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Stumbling On Wins: Two Economists Expose the Pitfalls on the Road to Victory in Professional Sports |  | Authors: David J. Berri, Martin B. Schmidt
Publisher: FT Press
Category: Book
List Price: $24.99
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Rating:  31 reviews
Sales Rank: 224139
Media: Hardcover
Edition: 1
Pages: 256
Number Of Items: 1
Shipping Weight (lbs): 1.1
Dimensions (in): 9 x 6.1 x 0.9
ISBN: 013235778X
Dewey Decimal Number: 338.477960973
EAN: 9780132357784
ASIN: 013235778X
Publication Date: March 18, 2010
Availability: Usually ships in 1-2 business days
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Product Description
“This book takes the hallowed traditions of sports decision-making and pokes them with a sharp stick.” –Henry Abbott, founder of TrueHoop, housed at ESPN.com “Moneyball should have been called ‘MoneyBaseball.’ Stumbling On Wins covers everything else. Every general manager needs to buy this book to save his owner money. Every fan needs to buy this book to know when it makes sense to yell at the general manager.” —Darren Rovell, CNBC Sports Business Reporter “This is an important book. Berri and Schmidt have been leaders of the revolution in the analysis of team performance in sports and, in this book, they explain why coaches, players, and fans cannot afford to ignore the stats if they want to win. Moneyball gave us an inkling of what is to come, but this is the real deal.” –Stefan Szymanski, author of Soccernomics and Playbooks and Checkbooks “Stumbling On Wins lays it all out—a roadmap of behavioral economics, that runs straight through your favorite sports arena. Brilliant stuff, beautifully written, and sure to captivate any student of economics or sports.” —Justin Wolfers, Associate Professor of Business and Public Policy, The Wharton School, University of Pennsylvania; writer for Freakonomics.blogs.nytimes.com “Berri and Schmidt are true pioneers of modern sports economics, proving time and again that sports are the perfect laboratory for social science research. Stumbling On Wins reveals that sports are more than entertainment; they tell us something important about ourselves.” –J.C. Bradbury, author of The Baseball Economist “This book isn’t just about sports statistics. In Stumbling On Wins, Berri and Schmidt have a compelling story to tell about how people make decisions in sports, and the stats narrate the story. This is a fresh and revealing look at how decision-makers frequently miss the mark and how they can do better.” —Brian Burke, AdvancedNFLStats.com Don’t they want to win? Every sports fan asks that question. And no wonder! Teams have an immense amount of detailed, quantifiable information to draw upon. They have powerful incentives for making good decisions. Everyone sees the results of their choices, and the consequences for failure are severe. And yet, they keep making the same mistakes over and over again...mistakes you’d think they’d learn how to avoid! Now, two leading sports economists reveal those mistakes in basketball, baseball, football, and hockey–and explain why sports decision-makers never seem to learn their lessons. You’ll learn which statistics are linked to wins and which aren’t…and which statistics can predict the future and which can’t (information that just might help you dominate your next fantasy league!). The next quantum leap beyond Moneyball, this book offers powerful new insights into all human decision-making. Because if multimillion dollar sports teams are getting it wrong this badly, how do you know you’re not? • Do better coaches really win more? Phil Jackson versus everyone else • The “hot hand ” and other figments of the imagination Enduring myths of on-court and on-field performance • How old is too old? Are teams playing too many athletes who are past their prime? • Are black quarterbacks underpaid? The curious cases of Donovan McNabb and Brett Favre
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| Customer Reviews:
Showing reviews 1-5 of 31
 Freaknomics meets Moneyball August 19, 2010
Randym
Sports economics sounds like a difficult and dry subject. It's not, at least not as this easy-to-read, absorbing book explains it. The revelations are so surprising and interesting it's hard to put it down.
Stumbling On Wins claims, among other things, that money doesn't buy wins, and that a big payroll can even hurt a team, if the GM doesn't understand what really makes a player valuable. And that GMs actually don't understand what makes players valuable, even though they all think they do. (Just like we all think we're better than average drivers.)
They start out with the famous OBP example - that it took a hundred years before people came to understand that on-base percentage was far more important than batting average or slugging. Then they lay out the evidence for another "market inefficiency" that still exists, in the NFL. Black quarterbacks still have to be much better than white ones to be considered as good. And while all quarterbacks have bad years, a black quarterback will be cut or traded after a bad year, while a white one will not. Based on their analysis, Donovan McNabb and Steve McNair have been better QBs than Brett Farve, but it's Farve who's the sure hall of famer.
Also interesting: they claim first round draft picks aren't a good deal. The most value is found in the second round. If NFL teams had perfect knowledge and were perfectly rational, they'd try to trade down to the second round, rather than up to the first.
A fascinating book that every sports fan should read.
 Linke "Freakanomics" for sports fans August 19, 2010
D. Greenbaum (Lawrence, KS)
"Stumbling On Wins" is a very entertaining book - it essentially takes a statistical, economic approach to sports in an attempt to answer common barroom debates such as which coaches are the best and do things like streaks and hot hands really exist.
This approach to sports isn't new - baseball has been stat-crazy for years, and "Moneyball" took it to the next level by providing (sometimes surprising) statistical value to various aspects of the sport. "Stumbling On Wins" expands the formula to other sports, such as pro basketball and football to answer questions about the real value of coaches and players.
The book is filled with nuggets of interesting data that have the potential to change how you look at sports. For example, in professional football, kickers really do matter (not terribly surprising) but what is surprising is that their skill on kickoffs is actually more valuable to a team then their field goal accuracy. Sound crazy? Well, there's stats to back it up.
Other areas of interest in the book cover things like the relative value of various pro athletes (underpaid and overpaid) which are always fun to debate, and especially for basketball fans, a baseball-level-geekery of analysis which is eye-opening to say the least (hint: rebounds are more important then you think.)
I would recommend this book to anyone with an interest in pro sports, from the casual fan to the fanatic. It is an enjoyable, fairly quick read and like the best books, it challenges how you think.
 Stupid Regression Tricks August 1, 2010
Aaron C. Brown (New York, New York United States)
0 out of 1 found this review helpful
A book like this can do three good things. It can be fun to read, well-written and amusing. It can show deep love and understanding of a sport, giving insights to participants and fans. Or it can illustrate quantitative reasoning, finding non-obvious conclusion from data.
Few books do all three. Moneyball has brilliant writing and baseball insight, but no clever reasoning. The Bill James Handbook 2010 teaches important things about baseball and quantitative reasoning, but is weak on literary style. Mathletics: How Gamblers, Managers, and Sports Enthusiasts Use Mathematics in Baseball, Basketball, and Football is fun to read and a great way to learn reasoning, but the author's interest stops at the box score, he never goes to the field.
This book does none of the above. The writing is wooden and often unclear. There is no interest in the games. Worst of all, the arguments are deeply flawed.
The first extended example claims to prove that shooting percentage in basketball is a better indication of player talent than points scored. This is surprising on the surface. When players do things under reasonably standard conditions, kick points after touchdowns, shoot free throws or bat in baseball, with well-defined outcomes, their average performance is usually tracked. But when players do things under widely varying conditions, especially when their team picks the attempts, we use totals instead. Thus total field goals made for a football kicker, but percentage of points after touchdown; total points scored in basketball, along with free-throw percentage; total RBI's for a baseball player, but batting average (or better, OPS). Totals are also good because they make adjustments for intangibles, for example a good defensive player in many sports will get higher offensive totals, because he is inserted for his defense. Or if a player has good teammates, he will benefit from less defensive attention, but lose out from fewer attempts. Averages can only measure specific skills, not contributions to the team.
To a first approximation, all players on a basketball team should have the same shooting percentage. If a player shoots better than his teammates, he should take more shots, including lower-probability ones, and attract more defensive attention; freeing up better opportunities with less defensive pressure for his teammates. His percentage should go down, and theirs should go up, until equilibrium is reached. The better shooter will show up by getting more points, but not a higher percentage.
This is not exactly true. A point guard, for example, can get a shot every possession, with little work or risk. Getting the ball to the center, with his hands above his waist near the basket, takes work and risks turnovers. So point guards need lower shooting percentages than centers. But the general principle applies, that you expect shooting percentage to vary according the team and a player's role, not according to his talent.
So how do the authors support their surprising contention? By regressing team wins on team shooting percentage. This is known as the ecological fallacy, attributing characteristics of a team on the players that make it up. Of course improving team shooting percentage is good, that's what happens when you put a better shooter in the game. But it is reflected in everyone's percentage, not just the good shooter's.
They compound the problem by validating the result in sample. They never test whether or not it is true, they just assert basketball fans and executives are stupid. I did a simple test. I looked at all NBA players since 1987 who changed teams or positions. For example, Jack Jarrett went from Portland's first backup point guard in 2007-08 to Indiana's starting shooting guard in 2008-09, replacing Marquis Daniels. If something is a skill inherent to a player, Jarrett's 2008-09 performance should be predicted by his 2007-08 performance; but if it results from the role on the team, it should be predicted by Marquis Daniels' 2007-08 performance.
Free-throw percentage is unambiguously player talent, there is no significant statistical effect of the role. The same is true of points. But field-goal percentages are predicted best by about equal combination of player and role. That makes sense, a better shooter will come in and raise the team's shooting percentage, including the percentage for his role, but not up to the full level of his talent, as he will take more shots, and more low-probability shots.
I don't claim this proves anything, it's just as sloppy as the authors' work. It does show that you need to test things, not just run a regression and declare yourself the smartest people in the world.
Another long portion examines racism in NFL quarterback selection. The method is to compare ten white Hall of Fame quarterbacks with four black quarterbacks who had similar per-game stats but shorter careers, only one of whom made it to the Hall. No one can seriously deny that the NFL discriminated against black quarterbacks for most of its existence, but this argument for it is fallacious due to selection bias. By selecting only successful (i.e. Hall of Fame) whites for the comparison group, the authors virtually guaranteed that the black quarterbacks would come up short. What you need to do is pre-select a group of players, based on criteria known before success is determined, and compare the experiences of whites versus blacks.
These are by no means the only errors. The problem with basketball shooting percentage (ecological fallacy, in-sample metrics, no testing) is repeated, and other errors are added, in the construction of "wins" indices for basketball and football. These underlie the arguments in more than half the book, rendering them worthless.
There are some good things about this book. The bibliography cites some excellent books and papers (unfortunately, many of the sound results are butchered by the authors' presentation). It is very short, 138 pages of text and if you don't count long lists barely mentioned in the text, it's probably under 100. The page size is small as well, suggesting the authors had trouble finding enough errors to fill a normal-sized book. Regression appears to be the only technique the authors know how to misuse. Finally, they confine their nonsense to sports. Imagine what would happen if they took their models to Wall Street (whoops, maybe they did).
What it takes to win August 1, 2010
mrliteral
Just how good are athletes, coaches or teams? Do make that determination, we typically rely on statistics. Similarly, the folks who run teams often rely on stats. The problem, as pointed out by David Berri and Martin Schmidt in the brief but informative Stumbling on Wins is that they often rely on the wrong statistics.
Perhaps no single measure of player performance is more commonly known as the batting average in baseball. It's been used for a long time and while it does have its uses, it is not a very reliable indicator to how much a player contributes. As the authors relate, it took a long time for owners and general managers to use better statistics (such as on base percentage) that better correlate to that ultimate statistic: wins. Similarly, scoring in itself is not a good indication of contribution to wins for basketball, as illustrated by the general managing failures of Isaiah Thomas.
Berri and Schmidt focus on the classic big four team sports: baseball, basketball, football and hockey. They look at what factors truly represent good playing or coaching and flaws in many draft strategies. They also dispense with certain myths such as the "hot hand' in basketball.
This is a decent and insightful book well worth the reading for fans of professional team sports. It does cover similar ground as other books, but it does so with enough freshness that it is a good read itself.
Fun to read. Enjoyable and unconventional way of looking at things July 30, 2010
Andy in Washington (Washougal, WA)
First a disclaimer. I am a casual sports fan- meaning that I will watch some games on TV, but I am not a stats or ESPN junkie. I would tell you who won the last few superbowls and NCAA tournaments, but could not name the starting lineup of any pro team. I am also an engineer, so I am very comfortable and familiar with statistics.
I liked this book. The authors take a look at sports (football, basketball, hockey, and baseball) from a mostly mathematical point. As a result of this analysis, they find trends that are not obvious and buck the conventional wisdom. For example, the interception rate of NFL quarterbacks is one of the most watched statistics, as is the ratio of TD passes to interceptions. The authors show that there is very little correlation between interceptions and wins produced by a QB.
There is a little bit of gimickry involved. The book creates several new "statistics" for sports, many of them analogous to the "wins produced" statistic now used in baseball. You can certainly argue whether these are the exact right ways to look at an athlete's contribution, but the authors outline their assumptions quite well.
The Good Points
It was fun to read, and often amazing to see that things I had always believed about certain sports are not supported by statistics
While some knowledge of statistics may give you a better feel for the nuances of their arguments, certainly anyone with even the most basic math skills can understand their points. If you can understand the concept that an event may be caused by multiple factors, and that one factor may be more of a cause than another, you will understand 90% of the math in this book.
Many of the best results are clearly presented in table form-so you can easily find them again during the inevitable arguments with your friends.
The Bad Points
I dislike books where a large amount of information is contained in the notes at the end of the book. It makes it hard to read. Most likely the authors did this to keep the style of the book light and easily read, and they succeeded. But it drives me nuts.
If you understand probability and statistics, the author's simplified and watered down explanations can be mildly annoying. I was baffled by a portion of their explanation when I finally realized they were talking about simple regression analysis.
Overall, I enjoyed the book, and found some new ways of thinking about what skills and statistics by an individual athlete contribute the most to success. It is a great jumping off point for thinking about your favorite sport, and could fill a sports bar with heated discussions for the next 10 years.
Showing reviews 1-5 of 31
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