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The Wages of Wins: Taking Measure of the Many Myths in Modern Sport. Updated Edition (Stanford Business Books) [Paperback]

David Berri , Martin Schmidt , Stacey Brook
3.4 out of 5 stars  See all reviews (16 customer reviews)

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Book Description

September 7, 2007 Stanford Business Books
Arguing about sports is as old as the games people play. Over the years sports debates have become muddled by many myths that do not match the numbers generated by those playing the games. In The Wages of Wins, the authors use layman's language and easy to follow examples based on their own academic research to debunk many of the most commonly held beliefs about sports.

In this updated version of their book, these authors explain why Allen Iverson leaving Philadelphia made the 76ers a better team, why the Yankees find it so hard to repeat their success from the late 1990s, and why even great quarterbacks like Brett Favre are consistently inconsistent. The book names names, and makes it abundantly clear that much of the decision making of coaches and general managers does not hold up to an analysis of the numbers. Whether you are a fantasy league fanatic or a casual weekend fan, much of what you believe about sports will change after reading this book.

Frequently Bought Together

The Wages of Wins: Taking Measure of the Many Myths in Modern Sport. Updated Edition (Stanford Business Books) + Scorecasting: The Hidden Influences Behind How Sports Are Played and Games Are Won + Stumbling On Wins: Two Economists Expose the Pitfalls on the Road to Victory in Professional Sports
Price for all three: $47.25

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Editorial Reviews

Review

"Wages is provocative, stimulating, and challenging." —Dick Friedman,—Sports Illustrated


"The Wages of Wins brilliantly and provocatively argues that our eyes betray us when we watch professional athletes. To see the truth about how good a point guard or a quarterback really is, we need the help of algorithms." —Malcolm Gladwell,author of Blink and The Tipping Point


"When I read the book, I was impressed by the amount of effort that went into compiling the reams of data that underlie the work. . . . The fundamental case the authors make is that the statistical analysis shows that the conventional wisdom about sports is dead wrong—that the data, as they put it, 'offers many surprises.'" —Joe Nocera,
New York Times


"Sports fans with an analytical bent shouldn't skip this book. And come to think of it, perhaps sports executives should be reading it as well."—The Free Lance-Star


“This book presents complex economic analysis in a breezy manner that the casual sports fan and econophobe will appreciate and enjoy. I plan to assign it to students and recommend it to friends.”—Michael Leeds, Temple University, and author of The Economics of Sports

From the Inside Flap

Arguing about sports is as old as the games people play. Over the years sports debates have become muddled by many myths that do not match the numbers generated by those playing the games. In The Wages of Wins, the authors use layman's language and easy to follow examples based on their own academic research to debunk many of the most commonly held beliefs about sports.
In this updated version of their book, these authors explain why Allen Iverson leaving Philadelphia made the 76ers a better team, why the Yankees find it so hard to repeat their success from the late 1990s, and why even great quarterbacks like Brett Favre are consistently inconsistent. The book names names, and makes it abundantly clear that much of the decision making of coaches and general managers does not hold up to an analysis of the numbers. Whether you are a fantasy league fanatic or a casual weekend fan, much of what you believe about sports will change after reading this book.


Product Details

  • Paperback: 312 pages
  • Publisher: Stanford Business Books; 1 edition (September 7, 2007)
  • Language: English
  • ISBN-10: 0804758441
  • ISBN-13: 978-0804758444
  • Product Dimensions: 6.2 x 0.8 x 8.9 inches
  • Shipping Weight: 15.2 ounces (View shipping rates and policies)
  • Average Customer Review: 3.4 out of 5 stars  See all reviews (16 customer reviews)
  • Amazon Best Sellers Rank: #530,934 in Books (See Top 100 in Books)

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Customer Reviews

Unfortunately, this book is extremely poorly written. t.g. randini  |  3 reviewers made a similar statement
To enjoy this book, you have to like either statistics or sports. S. Michael Bowen  |  4 reviewers made a similar statement
Most Helpful Customer Reviews
123 of 140 people found the following review helpful
1.0 out of 5 stars Bad math smugly explained July 28, 2006
By D. Blum
Format:Hardcover
I really looked forward to this book after reading the review in The New Yorker. The reviewer's critical skills, evidently, do not extend to evaluating the merits of a logical argument.

There are so many logical problems with the analysis in this book, it is difficult to know where to begin.

I will limit myself to just a handful, among countless possibilities.

1) The authors find a correlation between the stability of a basketball team's roster and its winning percentage, and conclude that roster stability is a factor in producing wins! Classic problem of mistaking effect for cause. Clearly, winning teams are disinclined to make major roster changes, and losing teams are eager to. I was so amazed at this I reread it to see if I missed where they pointed this out. They didn't.

2) The authors show a correlation between more assists and winning percentage and conclude that assists help produce wins. Again, very silly. A team with a higher shooting percentage and fewer turnovers will of course get more wins and produce more assists. But the assists are not producing the wins - the shooting percentage is. Were these factors discounted? Not according to the text.

3) Most problematic, the authors define a way of measuring the value of players to a team, and then "prove" their method by summing these values, per player, across each team, and show that they do indeed predict the number of wins each team will get. What they fail to realize is that their method of apportioning value to a player necessarily sums back to team totals such as points per possession that we know correlate to wins per team. But this in no way proves that the apportioning is wrong. We could just as easily base each player's value "team's points while players is on the floor - opposing team's points while player is in the floor". Sum for all players on team, and you will find the team's points-per-game and the opposition's points per game, and you have just "proven" that your method of measuring a player's value is accurate.

4. In looking at rebounds, there is not even the slightest caveat that a player's rebounds per game are affected by who he shares rebounding responsibilities with. If you are in the front court with Shaq, you will get fewer rebounds, not because the other team gets them, but because your teammate does, so comparing rebounding stats between players across teams is highly questionable.

5. Ridiculously, they conclude that adding great players to your roster makes the other players worse not better (this is written as a great revelation, demythifying the common presumption that great players make teammates better). Adding great players indeed will make other players statistically less productive. They will take fewer shots, get fewer rebounds, fewer assists if a new ball-handler is added, etc. And so, according their evaluation method, the other players become worse. This should clearly tell them there is something wrong with their system, based so heavily on specific metrics of productivity. Instead, they simply accept the merit of their method as fact, and conclude that adding great players really makes other players worse!!!

The most frustrating thing about this book, however, for an analytically minded reader, is its smugness. They understand statistics. They have the answers. They are bringing them down from the mountains and explaining them to us idiot peons. All while their reasoning is so problematic.

I in no way am a supporter of the intuitive and nonsensical drivel one hears from so many sports coaches, players and commentators. I would have enjoyed a good, statistical, analytical study of the game of basketball. Unfortunately, this is not it.
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22 of 28 people found the following review helpful
2.0 out of 5 stars Disappointing August 14, 2006
Format:Hardcover
I had high hopes for this book but my expectations were not met. The authors are clearly eager to bear the Freakonomics mantle (they say as much in several places), but unfortunately they do not exhibit anything resembling the flair of Levitt and Dubner. Their cute comparison of quarterbacks and mutual funds just sounds like a cheap imitation of the comparison between teachers and sumo wrestlers (which, honestly, wasn't all that clever anyway). Much of the other writing also seems to imitate the conversational style of Bill James, but without as much wit. Overall the writing comes off as alternately condescending and self-congratulatory, and sometimes both.

Style aside, the book contains a number of substantive weaknesses. For example, the chapter on the effects of labor shortages on fan attendance shows clear signs of bias. The authors favorably cite plenty of evidence that supports their hypothesis; and when confronted with evidence to the contrary, they suddenly decide to pick it apart and explain it away. Sorry guys, it doesn't work that way. This clear example of "disconfirmation bias" causes the chapter to lose all credibility. It wouldn't hold up in a peer-reviwed journal.

Further, although the authors claim to be "taking measure of the many myths in modern sport" (the subtitle of the book), they actually devote a lot of effort to knocking down strawmen. Is there anyone alive who really thinks that "the best players in basketball score the most" or that "quarterbacks should be credited with wins and losses"? No one with more than a passing knowledge of sports actually believe these things, but the authors act awfully smug after debunking these nonexistent "myths." Yes, we're all aware that offense is at most half of football, and that the passing attack is only about half of that. Luckily no one attributes wins to quarterbacks, except maybe to point out that a team can win with a mediocre QB (e.g., pointing out Trent Dilfer's career winning percentage) -- which is a different issue altogether.

The book also spends a lot of time trying to analyze basketball using methods that are much better suited to baseball. Don't get me wrong, I admire their effort to subject basketball to some analytical rigor. But baseball is largely an amalgam of statistics and can be studied as such. Basketball simply cannot. There are too many events in basketball that clearly affect the game but are not quantified (a pick, a shot that is altered but not blocked, a team deciding not to drive against a particular player, a player drawing a double team and getting a teammate open, the second-to-last pass of a possession). One might conclude, based on the demonstrated strong correlation between wins and the conventional statistics employed in this book, that these events are all relatively unimportant. But this argument ultimately fails because the purpose of the analysis is to measure the contributions of individual players. A team might score two points but the model does not adequately break down individual contributions beyond who scores the points and, if applicable, who gets the assist. Similarly, most of what happens on defense isn't recorded, and the model only takes into account steals and blocked shots. The authors sweep these weaknesses under the rug and proceed to devote dozens of pages to comparing players based on their new, supposedly superior, measures of individual performance. This is an enormous flaw.

Further, I was also struck how a team of economists could write about the value of basketball players without paying attention to the supply curve. They do adjust some of their stats for league-average at the position, but not on a category-by-category basis. In the final chapter, where they purport to show that scorers are paid too much, they fail to examine the issue of scarcity. My wild guess is that the data would support their conclusion, but I was struck by the absence of real analysis here.

Of course, no book on sports statistics and/or economics is complete without the obligatory nod to the genius of Billy Beane and the claim that salary disparities do not lead to competitive imbalance. This version of the story is no more convincing than any of the others. They happily point to the 2003 Marlins as an example of a low-payroll team winning against the odds, but somehow ignore the fact that a number of those players (Derrek Lee, A.J. Burnett, Josh Beckett, Ivan Rodriguez, Alex Gonzalez, Mike Lowell) are now earning big salaries in big markets while the Marlins are under .500. Sure, a team can win with young players who haven't yet become eligible for free agency or arbitration, but is that any way to build a franchise for long-term success? Where is the analysis of that rather obvious question? And where is the point, made quite clear in Moneyball, that no inefficient market can last forever? What happens when the next Billy Beane is hired to run the Yankees?

I will grant that the book is thought-provoking. But ultimately there are many other books on sports statistics and economics that are much more readable and well-argued than this.
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2 of 2 people found the following review helpful
1.0 out of 5 stars Ugh. April 25, 2011
Format:Hardcover
Berri's ignorant dismissal of years and years of research on how to quantify player efficiency/value/production for basketball is one of the stupidest straw-man arguments I have ever seen:

"This is the point we are making about decision making in the NBA. It is
not that people in the NBA are lazy or stupid. It is just that the tools at their
disposal do not allow them to see the value of various actions players take on the
court." (p.215)

And yet, Berri's purported values of rebounding (among other things) is, by every statistical model imaginable, absolute crap.

The problem here, like many reviewers have noted, is that basketball is NEVER a one-on-one interaction. To base values on the marginal production of a specific statistic continues in the future is absolutely stupid. Berri cites the "repeatability" of rebounding as reason to "believe" in it, specifically. But the confounding variables that make up rebounding are absolutely through the roof.

Some examples:

Input:
-Nine other players have the opportunity for the rebound, there are marginal returns on rebounding, especially defensive rebounds(Eli Witus)
-Defensive rebounds are frequently due to chance/non-skill related factors (Dean Oliver)
-Team pace, opponent team pace, opponent field goal attempts, team field goal attempts, position relative to basket: these all explain huge amounts of variation in rebounding (Obviously).

Here are two quick examples of this confounding:
-Imagine there are two players that are perfect clones, and will respond exactly the same given the same situation. If Clone #1 plays Center and Clone #2 plays Power Forward, Clone #1 will be more likely to get the rebound simply due to the position he plays (closer to the basket).
-Imagine an opponent shooting a well-guarded 3-point shot. The fact that the rebound exists is, to a high degree, the responsibility of the one forcing the missed shot (Dean Oliver). Whoever catches the "fly ball" can improve their position to catch it, yes; but players are not capable of predicting very accurately where the ball will bounce towards (or IF it will bounce at all).

Output:
-This one is what Berri misses entirely: players that rebound well offensively defend more poorly (SPM model). In fact, in my one-year studies on Regularized Overall Plus-Minus and offensive rebounds, there is (relatively) NO correlation between player offensive rebounding performance and team efficiency margin. This has also been discussed on the team level (by Pomeroy, for college hoops) - that offensive rebounding teams fail to 'get back' on D.
-Dirk Nowitzki physically CAN'T get your overvalued rebound as frequently because he is busy shooting three-pointers, but when he's not taking the shot, he is right there. (Okay, this is less of a variable and more of a rant).

The stupidest result of this system that bugs me to no end is his current 2011 numbers saying that Kevin Love is the most valuable player in the NBA. The adjusted plus-minus model, to a very high degree of cross-validated accuracy, puts Love at around the 170th-most valuable player. Berri's dismissal of the Adjusted Plus-Minus model is mind-boggling. By definition, the standard adjusted plus-minus model predicts OUT-OF-SAMPLE data with the highest degree of reliability. And the regularized plus-minus model does the same in terms of precision.

His other argument that Adjusted Plus-Minus data does not work since it does not correlate year to year is through his lack of understanding of how the statistic works. Yes, a statistical model for plus-minus (which Berri SHOULD have done) would carry over yearly...and Berri's mythical model will obviously carry over with high degrees of year-to-year reliability. But honestly, who cares if it doesn't carry over year-to-year if it predicts any given sample of data with higher accuracy? And the extremely accurate statistical plus-minus models (and the conglomerates of them) still use box scores under the THEORY of the adjusted plus-minus model, and predict more accurately than Berri's "WinsProduced."

In summary:
"Post hoc, ergo propter hoc" might work somewhat with individual statistics in a sport like baseball, but to apply simple correlation of player statistic A to team statistic A is, and I mean this, one of the most shortsighted things I've ever seen in basketball analysis.
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Most Recent Customer Reviews
5.0 out of 5 stars Great Book for understanding basketball production
The Wages of Wins does a great job breaking down common misconceptions about which NBA players are doing the most helping their teams to win. Read more
Published on March 10, 2011 by Paul
5.0 out of 5 stars The Wages of Wins
Fantastic read. Not something that one can read quickly or just skim if one hopes to get the most out of the book. Read more
Published on November 22, 2009 by Adam Resnick
5.0 out of 5 stars Great intro to the analysis of sports based on analytics.
WoW is a great introduction to thinking more critically about sports and how we define "the best".
Published on November 16, 2007 by G. Caprio
4.0 out of 5 stars Great Topics, Good Value
"Who's the best of all-time?" "Who's better than Tom Brady?!" "Kobe is MVP!" When the conversations turn to sports, those types of questions always linger and don't leave my head... Read more
Published on March 18, 2007 by Bret Dougherty
4.0 out of 5 stars A Very Unique And Entertaining Book
If you want an example of taking a unique look at a topic in a way that wins the reader, you have one in "The Wages of Wins".

David J. Berri, Martin B. Read more
Published on February 9, 2007 by Indiana Jeff Reynolds
3.0 out of 5 stars good ideas, not great book
very interesting and insightful analysis but unfortunately authors take a cutesy approach to presentation and it falls flat on its face. Read more
Published on December 18, 2006 by P. T. Kelly
3.0 out of 5 stars Good ideas, bad presentation
I bought this book after reading the authors blog for a while, and was a bit dissapointed. While they have some interesting ideas, I didn't find their arguments nearly as... Read more
Published on November 29, 2006 by B. Bauleke
1.0 out of 5 stars Wages Of Frustration
I really wanted to like this book. In the end however, reading it was strikingly similar to getting my younger sister to describe the latest Harry Potter book. Read more
Published on August 20, 2006 by Stephen Amell
4.0 out of 5 stars Put Reality in Your Fantasy League
To enjoy this book, you have to like either statistics or sports. Preferably both: *The Wages of Wins* is a crash course in *Freakonomics* for the really, really motivated guys in... Read more
Published on August 17, 2006 by S. Michael Bowen
5.0 out of 5 stars Freakonomic Sports
Freakonomic sports. This delightful book uses the statistics coming from professional sports combined with the mathematical analysis tools from mathematics to develop a bunch of... Read more
Published on June 28, 2006 by John Matlock
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