Category: NBA

  • 2023 All-Star Power Rankings | Volume I

    2023 All-Star Power Rankings | Volume I

    Monthly data from the NBA begets the fruitless (and slightly masochistic) tradition of ranking players. This post won’t rank players in the typical sense—in, say, an ordered list. Rather, I’m continuing a series I’ve done each of the past two seasons in which I update my All-Star ballot continuously throughout the season. (Read introductory editions for 2021 and 2022 for list structure.) Now, with 13-16 games under the healthy stars’ belts, I’m slightly comfortable indulging myself in this kind of thing. Leave your criticisms in the comments!

    Tier 1

    Regardless of positional constraints, these players are performing at All-Star levels. (The lower bound of their estimated value matches or exceeds All-Star “level.”) To argue otherwise may earn you the label of a basketball heretic.

    • Giannis Antetokounmpo (East)
    • Devin Booker (West)
    • Jimmy Butler (East)
    • Stephen Curry (West)
    • Anthony Davis (West)
    • Luka Doncic (West)
    • Kevin Durant (East)
    • Joel Embiid (East)
    • De’Aaron Fox (West)
    • Paul George (West)
    • Shai Gilgeous-Alexander (West)
    • Tyrese Haliburton (East)
    • James Harden (East)
    • LeBron James (West)
    • Nikola Jokic (West)
    • Damian Lillard (West)
    • Donovan Mitchell (East)
    • Ja Morant (West)
    • Pascal Siakam (East)
    • Jayson Tatum (East)
    • Karl-Anthony Towns (West)
    • Myles Turner (East)
    Tier 2

    These players have a larger margin of error associated with their status as All-Star performers. I’d consider these guys to be strong candidates. Whether or not they make the ballot is, in large part, determined by the NBA’s talent distribution at the top and positional constraints.

    • Bam Adebayo (East)
    • Jarrett Allen (East)
    • Jaylen Brown (East)
    • DeMar DeRozan (East)
    • Darius Garland (East)
    • Rudy Gobert (West)
    • Draymond Green (West)
    • Jrue Holiday (East)
    • Brandon Ingram (West)
    • Kyrie Irving (East)
    • Brook Lopez (East)
    • Chris Paul (West)
    • Domantas Sabonis (West)
    • Zion Williamson (West)
    • Trae Young (East)
    The Ballot

    You know the rules: 5 starters (2 frontcourt, 3 backcourt); 5 reserves (2 frontcourt, 3 backcourt); and 2 wild cards (position negligible). Rosters for both the Eastern and Western Conference.

    Eastern Conference
    • James Harden
    • Donovan Mitchell
    • Giannis Antetokounmpo
    • Kevin Durant
    • Joel Embiid


    • Darius Garland
    • Tyrese Haliburton
    • Jimmy Butler
    • Pascal Siakam
    • Jayson Tatum


    • Kyrie Irving
    • Myles Turner
    Western Conference
    • Stephen Curry
    • Luka Doncic
    • Anthony Davis
    • Nikola Jokic
    • Karl-Anthony Towns


    • Shai Gilgeous-Alexander
    • Ja Morant
    • Paul George
    • LeBron James
    • Domantas Sabonis


    • Devin Booker
    • De’Aaron Fox

    The NBA’s talent distribution makes it increasingly harder to choose All-Stars in its current roster format. Before, I’ve done up to 4 tiers of players to be considered for All-Star, in which the gaps among tiers were fairly recognizable. But this year, I somehow managed to fill 37 spots in 2 tiers. (Hence, I omit the last 2 tiers.) Stat “inflation” is one thing to consider in which the values of counting statistics like points and assists are lower than in seasons past. But there’s also a clear distinction between current and previous talent distributions. Thus, it may be worth revising the definition of an All-Star. (For example, expanding the number of roster spots to 15.)

    This season has legitimately been a fever dream. The Kings and Pacers have 2 All-Stars each (according to me). Brook Lopez and Myles Turner are officially on my agenda. Shai Gilgeous-Alexander might be the box-score MVP if not for an impromptu Stephen Curry mega-explosion. (Curry is currently my MVP frontrunner.) At the end of the day, I’m glad doing this didn’t worsen my tension headache. Please leave criticisms below! I don’t watch every game or look at every stat.

  • 2022 NBA Preview | Win Predictions & Power Rankings

    2022 NBA Preview | Win Predictions & Power Rankings

    (Picture via NBA)

    I typically don’t do things like this (because I think they’re pointless), but this season is as good as any for the masochistic practice of predictions! Yes, these will, in part, be your typical run-of-the-mill record predictions, but I’ll also throw in some power rankings to spice it up. Let me start by differentiating between those two things: 1) The win predictions are, shockingly, the number of games I estimate a team to win in 2023. By no means are they accurate or reliable, but they serve as ballparking values for more-or-less how I’m feeling about a team right now. 2) The power rankings, or the actual order in which teams are ranked, are based on the likelihood that I think each team will win the title. These are what I’d consider my actual “ranking” of each team. That means I may project a higher win total in the regular season for a team whose championship odds are superseded by another. With that wrapped up, let’s get into the nitty-gritty!

    (NB: I don’t end up predicting wins. Fairly self-explanatory.)

    “Just wait and see, five years from now…”

    30. Utah Jazz


    29. Houston Rockets

    Jalen Green could drop 20 a game. Looking out for him to blossom into a real offensive threat in the near future.

    28. Oklahoma City Thunder

    27. San Antonio Spurs

    Sometimes I forget they exist.

    26. Indiana Pacers

    25. Detroit Pistons

    Minefield of young talent. Not nearly fleshed out enough to make a push for anything, but I am eager to explore the synergies between their rookies and sophomores.

    24. Sacramento Kings

    Mike Brown as HC will make them an interesting watch. Preseason has shown us some gritty, switch-heavy defense, although the Kings have been treating the preseason like it’s the NBA Finals. They have an interesting assortment of players who are worth the view.

    23. Orlando Magic


    22. Washington Wizards

    I am oddly intrigued by this team. Not because I think they’ll be good, but because Beal-Porzingis will be an interesting offensive combo spread over time. Would tune into several of their games for Deni Avdija alone.

    21. Charlotte Hornets

    20. New York Knicks

    19. Chicago Bulls

    18. Portland Trail Blazers


    17. Atlanta Hawks

    16. New Orleans Pelicans

    Looking like they could ascend to “good” in the near future if the indicators show up. Throwing Zion into Ingram-McCollum offenses could be dangerous (for the opponents). But they did lose Tony Snell. Probably near the top of my watchlist. Basically tied with next team.

    15. Los Angeles Lakers

    Darwin Ham might be a basketball genius. Anthony Davis’s health is obviously key if they want to come close to contending. LeBron will probably still receive soft MVP consideration. Austin Reaves will manhandle your favorite backcourt. But the Westbrook signals don’t look great so far, especially on defense. If that domino doesn’t fall, I don’t see a spectacular ceiling for this team.


    14. Memphis Grizzlies

    13. Toronto Raptors

    Canadians are too defensive of their basketball team for me to risk ranking them any lower. But seriously, the Raptors are looking like they’ll be a good team. They’re young and complement each other well enough, so some upside is feasible. Not quite past that play-in level. Not quite average.

    12. Minnesota Timberwolves

    I don’t know.

    11. Cleveland Cavaliers

    10. Brooklyn Nets

    By now, I’m just playing Russian Roulette trying to get this right.


    9. Dallas Mavericks

    8. Denver Nuggets

    Lots of offense! Lots of offense! Jokic-MPJ-Murray lineups, in the spirit of throwing out predictions, will produce the highest offensive ratings in history this season. That’s it. Keep Murray healthy. Don’t let Michael Porter Jr. handle the basketball. Jokic. Defensive questions.

    7. Miami Heat

    6. Phoenix Suns

    No, I don’t think this team fell off a cliff. Well-coached, Devin Booker is a legitimate primary offender (get it?) at this point, so Chris Paul’s aging curve at least has a failsafe. Losing JaVale McGee is only a minor tragedy. Not sure if this is going to be a team that runs away with another top seed, though.


    5. Philadelphia 76ers

    De’Anthony Melton and P.J. Tucker are sneaky good pieces. Harden and Embiid shared minutes will produce some of the highest offensive ratings in the league, and they’re looking like a contender for one of the league’s best defenses too. Montrezl Harrell? I really don’t know.

    4. LA Clippers

    Literally flipped a coin to choose between them and Philly. No, I’m not kidding! I know that sounds like a joke, but it’s not.

    3. Boston Celtics

    This team got better on paper, but… Until they demonstrate in the regular season that the off-court predicaments are going to bleed into the on-court stuff to a “significant” level, I’m riding with the talent. Malcolm Brogdon is such a savvy addition to this roster, brings the pick-and-roll chops their offense would have thrived with last year. Timelord’s knee and the other stuff likely will cost them several games in the regular season, so let’s hope for them that home-court advantage falls their way (even if it’s not crucial).

    2. Milwaukee Bucks

    The Bucks added Joe Ingles! Let us fall to our knees and rejoice in this miracle! But seriously, that was quite the player to bring in during an offseason in which they lost no rotational pieces. Milwaukee underperformed in the regular season last year and lost a cutthroat semis that was decided by Grant Williams’s hot hand. This team is legitimately great and there should be no surprises if they capture their second title in three seasons next June.

    1. Golden State Warriors

    I’m liking Golden State to repeat for the championship this year. (Not particularly worried about the Draymond situation yet.) Donte DiVincenzo looks to be a prototypical Warrior, passing to cutters with solid perimeter defense off the bench. But Gary Payton II will be sorely missed at the point-of-attack. That dude was legitimately a monster and his contributions will never be fully appreciated. JaMychal Green also has some passing chops apparently, is a nice movement shooter you can stick in the corner and pull defenses. James Wiseman is not a finished product, but he’s big (even if his handle is vulnerable), incredible lateral quickness for his size, with a wide dunk radius that adds some versatility to the Warriors’ passing targets with lob finishing. Poole continues to grow, Curry (no explanation needed), and Draymond doesn’t fall off a cliff, and this team is a sure contender.

    Time to roast me in the comments!

  • My Tentative Process of Ranking NBA Players

    Ranking players, especially in the widespread arbitrary sense by which most instances occur, essentially has no practical value. But that’s because “player ranking” is often treated as a self-contained thing that looks inward of the result, disregards the implications value-systems have on the processes of team-building and assigning market values. Therefore, while the “result” (a list) of player ranking doesn’t matter for any reason which concerns the on-court product of a basketball game, it serves as an infamous source of entertainment value. Player ranking allows people on the internet to gain or lose their self-esteem vicariously through the quality of their basketball opinions, and thus the human instinct makes the performances all the more memorable.

    The “Non-Ideal” Theory of Player Ranking

    Basketball does not occur in a vacuum, nor should it as the product of systems within systems. However, the systems of the game impose more boundaries; if the ideal benchmark of a player’s value is his “intersystemic” efficacy, that is what he provides across a variety of systems, there is little room for an intelligible process. Thus, ranking players in this fashion involves to some degree the need to play god, to transpose instances upon others with limited bites of data. Namely, our ideas concern the “non-ideal” axioms we may invoke to provide rigidity in the process, to avoid incoherence. Perhaps there is meaning in working with such limited measuring sticks, encouraging collaboration and the expansion of our worldviews. So, in this post, let us set up a version of a player ranking process that emphasizes a player’s intersystemic value.

    The actions of players (parts), in conjunction with decision-making from non-player members of an NBA franchise, positively affect the team (system) by contributing toward the underlying mechanism that wins basketball games: scoring as many points as possible on offense and saving as many points as possible on defense within the time/space constraints of a typical game. The intrinsic difficulty in untangling the process of possessions stems from the degree to which actions are intertwined and indistinguishable among parts, meaning to continue with the task requires an observable number of finite dimensions in which decisions and the ensuing actions occur. From such emerges the models of possessions and practical applications of playbooks, which exist as sets of premeditated actions that describe patterns in players’ actions and their interactions with other players. (Major signs of caution are advised to remain aware of whether or not we censor certain information.)

    To estimate the manners in which players contribute to the process of possessions by proxy of his impact on a finite number of models of possessions, we employ a bottom-up approach that evaluates the consistency and efficacy of a player’s actions (in most cases, “skills”) based on varieties of qualitative and quantitative data and data points. Those initial “player profiles” which are intrinsically bound by their intrasystemic natures are then transposed onto intersystemic principles that similarly evaluate changes in consistency and efficacy, which is achieved through generalized pattern recognition of 1) how players of similar profiles tend to change through systems and 2) how varieties of teammates typically change based on their tendencies. The “end result,” the data point estimation which sorts the rankings, is a proxy for a player’s intersystemic value by estimation of how he fuels the successes and failures of possible systems.

    Knowledge Through Impartiality

    Film study is the most important part of our process, the fundamental “visual” tool which is falsely contrasted with analytics or statistics, the “numerical” tools. The visual aspect takes precedence because of the degree to which it constrains our interpretations of its data; statistics are represented on a far more rigid surface than are observations from tape, which can extend past the crude data point to qualitative analysis. We can observe the minutiae of what constitutes, for example, a play type on  A “post up” is a generalization, a short-hand with which inferences can be made quicker, but not necessarily more effectively. This is why the process requires diligence, a hyperactive form of analysis that trades off between pitfalls and follows the route which will (hopefully) lead us to the “best” possible decision.

    Pushing back against generalization is a broader theme in film study. When we search for something, the other things are filtered out in what we may ascribe to noise. But the censoring of information is not necessarily the most desirable course. Remember, we’re looking to emulate the bottom-up approach of how parts interact within systems, so to flow with the process organically will broaden our worldview of what considers contributions and what doesn’t. The resulting observations about interactions and synergies, which are selected to cover wide areas of possible circumstances, are condensed into “tendencies” by which players impact systems.

    Statistics aren’t omitted from the process and exemplify a trade-off between bias and variance (analogous to forms of regression modeling) shared with film. Statistics are shorthands that account for a player’s entire time on the court during a given season, Playoffs, career, et cetera, but the tools are biased toward the measurements that are decided upon. Meanwhile, film has the potential for the reduction of bias based on the viewer, but the length of seasons and typical thresholds that decrease the variance of observations would presumably require an inhuman amount of time and energy to overcome. Not all statistics are “good,” as has been proven many times. How many points a player scores per 75 possessions or his relative True Shooting percentage likely isn’t that “important” in this process, especially as self-contained objects. For this process, the most “important” statistics are “tracking” (non-traditional, non-box counting) stats and lineup stats, for their abilities to shed light on tendencies which may be less prone to variation among systems and synergies among parts (WOWY, assist networks).

    While on the topic of analytics, there surely must be some mention of “impact” (composite, one-number) metrics! Without them, we’d have virtually no idea the degree to which a player can impact the game outside of an arbitrary, dissonant mental estimate. Though it is important to continually be mindful of their weak spots and how certain modeling techniques may capture one player’s intrasystemic value fairly well, but not another. These are ideally the concluding steps in the process, a crude benchmark that offers strong, rigid methods with which we can connect the actions a player performs with the underlying “impact” on the successes and failures of the systems. 

    The Interpretation of Player Rankings

    By “ranking” players and devising lists, the purpose is not to create a perfect representation of reality or estimate within some strict interval the degree to which the process produces plausible results. Player rankings are not intended to be a reflection of how one interprets the process of possessions (the higher-dimensional, purely intersystemic basketball), but rather the entertainment-based alternate process by which one can estimate such a reality with a finite number of parameters, all of which are prone to human error, misinterpretation, and reduction. Ranking players is a social experiment, so let us treat it as such!

  • The Consequences of “Knowing” Individual Scoring

    “All things appear and disappear because of the concurrence of causes and conditions. Nothing ever exists entirely alone; everything is in relation to everything else.”

    Basketball is not the study of individuals, but rather the study of the interactions among parts which form wholes. The conditions of the sport make it so, repressing individuality, providing one-dimensional views of the ways in which parts adapt to and interact in systems. This leaves us, as evaluators of basketball, in a constant state of Epoché whose curtains deflect approximations of intersystemic truth, guided by logic and pattern recognition. But those mimicries of knowledge emphasize the ultimate pitfalls of intersystemic thinking: perceiving data for one thing and allowing the underlying motivations to narrow the descriptive power, the resulting knowledge.

    Possessions as a Process

    Scoring is perennially misrepresented as an individual skill, a sound heuristic on which to form judgments and construct an individual by his abilities. But this, of course, assumes that the priorities of the evaluator are in line with understanding the processes by which systems produce results, by which systems succeed or fail. To entertain the attribution of scoring to “putting the ball in the basket” in such a context would be a blasphemous reduction of the self-imposed heuristic. The process produces the results, but the latter does not describe the former, merely functions as a false indicator by other self-imposed heuristics.

    Points ascribed to individuals are the pyrite in the muddy solution to the complex question, one which has already been reduced to fit into the narrowing worldview that seeks knowledge. They encourage the interpretation of the result as the whole fruit rather than its outermost layer which conceals the seeds which had been planted to instigate the process. Measures have been derived from points as data points for players to attempt context, yet still ignore the underlying functions of the process, namely, a “shot quality” metric. Such presentation may encourage the idea of scoring as a measure of points relative to expectation, which remains a result-oriented approach.

    Yet, scoring remains a process which spins webs between individuals that conceal intersystemic phenomena in the guise of individuals making shots. The concepts of individual scoring, of shot quality, and of additional context attributed to the moment of a shot, serve as psychological safety nets against the masses of tangible and intangibles processes at work during possessions, processes within processes. To understand the extent to which data accumulates, let us tentatively outline a fundamental, ecological process of offensive possessions.

    The Pick-and-Roll

    Perhaps the most widespread tactical approach in basketball’s collective knowledge: the pick-and-roll, and any variation on which the “roller” (if not multiple) will typically relocate to a higher space on the court. Such plays are instinctually recognized as processes, either premeditated or an impromptu one whose execution is predetermined. A common goal of basketball offenses is to convert on the “best” shot possible, the one which will maximize their output in the limited space and time which they receive. They are shots that exist as possibilities and ranges; they are conditional and require recognition of what can be instead of merely what is, and sometimes are never found.

    Shots are not free, bound by the limited space and time of possessions but also by the alternatives by which the team might have scored. All shots have costs. (This is why the notion that “efficiency” does not matter is often disregarded.) Sometimes that cost, that next-best alternative, is more than the actual result (team fails to convert on “best” shot possible) and sometimes is it less (team succeeds to convert on “best” shot possible). The pick-and-roll illustrates how this phenomenon relates to the process of scoring, the manners in which teams seek the “best” shot possible and how the process influences the ability to seek, the trade-offs involved in a multi-dimensional scoring process.

    Let us conceptually omit the variance in remaining teammates and opponents, coaching staffs, and any parts which influence the happenings on the court during an offensive possession. During the pick-and-roll, there exist a Ball-Handler and a Roller, the former designated with the initiation of optimizing the “goal” (to find the “best” shot possible) with the ball in his hands while the latter encourages this by setting a screen. The two-man interaction between the Ball-Handler the Roller can be viewed as cyclical, an interdependent process by which both parts attempt to optimize the goal by improving each other’s shot quality.

    A “traditional” pick-and-roll would ideally result in a field-goal attempt at the rim for the Roller, as such shots (on average) garner the highest expected point-values and taller, sturdier bigs who set screens are less prone to physical resistance in the key. A manner in which the Handler can improve the Roller’s shot quality is by preoccupying defenders, as more space to operate will increase the shot quality of the Roller because he has less physical resistance against his shot. To act out such a thing, the Handler must communicate to the defense a reason for which he must receive an “extra” amount of attention, to open space for the Roller or instigate a chain-reaction of help defense which could improve shot quality for teammates. (Although we solely focus on the Roller in this instance.)

    To receive that extra attention is to possess a threat by which the Handler could score with the ball to a degree that exceeds the concerns of his teammates. Thus, the Handler must possess what is colloquially known as a “scoring threat” to improve the Roller’s shot quality in the manner expressed earlier. To do so he must previously score through ways which threaten the defense (processes within processes) and predispose the defense to cautionary measures in following possessions. If the Handler is successful in this regard, he may successfully contribute to the shot quality improvement at the moment of the Roller’s attempt and contribute to the process of scoring.

    So why don’t teams employ this two-man game in every possession if they will consistently maximize the difference between their shot quality and the opportunity cost? Because observed repetition refines cautionary measures, and the play is designed to exploit cautionary measures. A team’s shot quality would trend downward because the interaction between the Handler and Roller changed significantly; the further removed a defense is from observing the Handler’s scoring threat, the less likely they are to instigate the cautionary measure which allows for the play in the first place. Therefore, the Handler must recognize the trade-off, revert to earlier habits of attack to keep opponents on their toes and create a possession of possibilities, thereby allowing the process to continue.

    Simultaneously, the Roller may continue to garner defensive attention due to the shift toward his scoring threat. The defense would expect him to shoot more frequently and more efficiently, and thus alter their cautionary measures to account for more of his shooting attempts. The result would draw a discrete amount of attention away from the Handler, thus allowing for more opportunities for the Handler to score frequently and more efficiently, the precedence by which the Handler can then influence the Roller’s ability to score frequently and more efficiently. Thus, the process is cyclical, one which evaluates trade-offs and alters the roles of the parts within the system to interdependently optimize its goals.

    The Quasi-Existence of Individual Scoring

    Points and efficiency, although functional as crude data points of the results of a player’s shots, shed minimal light on the processes by which teams score under the principles of intersystemic thinking. Because the processes often involve trade-offs, the selections of attacks which repress individual talent and independent decision-making, the concept of individual scoring is intertwined in an elegant, endless system from which the concept cannot be unraveled. So why do we so often prescribe such incomplete data to the questions that arise?

    People’s predisposition to default to digestible, if-incomplete measuring tools breeds the ground for selectivity, taps into our insatiable need to quantify and rank our self-imposed classifications that narrow our worldviews and set the stage for unknowing, the consequence to the tactics of pattern recognition and the reconfirmation of our heuristics. Scoring as the main principle of basketball understands this, exists as a thing born out of many but is often reduced to the one, and urges us to reconsider the manners in which we observe and judge.

  • The Ultimate PER Guide | Untangling John Hollinger’s Analytics Lovechild

    The Ultimate PER Guide | Untangling John Hollinger’s Analytics Lovechild

    (Image via Bleacher Report)

    Player Efficiency Rating (PER) was the turning point for basketball analytics in the public domain; but with time comes controversy. Lots will claim that PER is an outdated metric, that recent efforts of all-in-one metrics have left PER useless. Let’s say this is true, and for good reason. PER has a limited scope compared to lots of modern metrics, which incorporated Plus/Minus and tracking data that seems to map a player’s value to an objectively greater degree than the box score. Let us be reminded that this is a good thing! More advancements means more descriptive power among these all-in-one metrics, so the science of player analysis has undergone significant evolution since Hollinger’s initial effort. So, as a brief summation, PER is NOT one of the absolute best measures of player impact for the modern era. But like any other subject with a rich history, there is value in going back to appreciate tradition. Let us explore the inner workings of PER. What makes it good or bad, and why should or shouldn’t you use it?

    How PER Works

    PER puts the “E” in “Efficiency” because it was designed as a fairer comparison between high-volume superstars and role players. Like lots of modern impact metrics, PER is a per-possession metric that estimates a player’s effect on his team’s point differential [1]. But instead of using advanced, complex mathematical modeling to accomplish its results, PER is grounded in concept and critical thinking. It works so that each box score statistic (points, assists, etc.) is assigned a weighting, which is personalized to its box score stat such that each weighting reflects the statistic’s point-value. If that sounds a bit confusing, hopefully this example makes things clearer:

    LeBron James committed 196 turnovers [2] during the 2022 regular season. Most basketball fans will agree that turnovers are bad! A turnover means the offensive team lost possession of the ball without having scored. Thus, they lost out on the opportunity to score points in that possession; and basketball is often a game that is won in a matter of possessions. Plus, there’s also the drawback from permitting the opposition a transition possession, which tends to yield more points than typical half-court offense. So we can all agree turnovers are bad, right? But how do we know how bad one is? Well, we have to consider what a turnover is taking away from, and the big thing is those aforementioned points the team could have scored if the ball weren’t turned over.

    Since a variety of outcomes could’ve followed barring one of James’s turnovers, Hollinger decided to use a single placeholder number to sum up all possible outcomes of a possession. This estimates just how many points the Lakers were missing out on because of the turnover. Let’s think about it this way: on average, NBA offenses scored 1.12 points per possession in the 2022 regular season [3]. Hollinger concludes this was the best estimate of how much an offense is missing out on from turning the ball over, not accounting for how the opponent can gain a transition possession, as stated earlier. But since the turnover is deducting that amount of value, a turnover in 2022 is worth approximately -1.12 points! If we apply that weighting to all of LeBron James’s 196 turnovers this year, we can estimate that he cost the Lakers almost 220 points from his turnovers.

    This process is done for all box score statistics (most of which have far more complicated weightings), and the results are summed up to estimate how many points a player is adding (or subtracting) to his team. However, as stated earlier, there is one last adjustment that converts the results to a per-possession basis. Namely, superstars don’t receive any benefits for playing more of the game. This “adjusted” form of PER is what you’ll see on Basketball-Reference or ESPN leaderboards. With that out of the way, let’s discuss the good and the bad of PER, and what its process means for the metric’s ability to evaluate players.

    The Good and the Bad

    Believe it or not, there is some good stuff about PER. Take this as more of an opinion than a fact, but PER has solid (and interesting) critique behind it. The idea that each statistics has a hypothetical point-value behind it is logic that is used to this day, even with the most revered metrics like Estimated Plus/Minus and BBall-Index’s LEBRON; and PER was the first to do it. Let’s also consider the benefit to translating the results to per-possession rather than per-game or across an entire season. PER can be a reasonable tool for identifying hidden gems slotted at the end of the bench, and can act as an indicator of whether a role player is outperforming one of the better players on the team. Back when PER was the gold standard, there was some value it could provide to teams looking to manage their roster and shuffle their lineups. Not at all a bad result!

    However, there are a considerable number of drawbacks to discuss with PER; and unfortunately, these dominate the conversation and are often valid concerns of the metric. Let’s return to the per-possession basis of PER. While there may be benefits, there are also flaws with this approach. There is the matter of fatigue in which players with a heavier load tend to tire out near the end of games, whereas role players can spend more of their time on the court with a fresh set of legs. Superstars also tend to player with better teammates, meaning they have fewer chances to exert their skill; and they often play tougher opponents, whereas role players tend to match up with the opponent’s bench units as well. That is, not all statistics are created equally, and a player’s impact can be reframed and reimaged depending on who else is on the court, which is something PER struggles to account for.

    The other glaring issue with PER is that it lacks a benchmark, or some type of measurement to fall back on to confirm the metric is grounded in reliability. If you’re familiar with other popular impact metrics, you may remember that they are often backed by RAPM, which is arguably the strongest all-in-one metric basketball has to offer. If not, I have written in-depth about RAPM before [4] if you’re interested in learning more about it. (TW: Math.) PER has been around for nearly twenty years, so it’s no surprise that it has been one-upped by more recent metrics, but the larger issue is that John Hollinger has refused to update the metric. PER has been more or less the same since 2005, which excludes the metric from the comprehensive analytical techniques of today. This, paired with the inconclusive nature of the metric’s logic, makes PER one of the less viable options to analyze players.

    Should You Use It?

    The biggest argument against using PER is that there are many better alternatives, which is true. Estimated Plus/Minus, LEBRON, RAPTOR, and BPM, among others, all have more solid bases in accomplishing their goals. We’ve discussed the positives and the negatives of the metric, and are hopefully all able to recognize that both exist. But, again, PER is simply outdated. Hollinger’s refusal to refine his metric has left it in the dust. You’re much better off using the Backpicks (proprietary) or Basketball-Reference models of BPM if you’re looking to view a player’s impact from the perspective of the box score. But does this mean PER is bad?

    I wouldn’t say so. PER has a very intriguing basis, and the logic Hollinger incorporated into the metric shows a considerable understanding of how basketball is played and won. Therefore, PER is still going to be quite a hit-or-miss metric, as lots of them are. But it’s not “bad” to the point that it measures every player off the mark. Heck, there’s the off-chance that PER pins a player down just right! However, it’s not great either, especially considering its peers. So the next time someone tells you PER is the worst thing to grace the Earth, tell them it could be worse. If it helps, tell them to look into Wins Produced from the Wages of Wins Journal. But that’s all from me, folks. I hope this was a somewhat insightful look into PER, and that you’re next perusing of a leaderboard is that much more confident.





  • My Top-10 NBA MVP Candidates (2/27/22)

    My Top-10 NBA MVP Candidates (2/27/22)

    (📸 The Ringer)

    The conflict between performing and storytelling on the basketball court has clouded the MVP race for decades; and like other highly-divisive topics in sports, both sides are represented by two camps:


    Traditionally, the MVP has a very loose criterion that hinges on the voter’s ability to tell a story with their vote. For example, take 2011 Derrick Rose’s MVP. He was clearly not the best regular-season player that year, but the Chicago Bulls sneaked up behind the newly-formed Heatles and snagged the first seed in the East. Sure, the Bulls were successful because of their defense and not their offense, but Rose’s floor-raising efforts and acrobatic, engaging playstyle drew fans to the screens and promoted the league’s popularity. Was Derrick Rose the “Most Valuable Player” in 2011? No; but nominating him as the MVP was good for the NBA.

    Perhaps more recently, there are those who strictly adhere to how “good” a player is when selecting their MVP ballot. This is a basketball-only approach that looks to recognize players based on their ability to affect a team’s chances of winnings: win-loss record, seeding, home-court advantage, all of that. There’s an obvious appeal here: it’s less biased than narrative-based voting when done right; it provides a sturdier baseline to evaluate candidates (not everyone cares who the best player on the best team is when using storylines); and it forces us to look closer at what’s happening on the court and overcome the deficiencies in our thought-processes.

    I flesh out these two approaches to not advocate for one or the other, but to establish my priorities as I assemble this list. Typically, my content has been based around the second approach: trying to use observations and material evidence to support arguments for one player or another. While such an approach is fully appropriate for, say, a player rankings list, I’m not sure the same applies to the MVP Award. Perhaps the “Most Valuable Player” isn’t necessarily providing the most value toward winning, but toward the welfare of the Association. With this in mind, I’ll still reference a player’s actual skill and heavily weigh it in my final ranking, but another priority is how a player has been drawing fan interest and promoting league viewership to provide a more holistic view of who has been the NBA’s Most Valuable Player in 2022.


    10. Kevin Durant

    The Slim Reaper has missed some time with injury troubles, but has still been playing around MVP levels when he’s on the court. Durant has assembled a masterful offensive skill set throughout his career, pairing his length in driving lanes with all-time shooting ability, which are exactly the types of characteristics you’d wish to see in a player who moves the needle for championship offenses. 

    9. Luka Doncic

    The greatest basketball prodigy since LeBron James started off the season in a bit of a slump, but picked himself up in recent weeks, re-evolving into the dangerous offensive centerpiece we’ve seen him be for the third consecutive season. Doncic can hit defenses quickly with unexpected attacks and passes out of traps extremely well. He’s a similar build to James in that he can quarterback an elite offense surrounded by shooters who leverages his drive-and-kick game to their advantage. Dallas has also made a surprise entrance as a top-five team in the West by SRS. [1]

    8. Chris Paul

    The Phoenix Suns have been the best team in basketball so far, and it would be narratively unjust to go without recognizing one of their players. Among the league leaders in my hand-tracking of shot creation, Paul is a masterful pick-and-roll ball-handler, splitting defenses at will and punishing drop with his lethal mid-range shooting. He drives Phoenix’s offense and manages to play at All-NBA levels while fighting against Father Time’s inescapable aging curve. CP3 is a talent for the ages.

    7. Ja Morant

    My favorite player to watch in 2022 and the sport’s next great athletic freak. Morant has been the figurehead of an exciting Memphis Grizzlies squad while being one of the more improved players in the league, playing around All-NBA basketball this year. At his best, Morant creates easy offense like the game’s very best. His incredibly dynamic scoring and uncanny passing vision formulates one of the most unique offense skill sets in the sport. Morant will do all this and also steal defensive rebounds from your favorite big man.

    6. DeMar DeRozan

    DeRozan is one of very few players who have proved they can still be one of the game’s very best scorers without three-point shooting. He’s been breaking basketball with his mid-range shooting, making 51% of a mind-shattering 14.5 attempts per 75 possessions! [2] DeRozan’s storyline would arguably make him a finalist if I were more partial to narratives, but there’s too weak of a stance based on performance alone. Playoff concerns aside, this player has been a unit on the basketball court, revitalizing a stunted career and shedding loads of doubt from critics.

    5. LeBron James

    The King is still really good at basketball. He’s been having one of his best regular season in years, punishing defenses with the scoring that vaulted his name into the GOAT conversation many years ago. Also one of the best passers in the sport and an adequate floor-spacer whose timeless athletic prowess makes him a strong defensive player even in his nineteenth season. The regular season could be hinting toward the reemergence of Playoff LeBron in a few month’s time.

    4. Giannis Antetokounmpo

    Ah, the wonders of voter fatigue. The Greek Freak was the third finalist on my ballot from last year, and while he’s done an outstanding job of raising the ceiling for a smaller-market team, the league might do better spicing things up a bit. Regardless, Antetokounmpo is arguably the first or second-best player in basketball right now, making the fourth spot my absolute floor for him.

    3. Stephen Curry

    Probably the face of the NBA. Curry is among the league-leaders in merchandise sales [3] and promotes the best TV ratings [4] in the league. His scoring has taken a massive hit from its glorious past, but his ability to bend and break defenses remains. Curry is loved by impact metrics and is having one of the best defensive and passing seasons of his career. Given he had maintained his early-season hot streak, he would be the top player on this list. But for now, he slides back to third.

    2. Joel Embiid

    Embiid is a masterful scorer who pairs punishing brute force in the paint with grateful skill on the block that garnered (self-anointed) comparisons to the likes of Kobe Bryant and Hakeem Olajuwon. He’s still one of the strongest defenders in the league and an improving playmaker. The fans seem to want to see Embiid as a finalist for a second straight season, and such recognition is warranted.

    1. Nikola Jokic

    The claim for the best player in the league in 2022 seems particularly exclusive this season because of the Joker. We’re talking about a player who has legitimate arguments as both the best scorer and playmaker in the sport right now, blending three-level scoring with an unheralded array of passes that stretch defenses to their absolute limits. Jokic has also been a clear positive on defense this season. By the way, Denver outscoring teams by +9.7 points per 100 with him on the floor and have been 19.2 points worse with him off. [5]






  • NBA All-Star Power Rankings (1/2/22)

    NBA All-Star Power Rankings (1/2/22)


    Ladies and gentlemen, welcome back to another edition of my NBA All-Star Power Rankings series! Here, I’ll detail the current landscape of the league’s best players and condense my thoughts into one All-Star ballot. Players will be arranged into tiers based on their level of play, which is entirely based on the degree of impact the player provides by helping teams gain higher seeding and home-court advantage for the Playoffs. To add a final disclaimer:

    This list is not my “prediction” of the league’s actual All-Star teams lineups. This is a reflection of my evaluations of players, and where that would place them in the NBA’s award hierarchy.


    Within the league’s top-25 or so players is a group that has fully established itself as All-Star-caliber (or better). There’s little to no doubt in my mind that these players should be headed to Cleveland in February.

    • Giannis Antetokounmpo (East)
    • Jimmy Butler (East)
    • DeMar DeRozan (East)
    • Kevin Durant (East)
    • Joel Embiid (East)
    • James Harden (East)
    • Zach LaVine (East)
    • Trae Young (East)
    • Mike Conley (West)
    • Stephen Curry (West)
    • Anthony Davis* (West)
    • Luka Doncic (West)
    • Paul George* (West)
    • Rudy Gobert (West)
    • Draymond Green (West)
    • LeBron James (West)
    • Nikola Jokic (West)
    • Donovan Mitchell (West)
    • Ja Morant (West)
    • Chris Paul (West)
    • Karl-Anthony Towns (West)

    Because these are players whom I firmly believe are All-Stars, I won’t belabor any points. I will address the two asterisks next to Anthony Davis’s and Paul George’s names, which were added due to uncertainty surrounding their injury status come February. Davis and George are both currently out with a sprained MCL and a torn elbow ligament, respectively. Both will be re-evaluated in a few weeks’ time.


    The “Probably” group includes players I currently believe are All-Star-level, but I may not be entirely sold on their status. A lot of these players will make my final ballot, but whether it be injuries, a lack of signals, or general uncertainty about their playstyle, I distinguish them from those I wholeheartedly believe are All-Stars.

    • Bam Adebayo (East)

    A unique mold of player for the modern game, Adebayo is on track to replicate his All-Star success from the last two seasons. He provides a level of spacing as a threat from the mid-range (39% on 8.6 attempts per 75) to tie into a strong overall scoring package, which he pairs with elite defense that has remained on the perennial DPOY watch.

    • Bradley Beal (East)

    Beal’s outside shooting slumped out of the gate, which was an attribute of his that was crucially valuable to an elite off-ball package. Resultantly, I can’t view him as an All-Star lock, but his passing and shot creation have been trending upward, which boosts his value in a floor-raising role, also helping to mask his questionable defensive play.

    • Jrue Holiday (East)

    Holiday is a player that provides a ton of value that the box score doesn’t capture. Adjusted Plus/Minus models have always looked fondly upon his shooting, passing, and tough brand of point-of-attack defense. After a while, it becomes hard to ignore what the analytics are communicating.

    • Khris Middleton (East)

    Minutes played alongside the Greek Freak have depleted Middleton’s scoring punch so far, (Middleton averages 28.5 points per 75 on 59% True Shooting as the lone star.) but his skills have still carried over: spacing, passing, and shot creation. My only setback is how those skills map to his overall impact; the metrics are concerningly low on Middleton thus far.

    • Jayson Tatum (East)

    After a rapid ascension in 2020, Tatum seems to have stagnated slightly. His shooting and scoring have been in decline, and he doesn’t have the playmaking chops like Lillard to make up for some of that value. He’s otherwise adding some on defense. This is one of many “Playoffs will tell” cases.

    • Damian Lillard (West)

    Lillard feels like an obvious choice most other seasons. The only reason I put him here is his early-season shooting slump. He’s quickly picked up where he left off previously, but his struggles have dented his scoring effectiveness and have slightly offset the continued value he brings as an elite playmaker.


    The league’s talent pool is stacked, and as a result I nearly overwhelmed the nominal threshold of an All-Star player being within the sport’s top-25. Since there’s a numerous amount of other players that provide impact in similar vain to these “probable” stars, the “maybe” talents serve as high sub-All-Stars and potential injury replacements.

    • Jarrett Allen (East)
    • LaMelo Ball (East)
    • Darius Garland (East)
    • Fred VanVleet (East)
    • Devin Booker (West)

    Again, perhaps these players could be viewed as legitimate All-Stars. The 2022 season hasn’t fully taken shape yet, which could mean rearrangement among the previous two tiers. I’m on the absolute fence with some of these players (e.g. Booker and Conley), whether it be more lack of indicators or too little room in the actual ballot.

    Note: I’m omitting the “Not Quite There” tier from previous editions of this series due to the influx of information that comes as the season progresses.

    Final Ballot

    Once again, we reach the trickiest part of this exercise. It was difficult enough to sort the closest calls, but the task extends when putting these players into their All-Star slots. Similar to the previous editions, the ballots are structured to include two teams for either conference: five starters with two backcourt and three frontcourt players, five reserves (same restrictions), and two “wild cards” (no positional restrictions).

    Eastern Conference


    • G: James Harden
    • G: Trae Young
    • F: Giannis Antetokounmpo
    • F: Kevin Durant
    • C: Joel Embiid


    • G: DeMar DeRozan
    • G: Zach LaVine
    • F: Jimmy Butler
    • F: Jayson Tatum
    • C: Bam Adebayo

    Wild Cards:

    • W: Jrue Holiday
    • W: Khris Middleton

    The two closest calls here were 1) whether to give the last frontcourt reserves slot to Adebayo or Middleton and 2) whether to give the second wild-card slot to Middleton or Bradley Beal.

    Western Conference


    • G: Stephen Curry
    • G: Luka Doncic
    • F: LeBron James
    • C: Rudy Gobert
    • C: Nikola Jokic


    • G: Damian Lillard
    • G: Donovan Mitchell
    • F: Anthony Davis*
    • F: Paul George*
    • C: Karl-Anthony Towns

    Wild Cards:

    • W: Chris Paul
    • W: Draymond Green

    Given the injuries to Davis and George persist, the roster would be rearranged to bump Draymond Green up to a frontcourt reserve slot, give Mike Conley the vacant wild card slot, and move Kristaps Porzingis into the second frontcourt reserve slot.

    Data from:


  • Introduction to Cryptbeam Plus/Minus (CrPM)

    Introduction to Cryptbeam Plus/Minus (CrPM)

    I talk about NBA impact metrics a lot; and as most familiar with my content know, I’ve even created a few. Now, I’m ready to add another player to the mix: “Cryptbeam Plus/Minus” (CrPM). With the metric’s namesake being the title of this website, CrPM joins a long line of composite metrics that aim to identify the difference-makers of the sport through quantitative analysis. Why? As the creator of Player-Tracking Plus/Minus (PTPM), Andrew Johnson, once said: “Because what the world needs now is another all in one basketball player metric.” [1]


    CrPM draws most of its inspiration from two established impact metrics in Jacob Goldstein’s Player Impact Plus/Minus (PIPM) and Ben Taylor’s Augmented Plus/Minus (AuPM). The commonality of these three metrics is the shared “branch” of metric: I tend to differentiate between impact metrics by one of three types:

    • Box: a composite metric that is calculated using the box score only
    • Hybrid: a composite metric that is calculated using counting statistics outside the box score (e.g. player tracking and on-off data) — but may also include the box score
    • APMs: a composite metric that uses ridge-regressed lineup data as the basis of its calculation

    As for where CrPM falls under these categories, it’s formally a hybrid metric. The metric can be broken into two major component: a box score term and a plus-minus term. The box score “version” of CrPM can function as an impact metric on its own as an estimator of impact via traditionally-recorded counting stats: points, rebounds, assists, etc. Using Regularized Adjusted Plus/Minus (RAPM) as a basis, the box score is regressed onto this target to estimate a player’s per-possession impact on his team’s point differential.

    Two plus-minus statistics are then added to the box-score estimate to create CrPM: on-court Plus/Minus, which is a team’s per-100 point differential (Net Rating) with a player on the floor, and on-off Plus/Minus, which subtracts the team’s Net Rating with a given player off the floor from his on-court rating. The goal of the plus-minus component is to fill in some of the gaps left in the immeasurable, e.g. what the box score can’t capture. Testing of the model did later reinforce this idea.

    Regression Details

    The regressions for both the box score and plus-minus variants of the metric were based on fourteen years of player-seasons from Jeremias Engelmann’s xRAPM model. (This means that, in the RAPM calculation, a player’s score is pushed toward the previous season rather than zero.) This provided a more stable base for the regression to capture a wider variety of player efficacy in shorter RAPM stints. Additionally, the penalization term for each season was homogenized to improve season-to-season interpretability.

    The box score is not manipulated in the CrPM calculation outside of setting the stats as relative to league averages. The raw plus-minus terms, however, use minutes played as a stabilizer to draw results closer towards zero as playing time decreases. While some incorrectly label a larger sample size as more accurate, this adjustment serves to reduce variance in smaller samples to decrease the odds for larger error in these spots. These two branches of NBA statistics combine to create CrPM. [2]

    The regressions, especially the box score ones, were all able to explain the variability in the target RAPM with a surprising degree of accuracy. The R^2 values for combined in and out-of-sample RAPM ranged from 0.725 to 0.750 for the box-score metrics and bumped up to 0.825 with plus-minus included. A large concern for most ordinary linear regressions is heteroskedasticity, which is when error rates become larger as the predicted variable increases. The breadth of performance captured in the RAPM target mitigated this, and CrPM serves as an accurate indicator of impact for average players and MVP players alike.

    • Target response of RAPM was collected from Jeremias Engelmann’s website.
    • Box scores and plus-minus data were collected from Basketball-Reference.

    Current MVP Ladder

    Because CrPM serves as an indicator of a player’s impact, it can do a solid job of identifying viable candidates for the league’s MVP award. Through the 18th of December, here are the top-10 players of the 2022 season with at least 540 minutes played per the metric:

    1. Nikola Jokic (+11.8)

    The reigning MVP has started his follow-up campaign with a bang, and looks to be the frontrunner to snag the award again. His placement in the box-score component of the metric (+12.4 per 100) would be first among all players since 1997 with at least 1,500 minutes played during the season. Jokic’s overall score of +11.8 in CrPM is tied with LeBron James’s legendary 2009 seasons for the best regular season on record.

    2. Giannis Antetokounmpo (+9.4)

    Voter fatigue in recent seasons has downplayed the regular-season greatness of the Greek Freak, but he seems as good as ever according to CrPM. Each of his last three seasons are top-45 seasons since 1997 per the metric, with his dominating MVP run in 2020 ranking fourth (+10.8) among all high-minute players on record.

    3. Joel Embiid (+6.6)

    The metric suggests Embiid provides massive two-way value, with his marks on offense and defense being nearly identical in both the box-score and plus-minus versions of the metric. Despite a shooting slump to start the season that followed an exceptional mid-range campaign for the big man, he still adds a ton of value in Philadelphia. So far, the 76ers outscore opponents by +4.3 per 100 when Embiid is on the floor and are +9.2 points better with him in the lineup.

    4. Rudy Gobert (+6.5)

    It’s not an NBA regular season nowadays without the analytics looking upon Rudy Gobert with perhaps a little too much enthusiasm. Regardless, he’s still a surefire candidate for the DPOY Award and a probable finalist, if not winner. Almost all of his impact comes from the defense end, adding only +0.4 points per 100 in the offensive component of CrPM, with the remaining +6.1 points coming from his all-time-level rim protection and paint anchoring.

    5. Stephen Curry (+5.7)

    Curry’s plus-minus portfolio isn’t as transcendent as it was during his all-time seasons in the mid-2010s, but a revamped Golden State roster that amplifies his strengths boosts those numbers into the upper echelon of NBA superstars once more. The Warriors outscore opponents by +14.1 points per 100 with Curry on the floor and are +12 points better with him on the court. While the box score can’t capture all of the value he brings to the table, Curry still looks like one of the best players in the league according to CrPM.

    6. Kevin Durant (+5.5)

    Curry’s former teammate is another shooting savant who continues to string together legendary offensive seasons with league-best marks in both scoring volume and efficiency. He’s arguably the greatest mid-range shooter in NBA history and makes Brooklyn’s offense great with these shots alone. Speaking of, the Nets look like a surefire title contender with Durant on the floor, when they outscore opponents by +7.3 points per 100 possessions.

    7. Clint Capela (+4.6)

    While I don’t think Clint Capela has been a top-10 player in the league this year, his placement illustrates arguably the biggest sign of caution I’d address when using CrPM. Because the box-score component receives a whole lot of the weight in the plus-minus-included formula, the metric is overly sensitive to defensive rebounds and stocks. Especially in the modern league, when spacing affects statistics like rebounds to a higher degree than ever, Capela is a case of, while being a valuable player nonetheless, a stylistic disadvantage of CrPM.

    8. Jarrett Allen (+4.5)

    I’m similarly not as fond with Allen’s actual ranking among the league’s best, but he’s been sneakily good this season. The Cavaliers have clearly stocked up on Michael’s Secret Stuff for 2022, because they’ve been better than the Nets with Durant when they put Jarrett Allen in the game. Cleveland outscores its opponents by +8.4 points per 100 with Allen in the lineup! One of the sport’s emerging two-way talents receives well-deserved credit in the analytics.

    9. Karl-Anthony Towns (+4.4)

    Towns has played like an all-league star for a while, and now that his longtime home of Minnesota has found its footing in 2022, his value is more evident than ever. CrPM views Towns as a clear value-add on offense and defense, and this is enough to make him look like a candidate for the All-NBA second team this year. He’s one of the On-Off kings so far, posting a +13.1 Net Plus/Minus in a similar vain to other top-player candidates.

    10. Jimmy Butler (+4.4)

    If this list were box-score only, Butler would be several spots higher with his +6.3 score in Box CrPM; however, plus-minus doesn’t look upon him like the other players on this list entering 2022. Miami plays like a surefire postseason team with him on the court, but they actually perform +2.4 points better with him off the floor! While this is very, very likely just noise that accompanies most plus-minus data like this, it doesn’t serve as a very good indicator of his impact, thus compressing his score in plus-minus-included CrPM.

    Full 2022 Leaderboard

    Nikola JokićDEN247837.93.911.8
    Giannis AntetokounmpoMIL268495.53.99.4
    Joel EmbiidPHI196293.33.36.6
    Rudy GobertUTA299200.46.16.5
    Stephen CurryGSW289625.20.55.7
    Kevin DurantBRK2710005.30.25.5
    Clint CapelaATL298640.24.44.6
    Jarrett AllenCLE289131.92.64.5
    Karl-Anthony TownsMIN289633.01.44.4
    Jimmy ButlerMIA186074.20.24.4
    LaMelo BallCHO258283.21.24.4
    DeMar DeRozanCHI248464.9-0.64.3
    Trae YoungATL299906.2-2.04.2
    Montrezl HarrellWAS317993.30.94.2
    Myles TurnerIND30887-
    John CollinsATL299392.41.53.9
    LeBron JamesLAL186673.10.73.8
    Chris PaulPHO289063.60.33.8
    Jusuf NurkićPOR307520.63.23.8
    Dejounte MurraySAS289632.21.63.8
    Donovan MitchellUTA289104.1-0.63.5
    Jonas ValančiūnasNOP319801.52.03.5
    Domantas SabonisIND3110571.91.53.4
    Jrue HolidayMIL258193.00.43.3
    Kristaps PorziņģisDAL216341.41.93.3
    Jaren Jackson Jr.MEM297870.23.13.3
    Jayson TatumBOS3010952.30.93.2
    Andre DrummondPHI29571-
    Fred VanVleetTOR2810602.70.43.1
    Anthony DavisLAL279551.02.23.1
    LaMarcus AldridgeBRK255901.81.33.1
    D’Angelo RussellMIN247812.90.13.0
    Miles BridgesCHO3111351.91.02.9
    James HardenBRK269421.90.92.8
    Richaun HolmesSAC225961.51.32.8
    Al HorfordBOS247110.22.42.6
    Luka DončićDAL217352.30.22.5
    Bobby PortisMIL257110.52.02.5
    Alperen ŞengünHOU29538-
    Jarred VanderbiltMIN28682-
    Daniel GaffordWAS28601-
    Damian LillardPOR248733.9-1.62.3
    Patrick BeverleyMIN215521.30.82.1
    Ja MorantMEM196193.0-0.92.1
    Wendell Carter Jr.ORL308650.21.82.0
    Evan MobleyCLE25840-
    Mike ConleyUTA267273.2-1.21.9
    Deandre AytonPHO206250.51.51.9
    Malcolm BrogdonIND258832.7-0.81.9
    Devin BookerPHO216763.1-1.21.9
    Robert WilliamsBOS23638-
    Derrick RoseNYK266362.2-0.41.8
    Paul GeorgeLAC248610.61.21.8
    Darius GarlandCLE299913.0-1.31.8
    Draymond GreenGSW28849-
    Jakob PoeltlSAS216060.51.11.6
    Nikola VučevićCHI20663-
    De’Anthony MeltonMEM27654-
    Bam AdebayoMIA185920.41.11.5
    Ricky RubioCLE318801.20.31.5
    Brandon IngramNOP248552.3-0.81.5
    Cole AnthonyORL237851.9-0.51.4
    Alex CarusoCHI24685-
    Mo BambaORL27774-
    Monte MorrisDEN298752.4-1.11.3
    Zach LaVineCHI279483.1-1.81.3
    Shai Gilgeous-AlexanderOKC258731.9-0.61.2
    Jalen BrunsonDAL277952.7-1.51.2
    Pascal SiakamTOR175861.10.11.2
    Mitchell RobinsonNYK27653-
    Aaron GordonDEN299451.2-0.21.1
    Devin VassellSAS235590.11.01.1
    Tyus JonesMEM306341.8-0.71.1
    Cedi OsmanCLE255521.3-0.21.1
    Kevon LooneyGSW30564-
    Deni AvdijaWAS31672-
    Christian WoodHOU28888-
    Desmond BaneMEM308631.3-0.31.0
    Anthony EdwardsMIN2810060.50.51.0
    Khris MiddletonMIL216501.00.01.0
    Immanuel QuickleyNYK296331.8-0.90.9
    Andrew WigginsGSW299011.7-0.80.9
    Gary Trent Jr.TOR279330.60.20.8
    Ivica ZubacLAC30742-
    Kyle AndersonMEM26565-
    Alec BurksNYK297740.40.30.6
    Caris LeVertIND236681.3-0.70.6
    Cody MartinCHO297990.10.40.6
    Tyrese HaliburtonSAC289300.10.40.5
    Larry Nance Jr.POR30650-
    Scottie BarnesTOR279730.10.40.5
    Tyrese MaxeyPHI289691.9-1.50.5
    Josh HartNOP247560.10.30.4
    Gordon HaywardCHO3110521.4-1.00.4
    CJ McCollumPOR248481.4-1.10.3
    Mikal BridgesPHO289630.30.00.3
    Tobias HarrisPHI217200.7-0.40.3
    Lonzo BallCHI27958-
    Jordan ClarksonUTA297301.3-1.00.2
    Steven AdamsMEM30754-
    OG AnunobyTOR165880.5-0.30.2
    Marcus SmartBOS29991-
    Kelly Oubre Jr.CHO319031.1-1.00.1
    Lauri MarkkanenCLE226640.3-0.20.1
    Kyle LowryMIA289620.9-0.90.1
    Devonte’ GrahamNOP288761.3-1.20.1
    Will BartonDEN258250.6-0.60.0
    Grayson AllenMIL308750.7-0.70.0
    Derrick WhiteSAS288750.3-0.4-0.1
    T.J. McConnellIND245810.4-0.5-0.1
    Franz WagnerORL319940.3-0.4-0.1
    Jerami GrantDET24797-0.10.0-0.2
    Danny GreenPHI23558-2.01.8-0.2
    Russell WestbrookLAL3010780.2-0.4-0.2
    Mason PlumleeCHO22562-1.61.5-0.2
    Patty MillsBRK309051.6-1.8-0.2
    Luke KennardLAC308700.8-1.1-0.2
    Herb JonesNOP28766-1.71.4-0.3
    Bradley BealWAS2810051.6-1.9-0.3
    Jae CrowderPHO28789-1.51.2-0.3
    Nassir LittlePOR26603-1.61.3-0.3
    Keldon JohnsonSAS278290.1-0.5-0.4
    George HillMIL266860.1-0.5-0.4
    Royce O’NealeUTA27833-1.40.9-0.5
    Bojan BogdanovićUTA298641.8-2.2-0.5
    Jordan PooleGSW288600.8-1.2-0.5
    Reggie JacksonLAC309921.1-1.6-0.5
    Gabe VincentMIA275320.3-0.8-0.5
    Jae’Sean TateHOU30844-0.80.2-0.6
    Cade CunninghamDET23745-1.71.1-0.6
    Lonnie WalkerSAS27611-0.1-0.5-0.6
    Norman PowellPOR268251.0-1.6-0.6
    Terry RozierCHO227080.5-1.1-0.7
    Bogdan BogdanovićATL205640.5-1.2-0.7
    Josh RichardsonBOS225550.1-0.8-0.7
    Shake MiltonPHI256360.0-0.8-0.8
    Carmelo AnthonyLAL30828-0.3-0.5-0.8
    Georges NiangPHI286620.2-1.0-0.8
    Anfernee SimonsPOR266181.3-2.2-0.8
    Harrison BarnesSAC258360.2-1.1-0.9
    De’Aaron FoxSAC299930.5-1.4-0.9
    Matisse ThybullePHI23555-3.62.7-0.9
    Danilo GallinariATL26568-0.1-0.8-0.9
    Isaiah StewartDET26668-2.71.8-0.9
    Cameron JohnsonPHO28682-0.6-0.3-0.9
    Raul NetoWAS30607-0.2-0.8-0.9
    Seth CurryPHI279291.1-2.0-1.0
    Pat ConnaughtonMIL32929-0.4-0.6-1.0
    Dennis SchröderBOS278940.8-1.9-1.0
    Kevin HuerterATL287740.2-1.3-1.0
    Malik MonkLAL28666-0.2-0.8-1.0
    Tyler HerroMIA258220.5-1.5-1.1
    Buddy HieldSAC308570.0-1.1-1.2
    Julius RandleNYK301063-1.30.0-1.2
    Joe InglesUTA297180.2-1.5-1.3
    Spencer DinwiddieWAS267620.2-1.4-1.3
    Grant WilliamsBOS28618-1.0-0.3-1.3
    Tim Hardaway Jr.DAL28878-0.1-1.2-1.3
    Precious AchiuwaTOR22579-2.81.3-1.4
    Terance MannLAC29829-0.5-1.1-1.6
    Josh GiddeyOKC26779-2.20.6-1.6
    Chris DuarteIND29843-1.0-0.6-1.6
    P.J. TuckerMIA30856-1.2-0.5-1.6
    Bruce BrownBRK24539-2.50.9-1.7
    Kyle KuzmaWAS29937-2.30.6-1.7
    Dorian Finney-SmithDAL28899-1.80.0-1.8
    Davion MitchellSAC29744-0.3-1.6-1.9
    Robert CovingtonPOR30822-4.22.2-2.0
    Luguentz DortOKC26841-0.3-1.7-2.0
    Eric GordonHOU257450.0-2.0-2.0
    Furkan KorkmazPHI27600-1.0-1.1-2.1
    Nickeil Alexander-WalkerNOP31877-1.3-0.8-2.1
    Kevin Porter Jr.HOU19574-2.20.1-2.2
    Dwight PowellDAL28536-1.8-0.4-2.2
    Duncan RobinsonMIA30849-1.3-0.9-2.2
    Isaac OkoroCLE23663-1.3-1.0-2.3
    Jeff GreenDEN29732-0.9-1.4-2.3
    Eric BledsoeLAC30787-2.4-0.1-2.5
    Chuma OkekeORL25562-3.51.1-2.5
    Cam ReddishATL25558-1.5-1.0-2.5
    Landry ShametPHO27562-0.6-2.0-2.5
    RJ BarrettNYK25784-1.4-1.2-2.5
    Kentavious Caldwell-PopeWAS31906-2.0-0.5-2.6
    Justin HolidayIND25693-1.2-1.5-2.7
    Darius BazleyOKC28765-4.51.9-2.7
    Frank JacksonDET28620-0.6-2.1-2.7
    Killian HayesDET23602-2.90.1-2.9
    Facundo CampazzoDEN28567-1.9-1.0-2.9
    Jeremiah Robinson-EarlOKC28608-2.90.0-3.0
    Jalen SuggsORL21583-3.1-0.1-3.2
    Saddiq BeyDET28897-2.2-1.1-3.3
    Evan FournierNYK30857-1.6-1.8-3.4
    Jaden McDanielsMIN26646-3.90.5-3.4
    Malik BeasleyMIN29750-1.7-1.8-3.4
    R.J. HamptonORL29536-2.4-1.1-3.5
    Garrett TempleNOP29532-4.20.5-3.6
    Avery BradleyLAL26599-3.1-0.9-4.0
    Gary HarrisORL24651-2.1-2.2-4.3
    Terrence RossORL28715-2.4-2.3-4.8
    Reggie BullockDAL27646-3.1-1.7-4.8
    Jalen GreenHOU18555-3.9-2.6-6.5

    Updated Dec. 18, 2021

    [1] Read Johnson’s article, a primer on PTPM, here.

    [2] Because Basketball-Reference doesn’t report plus-minus for offense and defense as liberally as it does combined plus-minus, the offensive / defensive splits for CrPM are slightly less accurate than its total version.

  • NBA All-Star Power Rankings (11/8/21)

    NBA All-Star Power Rankings (11/8/21)


    As the dust of the early season starts to settle, albeit to a degree that leaves lots to be desired, it’s around the time we begin to think about how the upcoming All-Star teams will take shape. With twelve spots to fill in each conference, the following excerpts will detail my current selections for the teams based on how these players are providing material, observable impact that helps teams win basketball games.

    Similar to my previous All-Star post for last season, players will be sorted into tiers based on my evaluations of their degree of impact, with “better” players being more likely to make the final ballot while some players may be on the fringe, fighting with similarly valuable players for the final spots.


    The tier of “absolutely” consists of players for whom I have minimal doubt are playing at an All-Star level or better. Namely, if they either sustain strongly resemble their current level of play, they will continue to make my succeeding ballots.

    • Giannis Antetokounmpo (East)
    • Jimmy Butler (East)
    • Stephen Curry (West)
    • Luka Doncic (West)
    • Kevin Durant (East)
    • Joel Embiid (East)
    • Paul George (West)
    • Rudy Gobert (West)
    • Nikola Jokic (West)
    • Donovan Mitchell (West)
    • Karl-Anthony Towns (West)
    • Trae Young (East)

    I pegged all of these players as All-Stars or better last year, meaning there are no newcomers so far. Compared to last year’s All-Star post (about a month into the season), this tier is thinned out, which is consistent with staying wary of the early season; the target of this exercise is to recognize tangible value that players provide to basketball teams, and each of these players provides established All-Star value.


    The “probably” tier is interesting. I’ve described many of these players as All-Star level or better in the past before, and will also likely remain All-Star-type players or better in my evaluations at the end of the season. However, there’s something to be missed in their performance so far, whether it’s aging, slumps, or uncertainties about their impact.

    • Bam Adebayo (East)
    • Devin Booker (West)
    • Mike Conley (West)
    • Anthony Davis (West)
    • James Harden (East)
    • LeBron James (West)
    • Zach LaVine (East)
    • Damian Lillard (West)
    • Ja Morant (West)
    • Chris Paul (West)
    • Jayson Tatum (East)

    The sore spot of this tier is clearly LeBron James. After nearly two decades of MVP-level play, we’re very likely partway through the beginning of the end of his reign of terror. Aging isn’t on his side, and thus he’s not pressuring the rim or attacking defenses through his passing in the same manner he would during his annual Playoff ascensions.

    A few of these names are mostly obvious All-Star performers, such as Anthony Davis and Damian Lillard. Whether it be rustiness due to injury or unlucky shooting, there’s that small degree of uncertainty that loosens their cases for the 2022 season. The remainder of the tier consists of either lower-level All-Star players or strong fringe members, such as Zach LaVine and Ja Morant.


    While some of these players are of comparable value to those in the tier above, most of these players are closer to injury replacements than legitimate All-Star contributors.

    • LaMelo Ball (East)
    • Bradley Beal (East)
    • Shai Gilgeous-Alexander (West)
    • Montrezl Harrell (East)
    • Tobias Harris (East)
    • Jrue Holiday (East)
    • Kyle Lowry (East)
    • Khris Middleton (East)
    • Domantas Sabonis (East)

    A name I feel the need to address here is Montrezl Harrell. With the benefit of hindsight that will come in the following months, I heavily doubt he will stay in this tier, but there are intriguing signals. He’s not overly dependent on perimeter creation as a finisher, and he’s had a significant spike in free-throw rate, drawing fouls and providing hyper-efficient scoring. It also doesn’t hurt that the impact metrics absolutely adore him.

    LaMelo Ball is a player I felt quite comfortable placing in this tier. I don’t think his outside shooting is sustainable, but his passing is off the charts and his shot creation has steadily improved from last season. As he continues to add value in the big-two skill sets of scoring and playmaking, he’ll develop into a viable offensive engine who can quarterback strong efforts in the Playoffs.

    “Not quite there”

    As the name suggests, this tier recognizes players that are more of honorable mentions that serious All-Star candidates. Namely, these are the players who I felt the need to consider in the process of creating my ballot; but after further research, decided they were more appropriately pegged closer to sub-All-Star level.

    • Miles Bridges (East)
    • Jaylen Brown (East)
    • John Collins (East)
    • DeMar DeRozan (East)
    • Draymond Green (West)
    • Brandon Ingram (West)
    • Dejounte Murray (West)
    • Julius Randle (East)
    • Russell Westbrook (West)

    Draymond Green is a player I’ve praised in the past for his heroic defensive efforts, snappy decision-making, and crafty transition passing, but I struggle to the see the confirmation that his impact is surely All-Star level. I suspect it’s probable he’s bumped up as the season goes on (even so far, his scoring has been somewhat adequate), but for now I’ll rank him as a very strong sub-All-Star-type player.

    Dejounte Murray was a player I was encouraged to stack up against Ja Morant in recent games, and while I see evidence that his passing and manipulation of the defense has grown, he doesn’t have the scoring punch and resulting threat to generate lots of offense for his teammates. I’ve also grown less fond of his defensive rotations and overarching off-ball defense. Regardless, Murray is a surefire candidate for a sub-All-Star team.

    Final Ballot

    Here’s the tricky part: condensing all of these tiers into the structure of an All-Star ballot. As stated earlier, there will be twelve players in each conference: five starters (two frontcourt and three backcourt players), five reserves (two frontcourt and three backcourt players), and two wildcards.



    • G: James Harden
    • G: Trae Young
    • F: Giannis Antetokounmpo
    • F: Kevin Durant
    • C: Joel Embiid


    • G: LaMelo Ball
    • G: Zach LaVine
    • F: Jimmy Butler
    • F: Jayson Tatum
    • C: Bam Adebayo


    • W: Kyle Lowry
    • W: Khris Middleton

    The hardest cut for me to make was the last guard slot on the reserves, which I gave to LaMelo Ball. The obvious candidates in his place were Bradley Beal and Kyle Lowry, the latter of which I gave a wildcard spot. I don’t think it’s impossible for Bradley Beal to rise on this ballot, but I’m concerned by his continuously declining outside shooting and lack of playmaking prowess next to players like Ball and Lowry.



    • G: Stephen Curry
    • G: Luka Doncic
    • F: Paul George
    • C: Rudy Gobert
    • C: Nikola Jokic


    • G: Damian Lillard
    • G: Donovan Mitchell
    • F: Anthony Davis
    • F: LeBron James
    • C: Karl-Anthony Towns


    • W: Ja Morant
    • W: Chris Paul

    Leaving Devin Booker and Mike Conley off my final ballot was a tough choice to make; the guard position in the West is simply too stacked for enough room to be made available. (And like I said, Booker and Conley are probably All-Star guys.) Aside from this debacle, I was pleased with my selections for the West. Gobert and Jokic as centers in the starting lineup felt slightly awkward, but a player like Gobert has way too much regular-season defensive value to leave off this type of ballot.

  • Top 10 NBA Players of 2021 (#1-3)

    Top 10 NBA Players of 2021 (#1-3)

    During the last post, I continued the top-10 series I introduced two days ago by covering the fourth through sixth rankings. Today, I’ll wrap up the “list” with spots one through three and discuss the skills and tendencies of the absolute very best basketball players in the game today. As a recap, here’s the criteria I laid out in the series’s introductory post:


    Consistent with my previous rankings, players are assessed based on how they impact success at the team level. Thanks to the revolutionary work from various basketball researchers, we have a great idea of not only which skills are most valuable, but also how much of an impact one player can have on a team’s success. I won’t belabor the topic, as I’ve engaged in many different conversations on it before, but this approach is antithetical to other, more common methods, which value skills next to one another based on the ranker’s personal belief system (a heuristic that isn’t guaranteed to be correct). To capture as much truth as possible, the value of different skills is viewed through my closest attempt to an objective lens.

    The next major part of the list concerns not the player, but the team around him. The endgame for every NBA team (as far as on-court performance is involved) is a championship. However, if we evaluated players based only on how he affects his own team’s title odds, a chunk of the league’s most talented players would lose their due representation. Paired with the fact that teammate synergies and coaching can actually cloud the strengths and weaknesses of a player’s value, the “title odds on a random team” criterion was adopted. (Note: The “economic” side of basketball isn’t included in these evaluations, e.g. contracts, salaries, enticement for free agents.)

    Perhaps the largest theme of this ranking, however, is how to react to single-season performances. Similar to the aforementioned factor of team construction around a player, the opponents a player’s team faces also play similar roles in augmenting, for example, box scores. Rudy Gobert received hearty criticisms for his ostensibly poor defensive performance against the Clippers in the second round, but more astute viewers noted the collapse of Utah’s perimeter defensive plan that led to an emphasized stress on Gobert to concede more long jumpers. The Clippers were a textbook “bad matchup” for a player of Gobert’s style, and while there are deeper conversations about drop coverage in the Playoffs, a lot of Gobert’s heavy scrutiny can be identified as an overreaction to results heavily influenced by situation.

    Because league-wide offensive efficacy has been shattering glass ceilings in the past two seasons, paired with the perceived psychological effects of zero fans in the stadium, larger-sample three-point shooting percentages are losing descriptive power. This is an example of where this list accounts for “good” and “bad” luck, and as the ultimate goal is to capture a player’s tangible skill and value, these rankings can be considered both retrodictive and predictive; meaning, there are instances in which the past sheds light on the present, and that reference points still hold value in these types of contexts. So while lucky or streaky box scores can be “appreciated,” that’s not the purpose of this list.

    Lastly, but certainly not least, this list ranks players at their fullest health, meaning players who suffered injuries won’t be penalized.

    The List

    10. James Harden (BKN)

    9. Joel Embiid (PHI)

    8. Luka Doncic (DAL)

    7. Kevin Durant (BKN)

    6. Kawhi Leonard (LAC)

    5. Anthony Davis (LAL)

    4. Nikola Jokic (DEN)

    3. LeBron James (LAL)

    During the preseason, my biggest concern with LeBron James is whether last season’s hiatus allowed for more time to replenish his athleticism, which then couldn’t be replicated in the following seasons. However, it seems James’s ability to pressure the rim largely carried over into 2021. He was in the 84th percentile with 10.5 drives per 75 possessions, 74% of which were unassisted, and these were comparable to his fully healthy stint last year. James’s reputation as one of the greatest basketball minds in history was as present as ever, constantly finding gaps and splitting defenses with his drives and slashing ability. This caused defenses to scramble, inadvertently allowing James to punish them with his other strong suit: passing. Nearly 11% of his drives resulted in a pass-out that led to an assist.

    James’s passing is so effective in the modern game because of his transcendent awareness and court-mapping. During my film study on him, he was consistently tracking the movements of his teammates on the perimeter and ready to instigate a high-leverage shot for an open shooter. Paired with his threat as a driver, which forces defenders down the baseline and unclogs the corner areas, James functions exceptionally well as the ball-dominant force surrounded by elite catch-and-shoot teammates. He was also in the 80th percentile or higher in both isolation volume and efficiency, and his ability to create offense for teammates and himself allows James to remain one of the very best offensive centerpieces in the league today.

    Similar to last year, James looked like a big positive on defense, and that was a large factor in why he ended up ranking higher than the NBA’s MVP Nikola Jokic. He was a versatile off-ball defender, using size to block driving and passing lanes while being able to guard a wide variety of players; he was in the 93rd percentile or higher in time spent guarding both “athletic finishers” and “stationary shooters” per BBall-Index matchup data. The largest reason I viewed his defense as slightly worse than last season was his rim protection, which started to regress closer to average. James wasn’t as present in the paint and deterred fewer shots, but he could still derail offensive sets before they culminated in these attempts, and that’s why I view James as a strong two-way player even at age thirty-six.

    Fun Fact: James was in the 96th percentile in the proportion of his half-court possessions in which he cut to the basket.

    2. Giannis Antetokounmpo (MIL)

    At the time of this writing, the Milwaukee Bucks are leading the Phoenix Suns 3-2 in the Finals, and Giannis Antetokounmpo is one win away from being an NBA champion. This is largely due to his perennially underrated capabilities as an offensive and defensive player, and his minor upgrade as a passer gives him the edge over a few players for me, as most of these decisions were made on very slim margins. Antetokounmpo seemed more comfortable with a wider variety of passes. While last season was characterized mostly by kick-outs and basic dump-offs, he’s now more likely to hit more players in more strenuating situations. He’s more effective as a skip passer and he’s hitting cutters a tad more frequently than before. Now that he’s surrounded by better shooters in Milwaukee, his paint and roll gravity are as valuable as they’ve ever been, and major catalysts to unlocking his passing.

    Antetokounmpo isn’t one of the very best on-ball threats in the league, particularly in the half-court when the paint is walled off, but his specialties as a driver and in transition offense are two feathers in his cap that add to a diverse and effective offensive portfolio. He’s an active lob finisher, which pairs well alongside strong passing, and he scored on a whopping 81% of his attempts at the rim in the regular season, and this number only fell to 78% on 10.7 attempts per 75 in the Playoffs. The major criticism of Antetokounmpo’s offense is that a system can’t be structured around him to win in the Playoffs, and there’s validity to this, which is why I fully endorse his transition to a more active off-ball role. He’s an extremely frequent cutter who sets formidable screens for teammates in a wide range of situations, while also being one of the most dominating roll men in the NBA.

    Arguably the main driver of Antetokounmpo’s mega-impact, however, is his game-changing defense. Milwaukee’s defense has been surprisingly effective in the Playoffs relative to their regular-season results, and Antetokounmpo has been the heaviest lifer. The Bucks’ defensive rating is nearly seven points better per 100 with him on the court, and this is largely because he’s an incredible defensive playmaker. He doesn’t function as a point-of-attack defender like some perimeter stars, but his hybrid role that takes him off the ball to stationary shooters or on the ball to versatile big men means he covers more ground than arguably any defensive star in the league. Antetokounmpo is among the hardest defenders to scheme around in a regular or postseason setting, and as a result, he’s super valuable in deep Playoff runs.

    Fun Fact: Despite troubled three-point shooting (30.3%) on very open shots (100th percentile in closeness to nearest defender), Antetokounmpo self-generates a ton of his shots, as he placed in the 97th percentile in the proportion of these shots that were unassisted.

    1. Stephen Curry (GSW)

    The skills that lead me to believe Steph Curry is the greatest offensive player in NBA history were on full display this season. His three-point percentages slumped out of the gate, eventually settling around 42%, but Curry was by far and beyond the best long-range shooter in the league this year. He graded out in the 100th percentile in BBall-Index‘s composite shooting metric that incorporates shot location, type, and difficulty. Curry’s stepback aids him in generating a ton of these pull-up attempts; and his sharp release ensures the range on his shots remains effective in shorter spurts, meaning looks of the same quality in the Playoffs are much more likely to fall victim to the more pressing environment.

    As arguably the greatest scorer ever, Curry demands more defensive attention than, again, probably any player in NBA history. Highlights of teams deploying three or four-man trapping schemes versus Curry were popular this year, and because Curry played with as few offensive threats as he has in nearly a decade, his “situational” gravity was perhaps as massive as ever. However, without the basketball, Curry still creates a ton of shots for teammates. Golden State surrounded him with defensive-oriented teammates who could design a system relying heavily on pin downs and ball screens to find an open shot for Curry. This “off-ball” creation of sorts that results in his constant shooting threat maneuvering around the court amplifies the shooting of his teammates. All of these superb skills result in Curry being the most scalable offensive star to ever play in the NBA, meaning he can boost the star talent around him and potentially improve his own value.

    Curry’s all-time impact manages to hold despite elite defense because he’s not a liability on that end. I graded him out as neutral this year because it’s hard to argue his presence either strengthens or worsens a team’s defense. The major weakness in Curry’s defensive profile is his man defense; opponents can target him on the perimeter and he’s fairly vulnerable to strong-set screens, meaning ball-handlers will usually punish him. Conversely, Curry is kind of a good team defender. He has solid awareness and can clog driving lanes before opponents will leverage them, and this keeps his defensive value from bleeding into the negatives. While it’s hard to imagine Curry truly amplifies any defensive system, there’s also a hard argument to be made that he takes anything off the table.

    Fun Fact: Curry was expectantly in the 99th percentile in the proportion of his half-court possessions on which he scored off a screen.

    Up Next

    Before the series began, I asked community members from Discuss The Game to share their top-10 lists so I could compare our lists following the conclusion of mine. During the next post, I’ll go over the voting results and discuss trends, theories, and why we differ on rankings.