Thinking Basketball

by Ben Taylor

Are top scorers really the most valuable players? Are games decided in the final few minutes? Does the team with the best player usually win? Thinking Basketball challenges a number of common beliefs about the game by taking a deep dive into the patterns and history of the NBA. Explore how certain myths arose while using our own cognition as a window into the game's popular narratives. New basketball concepts are introduced, such as power plays, portability and why the best player shouldn't always shoot. Discover how the box score can be misleading, why "closers" are overrated and how the outcome of a game fundamentally alters our memory. Behavioral economics, traffic paradoxes and other metaphors highlight this thought-provoking insight into the NBA and our own thinking. A must-read for any basketball fan -- you'll never view the sport, and maybe the world, the same again.

Genres: Sports, Basketball, Nonfiction, Psychology

180 pages, Paperback

First published June 29, 2016

Reviews

[Rahim Hashim · Rating 2 out of 5]

The topic of the book—looking beyond the standard box scores to understand what statistics best capture NBA players, games, and seasons—is quite interesting, but the book itself is limited in using only very basic modeling techniques to do so. Though Ben hints at certain biases that drive our imprecise heuristics while viewing the sport, he could have gone a step further in describing the implications. One clear example can be seen in Chapter 3 — Limitations of Power, where he looks at the importance of a single player in driving team success through various lenses, but fails to tie it back to things that matter to the sport, such as salary cap considerations, GOAT debates, etc.

Many of the chapters seem to be devoted to the idea that journalism fails to accurately capture the nuances of games (in particular, see: Chapter 5 — Winning Bias), which...isn’t a novel or particularly insightful concept. We know that sports reporters create heroes and villains and sensationalize to increase interest.

Charles Barkley is wrong — analytical approaches are critical in order to accurately and in an unbiased manner digest and interpret large amounts of data, as a single NBA game or season generates (not to mention 73+ other seasons that have been completed). However, this is a classic case of Blog Boys going too far, in not acknowledging that many aspects of the game are irreducible to univariate statistical descriptors, especially if they are based on static (i.e. non-dynamic) measures.

*Note: this is not a KD burner account.

[Jerold Yu]

While I agree with most of what the book argues, I wouldn’t say that it has drastically changed the way I evaluate the game of basketball. This book would be more suited to the casual fan who doesn’t take as much time to analyze basketball. Personally, I would have liked more mathematically rigorous arguments to wrap my head around some of the concepts. For example, I would have liked to see mathematical relationships between a team’s portability and it’s winning percentage or championship odds.

[Austin · Rating 5 out of 5]

Great content - a must read for any basketball(or any other sports fan) who wishes to participate in serious player/team debates ;). A logical dive into human biases that affect perceptions of teams/players and the case to question our own heuristics until we can affirm beliefs with data.

[Jake Frederick · Rating 4 out of 5]

Just as much a psychology book as it is a basketball essay. Having known Ben Taylor through his breakdowns on YouTube, I’m impressed how equally deft he is at explaining basketball and it’s concepts through video format and now (for me at least) literature. His measured analysis is the antidote to the brash and provoking “hot take kings” who fill up the early morning sport shows. It feels that in the social media era, every game is presented as a referendum for each player - we always have an opinion ready to fire off as soon as possible. For sports media, the more absolute and damning the criticism; the more eyeballs and engagement they can generate.

Thinking Basketball removes the arrogant and frankly toxic masculinity out of the conversation. Taylor makes room for nuance and understands the game as a process of multiple intricate pieces. Star players cannot thrive without the right role players or coaches, and all of them are at the mercy of variance. When basketball is presented in such a humble and deeply thought out way, it takes away its embarrassing reputation and makes it a joy to share.

Only not 5 stars because the analysis and breakdowns would be better served if it was accompanied with plays in real time to illustrate these ideas even clearer. Of course, Ben realized this too, and has been delivering the absolute best Basketball analysis on the internet. Do yourself a favor and check out Thinking Basketball on YouTube if you have any interest in basketball or peek editing and storytelling.

[Killer of Dreams · Rating 2 out of 5]

This book was extremely helpful in teaching me about statistics based on possessions and redirecting individualistic basketball and focusing on basketball being a team sport (the latter blew my mind and has allowed me to view pick-up basketball games differently). This content is four star rated but unfortunately doesn't take up more than two chapters.

Most chapters were decent though some I did not agree with their view of statistics being absolute. At times, Taylor’s focus on statistics alone misses context and that to side only to statistics is just as bad to bind only to heuristics. A good example was LeBron James in the 2014 NBA Finals who scored efficiently and a large amount of his points in "garbage time". This is reminiscent of Bill Russell staving off Wilt Chamberlain from scoring until the Celtics had an insurmountable lead before allowing Chamberlain to score and go after his records, which inflated Chamberlain' numbers.

Also, the citations of psychological studies is irritating. Modern psychology is too absolute and used sweepingly.

Weighing my appreciation for what I learned, my hate for certain rhetoric, and absolute reliance on statistics allows the book to earn two stars.


Notes

Introduction: I am disappointed out how this book is directed at correcting faulty cognitive logic. I had hoped Taylor would focus on deep basketball analytics and career ranking of players.

Chapter One: Decent chapter on global offense.

Chapter Two: The comparisons of basketball statistics to baseball statistics is confusing since I don't know too much about baseball. It's slightly irritating.

In how Taylor criticized Dantley by citing WOWY statistics, I feel that they are not helpful since it could be argued that there are extraneous factors like different lineups that Dantley's teammates faced without him.

Chapter Three: Despite the use of different statistics that I was unable to understand. These statistics also seem to use small sample sizes and appear volatile. I was still blown away by the conclusion of the chapter and how even great players are limited by the team dynamic of basketball.

Chapter Four: The mentioning of variance and averages has reminded me of my ill-attempts to understands statistics.

“Is a 93 percent foul shooter still not a 93 percent foul shooter just because he misses occasionally?” This is where I disagree with Taylor. Narratives can be created such as clutchness. Nick Anderson should not have missed four free throws but he did. He was bad in that instant, when it mattered most. Only mainstream narrators at fault for making sweeping, career-length claims.

I'm blown away by the explanation of muscle motion being susceptible to error.

Chapter Five: "In the aftermath of the 2011 NBA Finals, few fans remember Dallas Maverick star Dirk Nowitzki's subpar shooting series". I'm surprised I never fell into this category, since I was always saddened by Nowitzki's performance.

I am coming to find Taylor stuck in the moment, especially since he is hinting at defending LeBron James after the 2011 NBA Finals. This is convenient since he also ranked James above Jordan.

First he bashes Nowitzki, then he bashes Jordan, now he's praising Wade as the best player in the 2011 Finals. Taylor seems more to me like a LeBron supporter in the contemporary debates. It's not that he's wrong, more that he's critiquing Jordan and Nowitzki but no complaints for Wade, who missed a buzzer-beating three pointer for game 2, and LeBron, who played sub-par through the whole series, especially worst in the fourth. Even Taylor makes a quip, unnecessary passing remark of stating that Nowitzki was one of the few players who had his shot blocked, coincidentally by LeBron. No need to stick that in there unless you want to continue the subversion of discrediting the Mavericks and ignoring Miami's loss.

Taylor has been nit picky with criticizing narratives. Miami's offense sucked because they blew a lead and could not win in the end. That's what matters.

Chapter Six: Taylor is too much of a statistician: "Counterintuitively, the outcome of a game is no more decided by a play in the last seconds than in the opening seconds". Just because it's even in theory does not mean reality follows in suit. Taylor then twists the support for last quarter points by saying all points add up. He is sneaky and changes arguments and places them in unrealistic analogies. Of course all points are important but winning is the most important thing and the last shot equally matters.

Also, I have a hard time believing that Taylor debunks clutch performers and the use of a closer, motioning for the use of the previously used offense from the past three quarters will be more efficient. If this were the case, I do not understand why most NBA teams, as he states, utilize a closer instead.

Chapter Seven: I believe Taylor discrediting the ring argument does not consider that framing greatness can come in different ways, and some view a 3-6 record in the finals worse than a 6-0 record. I find it wrong that on his site, Taylor found Jordan to have the highest peak seasons of any player, but ranks Abdul-Jabber and James above Jordan because both had consistent careers and longer durations of lower peaks. Like in Bill Simmon's analogy (The analogy comes from his book, The Book of Basketball), Taylor favors the ten good years that David Robinson preformed rather than Bill Walton's two great years. Simmon's, a ring proponent, valued Walton.

Chapter Ten: His hate for Jordan has become obsessive:

“Jordan scored at an amazing rate of 36.7 points per 36 minutes, but his efficiency was a subpar 1.02 points per scoring attempt. In other words, Jordan was a clogged highway, producing marginally effective scoring for his team in lieu of other paths the Bulls could have explored”. To assume that Jordan carrying the Bulls scoring on subpar shooting efficiency means that Jordan clogged the offense and could've allowed his teammates to get more involved seems like a narrative, the very thing that Taylor criticizes. Instead, I see that the Bulls had to go through the Jordan route because Pippen's scoring and efficiency dropped, Longley's points per game dropped from 11 points per game in the regular season to 5 in the finals (with near same efficiency), and Ron Harper and Steve Kerr had slumps. Taylor acknowledges Pippen's back injury and almost backs away from his previous reasoning in a note: "Still, high-volume, low-efficiency games hurt most teams".

Status missing for February 5, 2020. I reached 77%.

[Kellen Short · Rating 3 out of 5]

This book was fine, a little disappointing. I am a big fan of Ben Taylor’s videos, and this book clearly lays the foundation that those videos build upon. However, it was not as engaging. There was a little too much cognitive science for my liking. It veered a little too far into a snarky, contrarian perspective rather than sticking to the strength of its own arguments. Decent overall.

[Ben Beard · Rating 2 out of 5]

I'm always down for a book that challenges conventional thinking. The thing is, sometimes it's conventional thinking for a reason, and you're not some galaxy-brained genius for going against it, you're just ... wrong. This book makes a lot of counterintuitive arguments, and I found myself disagreeing with almost all of them. "Offensive distributors like Steve Nash contribute more to winning than isolation scorers like Kobe." Disagree. "Possessions in the fourth quarter are no more important than possessions in the third." Disagree. "When comparing players' legacies, rings don't matter. At all." Disagree.

The problem is not that I disagree; hey, I could be wrong, ask my wife, it's happened before. The problem is the lack of support for these positions. In a book that is ostensibly all about ferretting out logical fallacy traps and using data to reach objective conclusions, there sure are a lot of conclusions being drawn that aren't supported by data. And sometimes there was plenty of interesting data, but the author doesn't use it to make a compelling case.

For instance, if high level distributers like Nash are inherently more valuable than isolation scorers like Kobe, then why were Nash's Suns never able to even get to the finals, while the Kobe centric Lakers won two titles? Both teams were surprisingly similar from a talent standpoint (hall of fame power forwards with swiss-army knife, do-it-all small forwards, surrounded by veteran, competent role players). The author may have a really good argument here, it's just ... he doesn't bother to make it.

Sometimes the conventional thinking is conventional for a reason. Perhaps, in a game that is all about the final score, having a guy who can score more than anyone else is actually really valuable, even if it means taking up more "lanes" than his less skilled teammates? If the refs, the players, the coaches, and the fans all consider fourth quarter possessions to be more important, maybe it's because ... they are? In a sport that can be influenced more by an individual than probably any other team sport, maybe how many championships you win should matter a bit when comparing players?

I would have loved to be challenged on my thinking on any of these points, but that would require a book full of compelling arguments with strong data to support them. Thinking Basketball is not that book.

[JC · Rating 2 out of 5]

I don’t think I learned anything new from reading this book. As much as the author speaks on biases, he has quite a few strong ones himself, namely an over-reliance on simple “advanced” statistics to explain a chaotic game. He also clearly has a favorite type of player — Iverson is a ball-hog who doesn’t “scale” on a good team, while Steve Nash is a god. He presents these sorts of things as facts, when in reality it’s more like he’s trying to explain the mysteries of the universe with Newtonian physics.

That said, there is some useful information here for a casual fan that wants to build a foundation for thinking about the game more deeply.

[Adam Schrecengost · Rating 3 out of 5]

More behavioral economics than basketball theory, Thinking Basketball is a solid introduction into how to properly analyze a team sport that is often driven by single player narratives.

[Aaron · Rating 4 out of 5]

I found this book after enjoying the author’s YouTube videos on basketball analytics. The strongest parts of the book are when Taylor discusses newer statistical ideas, such as why points per attempt is a more informative measure than raw points scored. He also makes a compelling argument that you don’t simply replace a player’s scoring in a lineup when they leave, but rather redistribute it among the remaining players. He connects this idea to an interesting traffic paradox, which is one of the more memorable analogies in the book.

Much of the second half focuses on mental biases that basketball fans tend to have, drawing heavily on ideas similar to those popularized by Kahneman. Taylor takes frequent shots at Bill Simmons in discussing biases like championship bias and clutch bias. These sections are the weakest part of the book, largely because Taylor tends to overcorrect. For example, he argues that the first shot of the game is just as important as the last shot because they are worth the same number of points. While this is meant to counter late-game bias, it misses the importance of leverage and game context. Shots are not interchangeable when score, time, and pressure matter. He also seems to ignore the dependence structure of a basketball game: an early missed shot affects everything that follows and is not independent of future possessions.

Overall, the book is at its best when explaining newer analytics and showing how teams can be greater than the sum of their parts. It is weakest when it tries too hard to correct for fan biases. It’s one of the better basketball analytics books out there, but it isn’t fantastic. I’d recommend the author’s YouTube videos over this book.

[Abuzar Bhatty · Rating 5 out of 5]

I wish Akhil would read this

[Dallin Kohler · Rating 4 out of 5]

Basically a book about cognitive biases in the context of basketball. Short book, good read.
Funny to think this came out in 2016 before Ben was all YouTube famous.

[Josh Url · Rating 5 out of 5]

I really enjoyed this book! It covers some of the common cognitive and basketball evaluation/perceptual biases well. It utilizes good analogies, examples, and new terms to further illustrate the Author Ben Taylor's points that typically run counter to traditional basketball wisdom. It covers a lot of basketball philosophies I have discussed in depth with friends and my students over the past several years in a very engaging and clear manner. I definitely recommend this book to any basketball fan and/or anyone trying to get into the industry!

[Ross Wilcox · Rating 5 out of 5]

Think you know how to evaluate player performance? Guess again!

[MIKE Watkins Jr. · Rating 5 out of 5]

One of the best books i've ever read that challenges the way that the typical fan assess basketball.

Various misconceptions from "the guy with the most PPG is the best player", "the best team always wins", and "isolation basketball is good for teams" are dissected and broken apart in this book.


This misconceptions stem from our brains reliance on best-guessing strategies known as heuristics that govern how we analyze the world at large and how we look at sports. "We make a decision that is good enough, but not necessarily optimal and then effectively tell ourselves it is completely optimal." He breaks down the process itself and how we as fans can notice it and combat it.


But yeah this is a very well researched and put together book...that really exposes the faulty way that most people analyze this sport.

For example, people tend to just look at the 2003 spurs team....notice their are no all stars on it....and proceed to assume that Duncan carried trash cans to the NBA finals.

Why? Because the brain categories things as a sort of short cut way to reach a conclusion. Any "role player" is the same....a role player...same value....same attributes...same contributions.

However, that's not the case...."not all role players are created equal" and that was clearly displayed on the spurs. In fact, Duncan led his team in scoring only 50% of the time in the NBA playoffs.


But yeah I don't wan to spoil much from this book...because you don't get the whole experience unless you yourself engage in the process of having each inherit biased perspective you relied on to assess basketball torn down.

[Ata Kalender · Rating 4 out of 5]

A thought-provoking, yet easy read, Ben Taylor's thinking basketball has its roots in the biases & heuristics research of Kahneman and Co. The writer goes into detail on several topics, including whether individual scoring or game-winning shots are as important as we deem them to be, whether the traditional statlines are actually reflective of what a player contributes to a team, or the extent to which a player may effect a game of basketball. The findings will not be shocking for followers of Taylor's fantastic YouTube channel or other contemporary basketball writers like Zach Lowe, but they may surprise casual watchers or even some seasoned fans. Taylor finds what our limited brains do with basketball is similar to what it does in other vague situations: the brain simplifies what it sees, uses bias & heuristics to determine who is good and who isn't, and disregards methodical ways of thinking, ignoring sample sizes or other data that should have been relevant. Taylor does a pretty good job of conveying our insufficiencies in thinking and evaluating basketball as a complex matter beyond emotional impressions, which I believe could provide an unexpected intro to the bias & heuristics area for an otherwise unaware reader. All in all, a good book.

[Glory Okoli · Rating 5 out of 5]

I came across Taylor’s YouTube channel long before I read this book, so the book didn’t contain any life-changing information for me since I’ve heard most of his arguments. Ben Taylor’s blend of statistics, neuroscience, and basketball strategy makes for a thrilling and unique read. His descriptions of technical concepts using every day terms is genius, and I think that’s where this book shines.

One thing I wish Taylor wrote about in more detail is his perspective on how basketball coverage *should* be done. In some ways this book comes off as some uppity intellectual diagnosing problems without offering solutions. His main thesis is that popular media members cover basketball in simplistic and inaccurate ways through short-sighted narratives. But one could counter by saying that overreacting to small samples is part of what makes sports discourse fun. I know Taylor would have good rebuttals to this perspective because his YouTube channel is hugely popular, and he doesn’t dumb down his analysis to catchy cliches or broad generalizations. But it would’ve been nice to hear the way he approaches his media presence in more detail. Elite book tho. Highly recommend

[Hizonfire · Rating 2 out of 5]

Maybe I read this too late as the book was written in 2016, just when analytics are just starting to get widespread across the league. As far as I can determine, the book is meant for the fan to view the game past cognitive biases and through data. Much of the data and concepts presented seem to validate common sense (a well-rounded player is better than a high-scoring iso-ball scorer) while some seem to exist in a vacuum or in a world full of numbers like the statistically best teams sometimes don’t win championships (of course, injuries and adjustments happen) and the value of clutch shots which seemingly contradicts the Sample Size dictum presented a chapter before, plus there are a lot of disclaimers and caveats in the concepts presented, which undermines the point.

While it’s a great attempt to turn a casual fan into a smarter, data-driven spectator, the writing is a bit dry and confusing with a lot of esoteric examples vs illustrating the point using actual game situations (there are but not enough). Perhaps the author has improved since writing the book as I enjoy his Youtube videos which are clear, accessible and grounded.

[Geoff · Rating 4 out of 5]

I picked up this book as I have an interest in Basketball from an Analytics perspective and felt this might be a good read to gather more information on how to view Basketball team stats. It did do that, but I must admit that a lot of the material was not new to me however it did give some ideas to think about with respect to what areas of a team's play may determine strengths and weaknesses.

If you are just looking for an overview of Basketball analysis with some good ideas on how to view player and team value this is a good book. If you are searching for a more in depth look at analysis you might want to check out Basketball on Paper by Dean Oliver.

I give the book 4 stars because I do find there is value in this book, particularly for someone just getting into Basketball Analytics. I also found it well written and put together with excellent examples so that puts it just above 4 stars.

[Connor Cummings · Rating 4 out of 5]

Great book about the numbers of basketball (the real ones within the most telling metrics, that help paint a more detailed picture). SPOILER ALERT: Main principle is that basketball stats focus too much on volume, but not enough on efficiency. I am now going to spend my time looking into points per attempt in a multitude of scenarios. I loved how he used a combination of statistical and psychological concepts to elaborate on the points being made.

I recommend this book to anyone who loves basketball, Moneyball, but especially those who are fans of a struggling NBA franchise. It gives hope and will help add reason and mathematical rational when you rage tweet at the team’s page during a loss.

[Pranav · Rating 3 out of 5]

This is probably a book for total newbies to basketball tactics and strategy. I mean the first chapter literally starts with explaining what a Power play is. Maybe i had the wrong expectations in mind but i was expecting something a lot more. Also i happened to disagree with a lot of things said in the book about individual vs team accomplishments. I disagree largely with the argument presented that you can't compare players off of their team achievements because great players often times make mediocre teams great. Of course a lot more goes into it but the best example of this is the Bucks championship in 2021.

[Rharm · Rating 3 out of 5]

I love the work of Ben Taylor, and I'm probably not the target audience for this book as someone who enjoys the very technical side of analytics. After reading Oliver's book, I would've loved to have seen more mathematical concepts discussed for some of Ben's analytical tools like "Box Creation" or "Global Impact" that he mentions in his YouTube video's, that being said, this book would get a way higher rating if I was new to Basketball or analytics in general, as the content is of course incredibly interesting and telling, especially the winning and late-game biases. I'd love to see a successor with updated notions and more calculations!

[Stefan · Rating 3 out of 5]

It has Basketball, it has analytics so what's not to love about this book. While Ben Taylor does make a lot of valid points and teaches the reader that there is more to the game than stars and highlight plays he also gets a bit lost in mathematics at times by under- or overvalueing the interchangeability of plays.
All in all a good read, maybe not the best for people who already see the game as he does but for basketball fans who want to know more about the analytics side of the game (or analysts who want to learn more about basketball).

[Jolo Lat · Rating 4 out of 5]

As a fan who isn't a casual but hasn't fully tried to understand advanced statistics, this was a great bridge to that. I understand that scoring isn't everything and there are other aspects of the game. Watching his videos on the "Greatest Peaks" made me want to read this cause his analysis for INDIVIDUAL Versus team is great for debates and appreciation of the history of the game.

I'm a Kobe fan and an appreciative Lebron and Jordan fan. This makes me appreciate players like Garnett and Duncan even more without the "Championship" fallacy and "clutch fallacy"

[Jonathan Johnson · Rating 5 out of 5]

Very good book

I love this book
The author takes out all of the hero bias that we have towards basketball players and breaks down the numbers that matter and how well our favorite players have performed according to these numbers
Overall, being an efficient scorer isn’t important
Clutch shooting is not important
The most important is having multiple teammates who can attractive extra defenders which free up open teammates
I would recommend this to any basketball historian

[Nathan Walker · Rating 4 out of 5]

Ben is a wonderfully bright basketball thinker. Few other analysts see the game in as complete a picture as he does! I loved the vast majority of the book and found its analyses convincing. Read this if you want to learn more how to better think about the game!

The "winning bias" chapter alone is well worth the cover price.

One star being docked for the chapters which I did not find quite as convincing, in particular the clutch chapter.

[Jorge Soto · Rating 4 out of 5]

No es el libro que esperaba, pero aprendí mucho gracias a él.

Cuando compré este libro, estaba buscando uno que enseñara las "Xs & Os" del Basketball. En su lugar, este libro está enfocado en cómo los Bias (sesgos) juegan con nosotros cuando tratamos de decidir ¿quién es el mejor jugador? o ¿cuál es el mejor equipo?.

Gracias a este libro, ahora analizo las noticias y jugadas desde otro punto de vista. Espero que de una forma más realista.

[Helfren · Rating 3 out of 5]

There;s a lot of numbers about the playoff turnover etc. However, the part that catches my attention a lot was, why the so called clutch scorers are more admired than the mid-game last second score? In fact the game is shaped from the early game and then gradually gets better when the end comes. The new way of thinking statistics to basketball is very mind-changing for me.

[Frankhudson · Rating 3 out of 5]

3.5 stars. It’s a great introduction to a more thinking way of looking at the game, as the title suggests. However, there’s not a lot of actual basketball in here, so it’s hard to integrate the thinking with specific concepts. Recommended for people without any background in analytics or are used to ‘old school’ arguments for debating not just basketball but sports in general.

[Achilleas · Rating 3 out of 5]

Very pleasant read. Having read a couple of books on cognitive biases and the subconscious, I found many underlying information trivial. Nevertheless, this is a book well written, with plenty of useful analyses. Given the tradition in sports literature, this should - understandably - be a revelation to many.