Author: chromeder


  • The Psychology of Basketball (Part 2 – Dissecting Traditional Values)

    The Psychology of Basketball (Part 2 – Dissecting Traditional Values)

    Nowadays, you’re either an eye-test guy or stats guy, right? There seems to be no acceptable middle ground, especially to the side I’ll take a deep-dive into today, the “traditionalists.” The use of any intelligible statistic beyond the box score signals someone who skims a Basketball-Reference page to evaluate a player, a common notion set forth by some. I haven’t absorbed the entirety of the traditionalist standpoint; so, to gain insight on what it entails, I turned to Ekam Nagra, the face of the “Ball Don’t Stop” Instagram page, a platform he uses to host a podcast. He will often use his posts to share his ideas on how analytics are poor tools to evaluate players, at times to interview former and current NBA players with similar opinions.

    Through my time spent learning the tendencies of his methods, I believe I’ve found a reasonable set of pillars that provide the structure for his evaluations, rankings, or any other process that requires player assessment:

    • Because the rules of basketball dictate the value of a possession to rely on whether or not the ball is scored, the most valuable individual trait is also scoring.
    • The previous view can be further defined to focus on volume scoring (although Nagra has expressed a distaste for the term in the past), with a crucial context of efficiency being the difficulty of the defensive scheming and the type of shot.
    • Defense, on the player and team levels, is less of an individual quality than offense because the latter dictates the momentum on the defensive end (offense “creates” defense in a way).
    • Statistics and analytics, in essence, lack context and are watered-down interpretations of court actions used as a flimsy replacement for “true” explanation.
    • Lastly, basketball analysis is an esoteric field. It requires direct, firsthand experience as a competitive basketball athlete to attain a higher ability to comprehend game actions.

    Anyone familiar with my previous work knows my evaluation tendencies, ones because of which Nagra would almost certainly dub me an “analytics boy” or a “stat fan.” I consistently use statistics and impact metrics in my end-of-season evaluations, so as a potential disclaimer, I am writing from a “progressive” perspective (i.e. in support of the analytics movement). Thus, I’ll dissect the meaning of Nagra’s explicit and implicit rationale to provide an analytical alternative, which will hopefully take the series an extra step further in the truer understanding of the psychology behind basketball.

    Scoring Blindness

    As I discussed in the first installment of the series, as defined by the Thinking Basketball book, “scoring blindness” is the tendency of a critic to overrate the contributions of a team’s highest-volume scorer (i.e. the player who leads his team in points per game). Although I don’t agree with the employment of such a method, I understand the concept behind it: if the point of a possession on offense is to score the basketball, then the best players will likely score most often. (This is something I generally agree with). However, Nagra takes it a step further in Episode 91 of the “Ball Don’t Stop” podcast, from which the following quote is derived:

    “… It just drives me crazy when I hear this, and I laugh, and it’s usually people that never played basketball saying this, or people that never really scored when they did play basketball, saying, ‘Oh, he’s just a scorer.’ … ‘You know, he’s the best scorer, he’s not the best player.’ … Scoring isn’t everything in basketball, but I’ll be the first to tell you it is by far the main thing. The name of the game is getting buckets.” (Ekam Nagra – Episode 91 of the “Ball Don’t Stop” podcast)

    I understand the train of thought behind Nagra’s beliefs. A team’s efficacy on offense is entirely dependent on how frequently they score the ball. This is why a team’s Offensive Rating is so widely used; it measures how good a team was at performing its offensive duties. Therefore, the “best” offensive players make the largest scoring contributions. However, I think it’s a misstep to connect scoring on the team level to individual scoring on the player level. This claim relies on the belief that individual scoring is not the only way to positively influence a team’s offense. High-level shot creation that unclogs the floor and opens more efficient attempts is, in fact, usually more effective to the team compared to consistent “hero-ball” and isolation possessions.

    Scoring blindness is, as stated earlier, the propensity to rate players based on favorable points per game figures, and we see it in practice with the criteria Nagra uses the evaluate players:

    “The number one thing in basketball, the foundation of the game is putting the ball in the basket. The guys that did that the best are the guys that shined the brightest in the history of the game. They’re the ones that moved arenas, they’re the ones that sold jerseys, they’re the ones put teams on their back, the guys that are, you know, making sh*t happen on the basketball court.” (Ekam Nagra – Episode 91 of the “Ball Don’t Stop” Podcast)

    I’ll return to the tendency later, but Nagra consistently attributes questionable factors to a player’s “goodness,” such as the roar of the crowd, merchandising, and a touch of the “Lone Star Illusion” (the tendency to undervalue the effects of a supporting cast, another topic invoked by Thinking Basketball). A self-proclaimed former player, Nagra often relates the demanding environment of the NBA to street-ball or pick-up preferences:

    “It’s… it’s simple, you know, common f*cking sense. If me and you were to walk into a court today and, er, open run or tryout or whatever, the first guy that would stand out, the first guy we’d look for if we were smart, is the guy that’s putting the ball in the hoop.” (Ekam Nagra – Episode 91 of the “Ball Don’t Stop” Podcast)

    This reminds me of the mentality of middle or high-school roster selection, or the mindset of the young players, which pose the ultimate goal to be the best and brightest scorer. After all, almost everyone wanted to be the ones to hit the game winners and the clutch shots when they were young, and that means you would want to become the best scorer. As I dive deeper into Nagra’s evaluation style, I’ve become more convinced a lot of his rationale is based on his time as a player: who stood out and who appeared to be the best.

    Nagra gives another opinion that provides insight on how he relates scoring to team performance later on in the episode used for the aforementioned quotes:

    “But those teams that win, and these teams that are led, and teams that go far in the Playoffs, they’re the ones that have the best scorer on the floor… or the second-best scorer on the floor… at all times.” (Ekam Nagra – Episode 91 of the “Ball Don’t Stop” podcast)

    Because he doesn’t give any specific examples, we could investigate this claim to create a “stepping-off” point to see whether or not his claims are based on facts or the internal, intuitive feelings he conveyed earlier in the episode. To either confirm or deny this claim, we can look at the league-leaders in points per game in recent history and connect them with which round their teams advanced to in the second season. (He doesn’t give a specific round or the number of postseason games played to constitute teams that “go far in the Playoffs,” so I’ll assume the lower fence is a conference championship appearance.)

    If a (qualified) top-two finisher in points per game was on a team that advanced to the conference championship or further in the same season, he will receive a “Yes.” If a player’s team did not manage to reach the semi-finals, he will be denoted with a “No.”

    • 2019-20: James Harden (No) and Bradley Beal (No)
    • 2018-19: James Harden (No) and Paul George (No)
    • 2017-18: James Harden (Yes) and Anthony Davis (No)
    • 2016-17: Russell Westbrook (No) and James Harden (No)
    • 2015-16: Stephen Curry (Yes) and James Harden (No)
    • 2014-15: Russell Westbrook (No) and James Harden (Yes)
    • 2013-14: Kevin Durant (Yes) and Carmelo Anthony (No)
    • 2012-13: Carmelo Anthony (No) and Kevin Durant (No)
    • 2011-12: Kevin Durant (Yes) and Kobe Bryant (No)
    • 2010-11: Kevin Durant (Yes) and LeBron James (Yes)
    • 2009-10: Kevin Durant (No) and LeBron James (No)
    • 2008-09: Dwyane Wade (No) and LeBron James (Yes)
    • 2007-08: LeBron James (No) and Allen Iverson (No)
    • 2006-07: Kobe Bryant (No) and Carmelo Anthony (No)
    • 2005-06: Kobe Bryant (No) and Allen Iverson (No)

    During the last fifteen seasons, only 26.7% of either conference final series has sported one of the top-two finishers in points per game in the same season. Admittedly, this isn’t the largest sample there is, but it disproves that having one of the top-two volume scorers in the league guarantees a deep Playoff run. We’ve actually seen more of the opposite; teams seem to be more likely to appear in the conference finals without, say, a thirty points per game scorer. This isn’t to say a team’s leading scorer hurts his team (although he sometimes does), but that a dominating half-court “assassin” is not a prerequisite to a deep run in the postseason.

    Defensive Ignorance

    With the current state of information available at the hands of most, there was bound to be a lopsided partiality to offense compared to defense. Box scores will track the number of points, rebounds, assists, field-goals, and turnovers a player records in a given period, but defense is restricted to steals and blocks (personal fouls are usually associated with the defensive box score but also include offensive fouls). Nagra is no exception to this tendency, expressing a clear opinion in Episode 34 of his podcast, which covered the validity of the terminology given to “two-way players.”

    He immediately provides insight on how he distinguishes the best players:

    “You know, the foundation of this game, since day-one, will always be scoring. The defense, all that other stuff is a bonus.” (Ekam Nagra – Episode 34 of the “Ball Don’t Stop” podcast)

    As discussed earlier, this relates to the connection Nagra established between scoring on the team level with individual scoring on the player level. We have already concluded this connection is mostly false and overlooks the larger expanse of offensive contributions that leads to scoring output among teams, so it’s safe to say this mindset is setting up all further opinions that build on this principle for some level of failure.

    However, it seems the prioritizing of high-volume scorer extends further than the structure of the game Nagra lays out:

    “The most feared thing in basketball, till this day, is a guy that can walk into a game and effortlessly get you thirty, forty, and fifty [points].” (Ekam Nagra – Episode 34 of the “Ball Don’t Stop” podcast)

    “I’ve never seen a coach break his clipboard because of two-way players just being a two-way player.” (Ekam Nagra – Episode 34 of the “Ball Don’t Stop” podcast)

    “You know, those are the guys [scorers] that people remember forever…” (Ekam Nagra – Episode 34 of the “Ball Don’t Stop” podcast)

    The common denominator of each sentiment is the reactivity to surroundings, especially emotionally-driven ones: fear, anger, and remembrance. Yet, Nagra uses these elements to evaluate on-court impact. The individual perceptions of these game actions may not even roughly correlate to value as a player, but he continually treats them otherwise. This relates to my earlier inferences that suggest Nagra structures his knowledge of basketball around his experiences as a player. However, as we explore later, having played basketball at even the highest level does not guarantee a higher ability to evaluate players.

    During the same segments, Nagra explores what he believes to be an inherent disparity between offensive and defensive contributions, the former of which drastically outweighs the latter:

    “Carmelo Anthony on the Knicks… top-four player in the game. You know, I didn’t care if he played defense or not. The fact that he could walk into a game and singlehandedly change the outcome, and… you know, have an impact on the game with just his scoring ability – that right there is it for me.” (Ekam Nagra – Episode 34 of the “Ball Don’t Stop” podcast)

    “Hey, if you’re a good defensive player, you’re a good defensive player. If you can score the hell out of the ball, you know, you’re a killer, you’re an assassin out there.” (Ekam Nagra – Episode 34 of the “Ball Don’t Stop” podcast)

    “You know, Michael Jordan and Kobe Bryant were the same way [skilled on offense and defense]. Like, I never saw anyone dub them as ‘two-way players.’ They were just the best players in the game… Them playing defense was a bonus.” (Ekam Nagra – Episode 34 of the “Ball Don’t Stop” podcast)

    Defense is consistently treated as a secondary trait, a bonus, to offense. Nagra suggested no other skill in basketball matters if, at the end of the day, the ball wasn’t going in the basket. He doesn’t hold this to be self-evident; rather, the rules of basketball (which require a bucket to be had) make it so. This is more antithetical to how basketball is played than Nagra gives credit for. Through the entirety of his segments that cover scoring or defense, he doesn’t address that the magnitude of a two-point basket on offense is equal to that of a two-point basket allowed on defense. If the world’s greatest offensive player is worth 1.3 points per team possession but allows 1.3 points per possession on defense, he’s not helping his team win at all!

    “Correctness”

    The last revealing quotation from Episode 34 comes with his disagreement on the soundness of dubbing “two-way” play:

    “What the f*ck is a two-way player? Like, who came up with this concept? You know, if you look back at it, like… I never heard this in the ‘90s. I never heard this in the 2000s.” (Ekam Nagra – Episode 34 of the “Ball Don’t Stop” podcast)

    Nagra displays a clear bias toward styles of basketball that align with the styles of play that were most prevalent in his youthhood, with a strong emphasis on jump shots. During Episode 36, he provides this excerpt on a tendency he observed upon LeBron James’s arrival in Miami:

    “I didn’t like it when he [LeBron James] went to the Miami Heat and he was like, ‘Hey, I’m not gonna shoot threes anymore; or, I’m gonna shoot less jumpers.’ … I didn’t feel like that was pure. You know, you can’t really cheat the game. You can’t be… like, it is what it is. You gotta make jump shots. In basketball, the foundation is ‘get a bucket,’ score a jump shot, all these things. You know, they matter.” (Ekam Nagra – Episode 36 of the “Ball Don’t Stop” podcast)

    During his discussion on why he believed Kawhi Leonard was the second-best player in basketball, Nagra heavily implies a “proper” or “correct” version of basketball exists that some of the league’s players have violated. He, again, refers to his foundation of the game (to get a bucket), the misinterpretation of which already dilutes the quality of any appendages, but then extends it to: “You gotta make jump shots.” To improve the team’s offense, it would be undeniably more effective for the unit to score fifty-five easy layups (if those were somehow available) than to score thirty, forty, or even fifty-four of the most difficult mid-range shots in league history. After all, the team that scores the most wins!

    Nagra’s inclinations toward his most prized styles of play signal heavy biases, and ones that cloud the truth behind “effective” basketball play as ones that are flashy, memorable, and visually remarkable. Thus, I don’t immediately absorb the opinions he states as ones of proper consideration, rather ones driven by personal preferences that don’t relate to the “true” topic at hand, which makes these claims nothing more than opinions in a sea of truth and falsehood.

    We’ll fast-forward to Episode 211 of the Ball Don’t Stop podcast, in which Nagra an All-Rookie and All-Defensive former NBA player in Josh Smith. When Nagra asks Smith what the latter’s reaction was upon the arrival of the analytics revolution, Smith replies with:

    “It [the analytics revolution] felt weird because… you know, when you start playing basketball, you’re taught the game the right way. You know, like, you know, mid-range, layups, three-pointers, you know, like… getting your teammates the ball… You gotta start inside out.” (Josh Smith – Episode 211 of the “Ball Don’t Stop” podcast)

    There’s a recurring theme in the “Ball Don’t Stop” podcasts that distinguish a “proper” way to play the game, one that paves the way for Nagra’s (and former players alike) distaste of basketball analytics and advanced statistics.

    Authority

    Among the pillars of traditional values stated earlier was the extreme value of having experienced the competitive and rigorous environment of professional or semi-professional basketball play. If such a trait doesn’t reside within the individual, he or she is automatically less able to discuss the evaluations of a player at a higher level.

    During Episode 211, he interviews an All-Rookie and All-Defensive former NBA player in Josh Smith. Nagra wastes no time in expressing disinterest in the analytics revolution and modernized statistics:

    “I feel like the game now, as talented as it is, as athletic as it is, they’ve [analytics and its supporters] kind of dumbed it down, the way it’s played, man; and like, it’s just weird to me.” (Ekam Nagra – Episode 211 of the “Ball Don’t Stop podcast)

    As we’ll explore later, Nagra sees the analytics revolution and its associated forthcoming as having deteriorated the play of the game, crucial context for later excerpts. Smith follows later in the episode with his own take on how players approach analytics:

    “As a player, how can you listen to a person that never played the game of basketball? ‘Cause most of those analytical guys… have never played a game of basketball, so they don’t have a feel of… what’s really going on… and time and situation and… the mental aspect of the game… You can’t put that in the analytics.” (Josh Smith – Episode 211 of the “Ball Don’t Stop” podcast)

    Smith certainly doesn’t speak for all players, especially the recently-employed more familiar with the analytical setting (Smith played his last full season in 2015-16), but there seems to be some notable stigma towards the analytics departments of NBA teams among players. They feel, as few to none of the analysts were players themselves, the analysts are not as qualified to dictate the tendencies and playstyles of those that are or were experienced as NBA players. Smith said that the lack of hands-on experience prohibited analytics developers from comprehending and incorporating the necessary elements.

    I’ve never played in the NBA, so perhaps there’s something that I’m missing, but no matter who you are or what your experience with basketball is, the exact same forty-eight minutes of play (barring overtime) is available to any and all who can watch. At the end of the day, all of the court actions that a player is involved in can be absorbed by an outside observer. Granted, the comprehension of these court actions is a skill, and one that requires great knowledge and practice; but the only aspect of the game that a non-player can’t directly recognize is the “mental” aspect: what flows through the players’ minds. The ability to experience these may add context to the triggers behind varying neurological patterns in certain moments; but as Nagra continuously states, victory is crowned by scoring more than the opponent. No aspect of a player’s impact is exclusive to former or current players.

    As Nagra and Smith continue their conversation, the latter gives more of his thoughts on how analytics is changing the game and, more specifically, how it affects the NBA as a show business:

    “It’s sad, because… I feel like it’s gonna eventually take… the ratings are gonna start going down because… like, the exciting part of the game was dunking on motherf*ckers… like, putting that sh*t in the rim, putting they *ss in the rim… It’s like, all these threes and layups and floaters and sh*t… It’s taking the excitement out of the game.” (Josh Smith – Episode 211 of the “Ball Don’t Stop” podcast)

    Smith clearly connects his distaste of analytics to how it affects the style of the game, an aspect for which Nagra also expressed concern. It’s not unreasonable to say that the pace-and-space style of basketball spurred by analytics makes the viewing experience less exciting, but then again, analytics were not created to improve game ratings. Analytics were created to give players and teams the highest odds to win. Advanced statistics and impact metrics aim to quantify and structure a player’s or team’s impact, not either’s likelihood of increasing viewer count. Thus, I see Nagra and Smith’s concern with analytics as not only misguided but untrue to the nature of its creation. Advanced statistics are not boosters of the NBA as a show business; they aim to provide explanatory and predictive power to help players and teams understand what happens on the court and to improve for the future.

    I went into this examination of “traditional” thinking with an open mind, even hoping to add a piece or two of its process to my own if I were to find the right evidence. Unfortunately, I don’t feel I’ve been given any more reason to revert to traditionalism given the alternatives (i.e. analytics). Nagra does not speak for all traditionalists and Smith doesn’t speak for all players, but the brief taste I had of their ideologies was nothing more than unimpressive. They aspire for a desirable style of play that, along with the growth of data and information, became obsolete. Now, there’s certainly nothing wrong with deprecating the current style of play as it pertains to the watching experience, but the same practice in evaluating players and teams is a method doomed for failure.

    Nagra peddles the belief that experience, or the lack thereof, is the problem in today’s game. To me, it’s less an issue stemming from experience, but the unrelenting tendency to hold onto ideals and the inability to adapt to an evolving game.


  • The Top 25 NBA Players of 2020 – A Remastered List (Part 2 #6-15)

    The Top 25 NBA Players of 2020 – A Remastered List (Part 2 #6-15)

    I’ve had more discussions on how to properly evaluate basketball players more times than I can count. More often than not, I’ve been met with disagreement in those conversations. After a very recent one that argued the very principles and measurements that govern and quantify certain skills, I was inspired to “remaster” my player rankings list from 2020. The recent acquisition of some proprietary data from BBall Index was the perfect opportunity to use new and refreshing information to increase the accuracy of my evaluations, and I’d like to share the results here.

    Criteria

    It’s very easy to skip a “criteria” section in a player ranking and go directly to the list, but such segments are the perfect indicators for why certain players appear in the spots they occupy. Therefore, if I receive any comments along the lines of: “Why is [insert player name] ranked so low? He averaged this many points, rebounds, and assists with this field-goal percentage, and his team record was this!” I will probably not respond. After all, this is not a list of which players have the sexiest box scores or which players’ teams were the best. The former merely quantifies tendencies and the latter is unrelated to individual performance as a whole, so they aren’t devices I’m particularly comfortable using.

    I’ve repeated my evaluation process in almost every post that pertains to the subject, and this one will be no exception. I follow a simple train of logic that, while not necessarily being an axiom of the process, is the “most likely” truth I’ve come across: 1) basketball is a team sport, and players are chosen to help improve the success of the team, 2) over the course of a whole season (the length of a “seasonal” evaluation), the ultimate team goal is to win the Finals, 3) therefore, the best players increase the likelihood of a championship the most. That chain of thought is often confused with prioritizing players whose teams performed the best or were the closest to winning a title in a given year. This is not the case. Players are seen as independent from their teams in these evaluations.

    Namely, “situational” value is not the target of this ranking due to significant levels of confoundment for certain players (i.e. certain team constructions can dilute the “true” value of a player). Rather, these evaluations consider how a player would affect all types of teams, ranging from the worst to the best ever and everything in between. To measure the championship likelihood a player provides, I estimate a player’s per-game impact alongside average teammates in a theoretically “average” system (metrics like Adjusted Plus/Minus capture the “most likely” value of this). However, this “true” APM value changes as a player enters a new environment. As the team quality falls below an SRS of 0, the player becomes more important (thus, his “true” APM rises) and, inversely, as the team’s SRS exceeds 0, the player becomes less and less important. The deceleration of the latter is measured through “portability,” which uses five scaling curves to estimate the degree to which these diminishing returns occur.

    To recap:

    • I translate all my thoughts on a player to a numerical scale that estimates a player’s “true” Adjusted Plus/Minus, or per-game impact alongside average teammates and against average opponents.
    • Portability ratings then measure the changes in “true” APM (which I call “Plus/Minus Rating,” or “PMR”) to estimate how a player impacts the more extreme team qualities.
    • The team SRS with versus without the player and how it translates to championship equity is determined using a function, based on historical data, that estimates title odds.
    • The weighted (for how likely a player would be on a given team) average of championship odds with and without a player is his Championship Probability Added (“CPA”) value.

    Note: The distribution of team SRS is based on the last fifty seasons of team data / Portability is more of a spectrum than anything else, so if two or more players have the same CPA value, I opt for which one is more scalable, even if the two happen to be assigned to the same scaling curve.

    With the criteria portion out of the way, let’s get into the juicier content: the rankings themselves. Earlier today, I kicked off the series with the #16 to #25 players, which is followed here with a separate post for the #6 to #15 players and will conclude with the top-five. Let’s dive in!

    HMs (include but are not limited to): De’Aaron Fox and Donovan Mitchell

    25. Bradley Beal

    24. Pascal Siakam

    23. Kyle Lowry

    22. Devin Booker

    21. Bam Adebayo

    20. Kemba Walker

    19. Jrue Holiday

    18. Chris Paul

    17. Jayson Tatum

    16. Khris Middleton

    15. Karl-Anthony Towns (C)

    Towns is blossoming into one of the sport’s greatest offensive big men ever right before our eyes. His outstanding outside shooting and scoring gravity have made him one of the most effective weapons at his position, and strong isolationism and finishing bolster the quality of his skill set. Towns is one of the league’s more troubled defenders; he has yet to get a groove on that front. He’s an effective interior defender at times, and he guarded fairly difficult opponents, but a lack of intensive engagement is the defining aspect of his defense.

    Championship Probability Added: 4.4%

    14. Paul George, Clippers (SF)

    It’s entirely fair to say Paul George was one of the least improved players in 2020, but the drop wasn’t quite enough for me to remove him from bordering superstar territory. He is still one of the most efficient and gravitational three-point shooters in the league with effective off-ball movement and surprisingly good playmaking as a secondary star in Los Angeles. He took a step back on defense with less activity in passing lanes compared to 2019, and his paint presence was nothing to marvel about, but I still saw George as a large plus defensively.

    Championship Probability Added: 4.6%

    13. Rudy Gobert, Jazz (C)

    The “Stifle Tower” isn’t the hot topic he was after winning two consecutive Defensive Player of the Year Awards, and rightfully so in a way. Recent data has suggested non-versatile big men who stick in the paint lose value in the Playoffs, and Gobert was no exception. However, the remnants of his defense, and especially his all-time level interior play, led me to believe he remained basketball’s best defender. Gobert would deter shots at the rim, he would prevent the potential points (he was in the 100th percentile in adjusted points saved at the rim per 36 minutes), and he would block shots more effectively than nearly any player in the league.

    Championship Probability Added: 4.8%

    12. Kyrie Irving, Nets (PG)

    Although he only played 20 games in the regular season and none of the Nets’ playoff games, Irving was still one of the top-four point guards in the league at full health. He was as good as he’d ever been offensively, displaying mastery in distance shooting, isolation, finishing, and creation. Irving is one of the rare engines who could quarterback a very good offense, and because he was in the 97th percentile in high-value assists per 75 possessions, I saw more to suggest Irving, despite all of his off-court issues, was one of the most impactful basketball players in the league.

    Championship Probability Added: 5.0%

    11. Jimmy Butler, Heat (SF)

    Jimmy Buckets blew my expectations out of the water in 2020. He’s known for having led Miami to an unexpected Finals berth, but the skill of his that stood out to me was his off-ball capabilities, which were among the very best in the league. Butler was in the 93rd percentile in points generated on cuts and shots off screens relative to league efficiency and covered a lot more ground than a lot of players with similar roles. He was also in the 98th percentile in matchup difficulty and the 99th and 98th percentile in position and role versatility on that end, which measure the diversity of the number of positions and offensive archetypes he guarded, respectively.

    Championship Probability Added: 5.3%

    10. Damian Lillard, Trail Blazers (PG)

    Lillard entered rarified air as an offensive player in the bubble, and a lot of it seemed to be clear, tangible improvement. He captivated fans en route to a “Bubble MVP” with his three-point logo shots (after all, he was in the 93rd percentile in average three-point shot distance). Lillard remained one of the sport’s very best isolation scorers, drivers, and playmakers. His passing was very versatile but not necessarily efficient, although this deficiency was compensated with top-tier creation and scoring gravity. Lillard’s defense was the weakness in his campaign, but it doesn’t drag him down any further than tenth on my list.

    Championship Probability Added: 6.7%

    9. Joel Embiid, 76ers (C)

    Joel Embiid doesn’t exactly fit the developing skills of the pace-and-space league of today, but his post play and interior defense make him one of the most valuable centers in the game. He was in the 99th percentile in both isolation attempts and impact per 75 possessions, the latter of which uses league-average efficiency as a baseline. Embiid also guarded some of the most difficult matchups in the league, ranking in the 95th and 88th percentiles in time spent guarding All-Star and All-NBA players, respectively. Although he didn’t have the outside shooting or perimeter defense to become a well-rounded superstar, the skill set he had ranked among the league’s very best.

    Championship Probability Added: 6.9%

    8. Luka Dončić, Mavericks (PG)

    The Slovenian wunderkind had one of the greatest seasons from a 20-year-old in the history of basketball. Dončić evolved into one of the league’s greatest finishers and passers, the latter of which was the primary reason for his offensive explosion. He was one of the most efficient and versatile passers in basketball, led the league in Box Creation, and received BBall Index‘s highest grade in playmaking not given to a player named LeBron James. The strong point of his offensive portfolio was how it cultivated the most efficient team offense in the history of the NBA. Granted, some of it was due to a recent offensive burst in the past few seasons, but Dončić has one of the brightest futures in the league as an offensive superstar.

    Championship Probability Added: 7.8%

    7. Nikola Jokić, Nuggets (C)

    Similar to his fellow European predecessor on this list, Nikola Jokić is one of the brightest stars in the NBA’s next wave of playmaking superstars. Despite his position, Jokić made a strong case as the very best passer in basketball, rivaling Dončić and the Finals MVP, LeBron James. He was also undervalued as an isolationist, ranking in the 95th percentile in frequency and the 88th in effective field-goal percentage on such possessions. Jokić used his burly frame to his advantage, playing a unique form of bully ball that allowed him to place in the 85th percentile in adjusted (for frequency) field-goal percentage at the rim. I couldn’t help but not view his defense as anything but a slight positive, as he was active in the interior with some of the league’s smoothest hands. Jokić is on the cusp of superstar play.

    Championship Probability Added: 8.5%

    6. James Harden, Rockets (SG)

    I’m not sure the “reasonable” range in which I could see Harden will ever change. He always seems to be in his own territory due to extremely impactful offensive play with a diverse skill set but the limited scalability and unnerving ball dominance to push him up among the league’s megastars. Regardless of which tier he falls under, it’s hard to deny he’s mastered nearly every skill on the offensive end: shooting, finishing, passing, creation, and foul (baiting) drawing. Harden’s skills, admittedly, don’t translate to the playoffs as well as others, but the degree to which it does is far less strenuous than most will suggest. Aside from strength in the post with moderate effectiveness on shot contests on the perimeter, his defense is a very mild negative to me. Because he plays in a time with so much star talent, it’s easy to overlook Harden now, but his performances will be marveled upon in the following decades.

    Championship Probability Added: 10.0%

    Stay tuned for the final installment on the series, which ranks the top-five players of the 2020 season, coming soon!


  • The Top 25 NBA Players of 2020 – A Remastered List (Part 1 #16-25)

    The Top 25 NBA Players of 2020 – A Remastered List (Part 1 #16-25)

    I’ve had more discussions on how to properly evaluate basketball players more times than I can count. More often than not, I’ve been met with disagreement in those conversations. After a very recent one that argued the very principles and measurements that govern and quantify certain skills, I was inspired to “remaster” my player rankings list from 2020. The recent acquisition of some proprietary data from BBall Index was the perfect opportunity to use new and refreshing information to increase the accuracy of my evaluations, and I’d like to share the results here.

    Criteria

    It’s very easy to skip a “criteria” section in a player ranking and go directly to the list, but such segments are the perfect indicators for why certain players appear in the spots they occupy. Therefore, if I receive any comments along the lines of: “Why is [insert player name] ranked so low? He averaged this many points, rebounds, and assists with this field-goal percentage, and his team record was this!” I will probably not respond. After all, this is not a list of which players have the sexiest box scores or which players’ teams were the best. The former merely quantifies tendencies and the latter is unrelated to individual performance as a whole, so they aren’t devices I’m particularly comfortable using.

    I’ve repeated my evaluation process in almost every post that pertains to the subject, and this one will be no exception. I follow a simple train of logic that, while not necessarily being an axiom of the process, is the “most likely” truth I’ve come across: 1) basketball is a team sport, and players are chosen to help improve the success of the team, 2) over the course of a whole season (the length of a “seasonal” evaluation), the ultimate team goal is to win the Finals, 3) therefore, the best players increase the likelihood of a championship the most. That chain of thought is often confused with prioritizing players whose teams performed the best or were the closest to winning a title in a given year. This is not the case. Players are seen as independent from their teams in these evaluations.

    Namely, “situational” value is not the target of this ranking due to significant levels of confoundment for certain players (i.e. certain team constructions can dilute the “true” value of a player). Rather, these evaluations consider how a player would affect all types of teams, ranging from the worst to the best ever and everything in between. To measure the championship likelihood a player provides, I estimate a player’s per-game impact alongside average teammates in a theoretically “average” system (metrics like Adjusted Plus/Minus capture the “most likely” value of this). However, this “true” APM value changes as a player enters a new environment. As the team quality falls below an SRS of 0, the player becomes more important (thus, his “true” APM rises) and, inversely, as the team’s SRS exceeds 0, the player becomes less and less important. The deceleration of the latter is measured through “portability,” which uses five scaling curves to estimate the degree to which these diminishing returns occur.

    To recap:

    • I translate all my thoughts on a player to a numerical scale that estimates a player’s “true” Adjusted Plus/Minus, or per-game impact alongside average teammates and against average opponents.
    • Portability ratings then measure the changes in “true” APM (which I call “Plus/Minus Rating,” or “PMR”) to estimate how a player impacts the more extreme team qualities.
    • The team SRS with versus without the player and how it translates to championship equity is determined using a function, based on historical data, that estimates title odds.
    • The weighted (for how likely a player would be on a given team) average of championship odds with and without a player is his Championship Probability Added (“CPA”) value.

    Note: The distribution of team SRS is based on the last fifty seasons of team data / Portability is more of a spectrum than anything else, so if two or more players have the same CPA value, I opt for which one is more scalable, even if the two happen to be assigned to the same scaling curve.

    With the criteria portion out of the way, let’s get into the juicier content: the rankings themselves. Today, I’ll kick off the series with the #16 to #25 players, which will be followed with a separate post for the #6 to #15 players and will conclude with the top-five. Let’s dive in!

    The “just missed the cut” bunch, or players within half of a percent of making the list, includes but is not limited to De’Aaron Fox (2.1%) and Donovan Mitchell (2.1%).

    25. Bradley Beal, Wizards (SG)

    Although most saw his season highlighted by an outstanding 30.5 points per game, Beal’s real talent was his increasing scalability. The impact he provided off the ball, in screen action on the perimeter, and improved passing efficiency were the true upgrades to his offensive skill set. He lagged behind on this list due to a troubled defensive game, but its offensive counterpart mitigated any extreme effects.

    Championship Probability Added: 2.5%

    24. Pascal Siakam, Raptors (PF)

    “Spicy P” was edging into a lot of people’s top-ten rankings approaching the end of the season due to leading the number-two seed in the East in scoring. However, similar to Beal, the traits Siakam exhibited that I valued more were his “portable” ones: extremely versatile defense (he guarded each one of the five positions during at least 13.9% of his possessions) and stronger movement off the ball. I attribute the changes in his postseason box score to an extreme matchup more than most.

    Championship Probability Added: 2.7%

    23. Kyle Lowry, Raptors (PG)

    Lowry has always been a great option for Toronto on the perimeter, whether it be on the offensive or defensive side of the ball. He paired extremely strong playmaking and offensive screen action with active and attentive perimeter defense that captured the scrappy nature of his play. Lowry has yet to break through on either side of the ball to vault him into strong All-NBA candidacy, but the aggregate effects of his two-way play earn him a well-deserved ranking.

    Championship Probability Added: 2.7%

    22. Devin Booker, Suns (SG)

    Devin Booker may be the most undervalued offensive engine to be drafted in the past six seasons. He’s developing into a master of nearly every offensive skill: scoring, shooting, passing, creation, off-ball movement, and even some post play. His 2020 campaign a more promising signal of his future than most will recognize. If his defense were only more effective, he would enter All-NBA territory right now. For now, he’s a strong All-Star level player.

    Championship Probability Added: 2.7%

    21. Bam Adebayo, Heat (PF)

    He may not have the spicy scoring average or captivating outside shooting to woo fans like a lot of the on-ball engines on this list, Adebayo more than makes up for it with his strong secondary traits and game-changing defense. He was the Robin to Jimmy Butler’s Batman in Miami’s surprisingly good offensive scheme last season, and his finishing and rim rolling capabilities were perfect complementary skills to Butler’s playmaking.

    Championship Probability Added: 2.9%

    20. Kemba Walker, Celtics (PG)

    After a strong offensive season in Charlotte, Walker made the unexpected transition to secondary star behind Jayson Tatum, but my best guess is that he was still the best offensive player on the team: more refined scoring, passing, and he provided a much-needed boost to convert Boston from an up-and-coming band to one of the league’s highest-performing offenses. Walker was not quite a top-ten offensive player in my eyes, but a diverse portfolio of defensive matchups and mild effectiveness earns him a top-twenty nod for me.

    Championship Probability Added: 3.3%

    19. Jrue Holiday, Pelicans (SG)

    Holiday may seem to have been dwarfed under the rookie sensation that was Zion Williamson or the All-Star appearance of Brandon Ingram, but he was the clear driver of the New Orleans squad. He led the team in Box Creation and was a close second in offensive load to Ingram. The more impressive note on Holiday’s game to me is his sneaky good isolationism; he was in the 90th percentile in effective field-goal percentage on such possessions, which paired with exceptional passing and playmaking, enabled Holiday to act as one of the exclusive offensive engines in the NBA.

    Championship Probability Added: 3.3%

    18. Chris Paul, Thunder (PG)

    Previously seen to be approaching the dusk of a luxurious NBA career, Paul sparked some life in his aging game by regaining status as a premier passer and playmaker and some of the most effective outside shooting in the league. His lack of efficacy off the ball and declining defense lead me to believe he was best suited as a number-one option, but this likely means none of his offenses would have ever eclipsed into greatness. Perhaps his stint with James Harden contests that, but I view Paul as a fairly neutral defender with strong offensive quarterbacking abilities.

    Championship Probability Added: 3.6%

    17. Jayson Tatum, Celtics (PF)

    It wasn’t uncommon to see critics view Tatum as on the verge of a breakout season, and he finally materialized the possibility in 2020. A refined selection of shots that placed less emphasis on long twos was a crucial addition to his game; and, although his efficiency was less than league-average last year, an exceptional outside shooting portfolio, a strong one-on-one skill set, and developing finishing abilities signals promise. Tatum’s extreme versatility and perimeter engagement on the defensive end led to an All-NBA level season.

    Championship Probability Added: 4.0%

    16. Khris Middleton, SF (MIL)

    Giannis Antetokounmpo’s partner in crime blossomed into one of the league’s most effective secondary options in 2020. He exhibited one of the best outside shooting campaigns of the year and, alongside his developing passing game and strong gravity, evolved into one of the very best offensive players in the sport. His defense was also a large positive. Middleton wasn’t the most active defender in the world, but he was among the most disruptive in the league and prohibited shots at the rim as well as any wing in the league.

    Championship Probability Added: 4.3%

    Stay tuned for the next two additions to the series, which will be released in the next few days!


  • 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.