The Midrange Theory

by Seth Partnow

At its core, the goal of any basketball team is relatively take and make good shots while preventing the opponent from doing the same. But what is a “good” shot? Are all good shots created equally? And how might one identify players who are more or less likely to make and prevent those shots in the first place?

The concept of basketball “analytics,” for lack of a better term, has been lauded, derided, and misunderstood. The incorporation of more data into NBA decision-making has been credited—or blamed—for everything from the death of the traditional center to the proliferation of three-point shooting to the alleged abandonment of the area of the court known as the midrange. What is beyond doubt is that understanding its methods has never been more important to watching and appreciating the NBA.

In The Midrange Theory , Seth Partnow, NBA analyst for The Athletic and former Director of Basketball Research for the Milwaukee Bucks, explains how numbers have affected the modern NBA game, and how those numbers seek not to “solve” the game of basketball but instead urge us toward thinking about it in new ways. From shot selection to evaluating prospects to considering aesthetics and ethics while analyzing the box scores, Partnow deftly explores where the NBA is now, how it got here, and where it might be going next.

Genres: Sports, Basketball, Nonfiction

288 pages, Hardcover

Published November 16, 2021

Reviews

[Dominic Carlin · Rating 4 out of 5]

Look, okay, yes, I'm a nerd.

I'm not even a basketball fan and I've just read a book about statistical analytics in basketball.

I just like sports and I just like numbers, okay?

[Mrwalkerb · Rating 3 out of 5]

Explained a lot of the past decade’s stylistic shift in an easy to follow manner. That being said the amount of footnotes were distracting and rarely if ever helpful. Would be much more enjoyable if the author wasn’t trying to write an NBA version of Pale Fire

[Lance · Rating 3 out of 5]

Okay for hard core basketball junkies

I liked the concept of this book and most of its narrative on the job and role of analytics in basketball. It’s a word the author states that he hates - at least in the manner that it’s used in sports today. While some sections are excellent, others get so bogged down with numbers and acronyms it can be a challenge to read.

For a good chapter, chapter 8, the same title as the book, does a good job on explaining why there’s less midrange jump shots (12-15 feet from the basket) taken now. Not to say there is no midrange GAME - just not as many shots.

Overall, this is a book best suited for very hard-core NBA fans that should be consumed in small doses. I did like it but I had to stop frequently and go back to remember what some of these acronyms mean. Shows how much I will still need to learn for a complete knowledge of today’s NBA.

[MIKE Watkins Jr. · Rating 3 out of 5]

Pros:

1. The book provides a compelling theory as to why the midrange has "died" in the NBA. Curry alone isn't responsible for this shift. It was initiated with the introduction of zone defenses, which made it to where teams could "straddle" around a center, resulting in an increase of kick-outs to perimeter players. Moreover, in 2004 the NBA introduced "freedom of movement" rules to restrict hand checking and whatnot on perimeter players. This resulted in a more up-tempo play with fewer post-ups by bigs and more PnR's with guards.

I think the most interesting revelation though of the midrange theory is this.. "Two out of every three shots which were long twos in 2004–05 had been replaced by three-pointers by 2019–20. The midranges that went away weren’t selected at random. Rather it was almost exclusively assisted midrange attempts that had been subbed out."

Seth goes on to justify this shift by pointing out how efficient players became over time (even bigs) at shooting 3 pointers via graphics+his own words.



2. I love how the book takes time to showcase the context around stats. Learning that there are many aspects of the game that lead to a single rebound was mind-blowing, to say the least. That instead of looking at who grabs the rebound, one should look at the perimeter defense and contest at the rim that resulted in the rebound.


Cons:


1. The book barely touches on the whole midrange thing...so the title was deceiving. A lot of this book focused on basketball statistics in general.


2. The book was a little too stat-heavy and not as elaborate as it needed to be. For the typical stat junky I think manifesting a book with that ratio is fine, but for someone like me who loves the game but isn't quite as knowledgeable of the analytic side of it....that's problematic.


3. I understand that certain topics in any given field are not as interesting as others. You can get the best professors in the world to teach some of these lesser topics and they still end up falling short of the more interesting topics. However, I think a truly gifted writer is able to make the drop off from the most interesting subject matter to the least not so noticeable. Seth didn't quite do a great job of that in this book....the drop-offs were noticeable. I feel like there were a few stand-out chapters like the midrange theory chapter or the chapter about the importance of the salary cap in dictating team formulation, but yeah.











Cons:

[Ed · Rating 4 out of 5]

Big fan of Seth Partnow and devour everything he writes for The Athletic. Really enjoyed the opening chapters, particularly the great analysis digging deeper into Westbrook's rebounding stats. Unfortunately, the book thins out a bit after that and the final chapters seem like a bit of an afterthought just to up the page count. Also, it would really have benefitted from better editing in terms of cutting down on unnecessary footnotes, of which there are many. By and large - if it's important enough to include, then just include it in the main text!

[Michael · Rating 3 out of 5]

Best book I’ve read on how advanced basketball statistics and the underlying philosophy behind them work. I really enjoyed it but for the over reliance on footnotes which were distracting and robbed the book of momentum.

[Darren · Rating 4 out of 5]

What is or isn’t analytics has become one of the more annoying topics that’s tossed around ad nauseam by the collective basketball media every other day but it’s been a topic I’ve become much more interested in to dull certain boredoms of a long season of a losing team or two and while I’m not one that can fully parse all statistical data with ease this book was an informative read. Doesn’t hold your hand and allows you to come to your own conclusions while not being too dense for the layman to understand. Loved the explanations of the day to day responsibilities of someone in an analytics department especially surrounding the draft. You really see the effort and dedication required to make our favourite teams go. Perfect book for anyone who wants to rethink certain aspects of the game that we are incorrectly taught and/or widen your horizon of what makes a “good” basketball player more than just being a “winner” or what have you

[Omar Zahran · Rating 4 out of 5]

The term “analytics” is one you hear in coverage of the NBA all the time these days. But because of the people that say it, it almost comes off as a dismissive derogatory term aimed at mocking the use of data models in sports.

Partnow tries to establish what that term is and why it’s so much more than just shooting threes. He does a great job explaining how efficiency is king in these discussions, and the intent of it is not to cheapen the game but to make things more fluid and evolve it.

I particularly enjoyed the walkthrough of the calendar year of someone that works in the analytics department of a team as well as the way that he and others in those positions approach numbers.

That being said, this is a book for basketball junkies. If you are not one, you will be lost with a lot of the terminology and industry terms used here. If you want to learn more about the modern data points of NBA basketball, this book is a great place to start.

[Roham Kalkhoran · Rating 4 out of 5]

3.5 stars if I could.

Really interesting book if you are both a big NBA fan and a data nerd, which I am. Does well to explain both some of the key trends in the past few decades (prevalence of 3 pointers, less importance of big men), alongside interesting insights into trade deadline, draft etc from an insider’s POV.

I dock it points because 1) I think the writing style is overly complicated/elevated for what the topic is and 2) the INSANE amount of footnotes - so ridiculous.

Overall interesting read!

[Henry Crabtree · Rating 4 out of 5]

4.5

[Ben Schribman · Rating 3 out of 5]

3.5 listened to this one while I was working so I’m sure I missed a bit. I found the draft section to be most interesting

[Eric · Rating 4 out of 5]

A stats grad student here. You don’t need to know analytics to read this book. All you need is a strong interest in basketball. This book explains the basic formulas and gives you a deeper understanding of what really goes out there on the court and how much can be explained through statistics. This book elaborates on details of the game that easily go unnoticed. A lot of thought goes into each aspect of the NBA. Like a researcher, the book concludes with next steps and the future. I highly recommend for all basketball fans and analytic minds

[Kris · Rating 5 out of 5]

I’d consider this essential reading for those looking to get a deeper understanding into basketball statistics. There’s a bit of a drop off in the later chapters but a very informative read overall.

[Nathan Fisher · Rating 2 out of 5]

Wish I could give this a 2.5 -- another book I'm very ambivalent about, and wish I liked more even as I like it just fine. Grading against the curve of contemporary sports writing, quite good, but that's exactly part of my frustration -- why is it that contemporary sports writing is so lackluster, so allergic to prose? This book is solid for extreme casuals — to be clear, I consider myself basically a casual as well, and yet a lot of the core of the book's content was familiar to me from consuming basketball writing semi-regularly on a high-enough tier (and, of course, watching an above average amount of basketball). There was plenty here that I didn't know in particular, but this didn't radically or substantially alter my understanding of the game or of what 'analytics' is — I was left desiring a more intricate and ambitious book. At times, this was concise to the point of abruptness. I realize this is damning with faint praise, but that said, it's not bad at all.

(There's an interesting little aside here about a team's analytics department having to be extra careful with their trade boards so as not to alert any of the current players of their thinking. I'd be really interested in this dynamic of the front office / analytics / coaching / player nexus — obviously not all players are knee-jerk averse to the insights wrung from advances in tracking data, etc. but even if they all say "it's a business" when asked, that has to be a difficult tension to resolve. I'd be interested in hearing more about how Partnow and his colleagues navigate that terrain — analytics is, as he says, just another way of talking hoops — but it can also be a very relentless and potentially, as he admits, dehumanizing pursuit. What that looks like internally in an organization seems like a suitable entry point to compelling writing on sports, that gets both its wonkiness and its psychological interiority. Would have loved to hear more about that here — has anyone written in-depth about this?)

[Zach Knowlton · Rating 5 out of 5]

Any chance I have to read something from Seth I take some time out of my day to do so. Incredibly stoked to have an entire book to gain some good basketball insights. This is a must read for anyone who wants to learn about and grow in the sports analytics community. I found it to be spot on with many things I'm dealing with in my current sports analytics journey.

[Tiago · Rating 4 out of 5]

That was a very interesting read for me. I am a numbers junkie and always liked sports statistics. So, when I heard about this book, it immediately jumped to the front of my reading list.

The title already catches the eye of the reader as the basketball changed a lot during the last decade (the number of three point shots skyrocketed). But that midrange theory is just one chapter of the book. The book starts by defining what analytics is and, more important, what analytics is not. Then, we get to know the challenges that are tackled with analytics (draft, free agency, salary cap, team and player offensive/defensive evaluation), the dangers of relying too much on analytics (playing for the metric). The book is rich in footnotes and references to basketball analytics sites. There is also an appendix with the formulas for the metrics discussed throughout the book.

There is also one little gem in the book. It is a chapter where the author describe the routine of a stats//analytics professional on a team. We get to know what are the main roles and also the year-round routine. That chapter made the difference when comparing all the books of sports analytics that I read. For anyone interested in numbers and sports, it is a recommended read.

[Clay Kallam · Rating 4 out of 5]

Seth Partnow's "The Midrange Theory" isn't quite what you'd expect. He's a numbers guy, a serious basketball analyst, and his grasp of the analytic revolution in the NBA game is impressive. But if you're expecting to discover new ways of looking at the game, and cutting-edge stats, this is not the book to buy.

It is a good book, but it's really more about the development and application of analytics rather than the deployment of new tools readers can apply to their understanding of the sport. (The seminal book for basketball analytics remains Dean Oliver's "Basketball on Paper," even though much of it has been rendered anachronistic due to the much greater depth and availability of data.)

There are some neat analytical points -- the questionable use of the two-for-one strategy, for example -- but Partnow weaves in the salary cap and other complexities that move beyond such questions as the best way to defend a pick-and-roll.

Basketball junkies, though, should snap this one up. There's plenty to absorb here, and Partnow's clear writing style keeps the book from getting bogged down in too many numbers.

[Hugo Salas · Rating 4 out of 5]

Muy interesante. No sé nada de stats avanzados para la NBA y está fue una bonita introducción. Confirma mucho de lo que "ya sabíamos" a través de métricas complejas (e.g. Jimmy Buckets es una fiera en la defensa y Westbrook tiene más rebotes de los que merece).

Pero le hizo falta un buen editor. Su prosa no fue tan clara y, sobre todo, sus gráficos merecían más cariño. Utilizó muchos acrónimos sin describir y siento que pudo haber hablado más a fondo sobre las métricas sofisticadas.

También, le hizo falta ser más riguroso/matemático en sus explicaciones, se quedó en un punto medio bastante mediocre en donde ni es muy claro para todas las audiencias, ni es suficientemente profundo para los técnicos.

Si a este libro le agregas un buen editor y un buen diseñador para los gráficos, tendríamos una joya.

[Jay Molnar · Rating 3 out of 5]

I enjoy learning about the new wave of how information is affecting the strategy of sports and I'm a fan of that analytical application to basketball. I'm a frequent visitor to the KenPom and Torvik sites for college basketball. I thought this book was going to be a little more generalized to basketball as a whole, but it seemed extremely NBA focused of which I'm just a peripheral fan.

The notes around defensive stats being fairly immature was enlightening and he did a good job explaining the basic tenets of "analytics", but the book as a whole was a bit dense at times especially talking about tracking data which I honestly don't find that interesting. I appreciated the book and hope for more like it, especially in football, but this wasn't my favorite read.

[AndrewMillerTheSecond · Rating 3 out of 5]

I’m a baseball analytics guy and wanted to find some books about analytics in other sports. I have OK knowledge of basketball so there were some non-stat terms that went over my head, but this book is helpful in understanding the meta for the analytics in that sport. The quality is inconsistent; the chapter on the “practice of analysts” is next to useless while the afterword (paperback copy) and chapters on RAPM and the midrange shot were great. There *could*, hypothetically, be much better written primers to basketball analytics, but this might be the best one out there in book form. Beware of the footnotes, too, because he puts them on nearly every page and they frequently add nothing to the book. If not for them, this would be 4/5.

[K Hue · Rating 4 out of 5]

Great read breaking down "advanced metrics"...there is so much more to an NBA season. Didnt realize how hard the analytics team and GM and coaches and players work together for just fractions of a point edges here and there. Eye-opening is that most games are decided by just a few crucial moves, substitution patterns, shot selection, etc. Makes sense as the competition at this level is already very, very elite. Also interesting to read about players who are good in 82 game regular season (Carlos Boozer) vs clutch players in the 16 game playoff season (Robert Horry, who hardly plays during regular season).

[John Chidley-Hill · Rating 3 out of 5]

Although I’ve been covering the NBA off and on for years, I’ve got to admit that there is much I don’t know about analytics and some of the finer points of the game. When I found this book on a library shelf I immediately took it out because it was exactly the kind of book I knew I needed to flesh out my knowledge base.

That said, some sections of this book went right over my head. Even when I re-read them a couple of times. This is also a small quibble, but there were more than a few typos or dropped words. The layout was also sometimes strange and a few of the charts had print that was way too small (but maybe I’m getting old?)

[Sean Matt · Rating 3 out of 5]

it's crazy to me, this phenomenon of basketball stat nerds. you don't really see that in football. prolly 'cause basketball is more self contained, too difficult for some poindexter to generate interesting takes by cutting up a football game in that way
^i like this insight and i got that from reading this book so, in that sense it was worth it

this guy's book is full of some pretty cringe/eye-rolly takes, but it's also got some tidbits of curious info on basketball stats, that i never thought of - which kept me zippin' along thru the whole book

all things considered it was worth reading, but i didn't think it was great by any stretch

[Ward · Rating 4 out of 5]

As a sport analytics student this book was awesome. Really interesting insights into the world of an NBA analytics staff. I think Partnow does a good job of explaining advanced statistical concepts to lay basketball fans who are looking for a deeper dive. I wouldn’t recommend this book to someone who isn’t interested in basketball or data science though as it’s pretty narrow in scope. I also thought there were a lot of footnotes and some of them definitely could’ve just been included in the next.

[Marcus Pacenza · Rating 4 out of 5]

Really interesting look at basketball statistics and analysis from one of the smartest writers in basketball. Partnow approaches old tired topics of basketball analytics and breathes new life into them, covering topics from drafting rookies to determining player value to the "death of the midrange." However, wish the book had more overall direction, the chapters don't flow well together sometimes.

[Tim Tufts · Rating 4 out of 5]

Fascinating look at how tracking data and analytics have developed in the NBA and how it informs the discussions around the sport. I had basically no context about basketball coming into it, but I subscribe to a lot of hockey analytics. It was hard to follow some of the basketball specific details without that baseline knowledge, but the big picture about measuring and understanding the game was clear throughout.

[Scott Martin · Rating 3 out of 5]

(3.5 stars) This book looks to demystify all the talk and conjecture about analytics in basketball. Particularly, it answers charges about how it is killing the mid-range jumper and hurting the game. Not necessarily. It also notes how sometimes a simple box score can be misleading (you might see a guy with 12 rebounds, but how many were uncontested? A good read for a basketball fan, and if you are a huge Seth Curry fan, you really like it.

[Jesus Daboin · Rating 4 out of 5]

Even though I think sports analytics is a fascinating field, this is the first time I have read a book on it. I have been watching basketball for almost a decade and seeing the changes in the game driven by data analytics was incredible. I truly enjoyed Seth's perspective about the evolution of the game and this book made me curious to read more basketball/sports analytics books. A solid 4/5 for me

[Paul Carr · Rating 4 out of 5]

A very good book, not just about basketball analytics, but about all sports analytics. Seth Partnow dives into the minutia of basketball data, and he also explains how to think about and use sports data. How do you go about answering questions? How do you go about asking questions? Seth uses his NBA experience to showcase process at the macro and micro levels. A good read for anyone interested in the sports analytics field.

[Clayton Baum · Rating 3 out of 5]

I feel bad reviewing a book that I barely didn’t finish, but this one was a mixed bag. So many footnotes, and I’m usually pro-footnotes in nonfiction books, but a lot of these were just unnecessary, snide comments. Lot of good stuff in here, and it’s one of those books that helps you understand the game behind the game better, but I guess this is why you don’t want certain analytics guys writing books.