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107 of 122 people found the following review helpful:
1.0 out of 5 stars
Bad math smugly explained, July 28, 2006
This review is from: The Wages of Wins: Taking Measure of the Many Myths in Modern Sport (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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20 of 24 people found the following review helpful:
2.0 out of 5 stars
Disappointing, August 14, 2006
This review is from: The Wages of Wins: Taking Measure of the Many Myths in Modern Sport (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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4 of 5 people found the following review helpful:
1.0 out of 5 stars
A Loser, June 6, 2006
I love sabermetric/sports analysis research and writing. Unfortunately, this book is extremely poorly written. Half the volume concerns the analysis of NBA basketball and seeks to rate players based on a new productivity model.
Unfortunately, this model makes no sense. It overvalues greatly the rebounding and undervalues the defense that causes missed shots that lead to the rebounding. These economists are getting cause and effect completely BACKWARDS... and thus there rating scheme vastly overrates and underrates various players.
For a much better analysis, read Dean Oliver's BASKETBALL ON PAPER.
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