its relationship with Scorer Rating falls just under 0.5 at 0.48 and volume takes a rise to 0.38. The clear message with these four seasons is that importance fluctuates from year-to-year, but a strong assertion holds: efficiency is drastically undervalued in evaluating scoring. The nail in the coffin was this last season, in which volume had a typical correlation of 0.41 while efficiency skyrockets to 0.6! A lesson is taught by Scorer Rating: the tendency to neglect efficiency for high volume is a blur to a player’s true value as a scorer.

    The other route to go about comparing efficiency and volume is conceptual. How else can we interpret the results of Scorer Rating’s relationships with volume and efficiency? For one, it confirms a belief I’d held since the Harden debacle in the prospect of his trade to the Miami Heat. High-volume scoring doesn’t easily evolve on greater and greater offenses. A diminishing returns effect kicks in quite fast on these less-scalable traits. Unless that scorer is a Harden-like player, who eats into teammates’ possessions, his scoring rate will see a notable decrease. Therefore, volume scoring is more of a floor-raising skill. It’s most valuable on teams with poor to mediocre offenses and good to great defenses, in need of that scoring boost to truly take off. Efficiency, on the other hand, is the ceiling-raising technique. Given the relatively small range of scoring attempts among teams, being able to capitalize through efficiency is a safer bet to post a highly-efficient offense.

    Allen Iverson: a perfect example of a high-volume, floor-raising scorer.

    There’s one last thing to consider when it comes to a player’s scoring value: it’s not the same as his scoring abilities. A second diminishing returns effect we haven’t yet discussed relates to a player’s efficiency and shot frequency: more attempts equals lower efficiency. This is a traditionally-accepted concept that explains why all 100% shooters usually take three total shots or less. A player like Duncan Robinson may not be able to replicate his 64.3 scoring percentage on more than his actual 11 attempts per game, but in terms of how his scoring impacted the scoreboard, he’s among the top of the league. It’s entirely valid to assign a higher value to volume when choosing the league’s most talented scorers, but it’d be unwise to forget about efficiency in any scenario…

    … and, Stephen Curry’s 2016 was the greatest season for a scorer in NBA history.