The Wages of Wins (and Conventional Wisdom)

Warning: shameless lengthy quoting of myself below.

I received in the mail today the book The Wages of Wins. Written by three economists, including the widely published sports economists David Berri and Martin Schmidt, it’s the sports world’s answer to Freakonomics, 2005’s smash best-seller by economist Steven Leavitt.

I mentioned the book a few months back in discussing the issue of competitive balance in baseball (which the authors regard as a) better than is commonly thought and b) far less subject to payroll discrepancies than is commonly thought), and I won’t dwell on that particular topic now. I’ve read about 100 pages so far and it’s a great book: accessible, compelling and funny.

There are a few key points the authors emphasize over and over again:

1) conventional wisdom in sports is often wrong (more on that in a moment)

2) we do need numbers to tell us who is good and who isn’t (more on that in a moment, too)

3) competitive balance is weakest by far in basketball, but competitive balance is not all that important to a league’s economic well-being and, furthermore, in sports in general is a function of factors no one ever really discusses (more on this in a future post)

4) that they (the authors) hate the New York Yankees (no further commentary required)

It is clearly one of the key goals of the book to scrutinize what the authors regard as some of the key pillars of conventional wisdom in sports. Early in the book, they quote at length the legendary economist John Kenneth Galbraith. Here, in part, is what JKG had to say about  “conventional wisdom,” a phrase the authors say Galbraith himself coined, in 1958:

“…men react, not infrequently with something akin to religious passion, to the defense of what they have so laboriously learned. Familiarity may breed contempt in some areas of human behavior, but in the field of social ideas it is the touchstone of acceptability…”

A commonly heard contention in the social sciences in general is that it gets it backwards to argue that we believe what we see. In fact, it’s closer to the truth to argue that we see what we believe. In other words, our perceptions often colored cloud our judgment and our ability to see beyond our particular biases and pre-conceived notions. This is why, in addition to warranted skepticism about conventional wisdom (as long as that skepticism is well informed and well substantiated), we need data to keep us honest. Related to this latter point, the authors quote sports writer Allen Barra at some length:

“’Stat nerd” they (critics of the statheads) snort contemptuously at me…but the truth is that they depend as much on numbers as anyone else…What else, after all, are you going to rely on? What, in the final analysis, are statistics but a record of what a player does when you’re not watching him? And we don’t have time to watch 99% of the players 99% of the time.”

I’ll get into some of the particulars of the book over the next couple of weeks, but I wanted to highlight these two larger and related concerns (on conventional wisdom and reliance on systematic data) because they crystallize well many of my criticisms of the way sports (not to mention politics) are covered.

One of things that struck me about the criticisms of Moneyball whenthat book came out three years ago was the anger directed toward the author and, by extension, Beane’s methods themselves, for displaying a kind of pointy-headed arrogance about sabermetrics’ understanding of baseball. But, as I wrote earlier this year in the Gadflyer the charge of arrogance arguably better applies not to the data crunchers, but to their critics:

“There are interesting parallels between [the global warming] debate and the one in Michael Lewis' Moneyball, the book that explicated Oakland A's General Manager Billy Beane's philosophy for evaluating talent and putting together a consistently competitive baseball team on a limited budget. On one side of the divide that Lewis sets up in the book (and over-states to some extent) are the traditionalists, that is, the scouts, who observe young players in person and assess their future potential based on what their eyes and experience tell them. These are blue-collar, beer drinking guys who've spent a life time in the baseball equivalent of the trenches – in broken down hotels and half-empty ballparks in the middle of nowhere. On the other side are the so-called sabermetricians, the new wave of baseball analysts and personnel people who rely on sophisticated computer analysis of a player's previous record to project their likely future performance. Lewis portrays the scouts as resentful at the young whipper-snappers who don't actually know anything about the sound and feel and smell of the game, so wrapped up are they in their ivory tower models.

The scouts and [global-warming skeptic Bill] Gray see the computer driven intellectuals as elitist and arrogant and out of touch with how things really work. But, the striking thing about the scouts and about Gray is this: the powerful and unstated arrogance in their outlook. Their eyes tell them everything they need to know about how the world works. That humans can deceive themselves, or miss crucial details of a complex picture, or maintain perceptions colored by bias of one sort or another is implicitly ruled out here….

Neither global warming scientists nor sabermetrics claims to have God-like powers of foresight. Instead, they utilize probability theory to argue that, over the long run, the patterns and trends they see have increasing relevance. They can't know what will happen tomorrow. But, they can make plausible guesses about what, on average, is likely to happen over time. That's a very different kind of knowledge claim than the one that Bill Gray imputes to his ideological opponents. Gray can't predict the future either. But, he wants us to trust that he can, because he's flown into hurricanes and if anyone fails to see what he's been through, what he knows in his gut, well, they can't be acting in good faith.”

As I say in the Gadflyer piece, the performance analysts and stat guys (and global warming scientists) can, of course, be arrogant, not to mention wrong. But, The Wages of Wins, like the more rigorous performance-based turn in analyzing sports more generally, is serving an important function: scrutinizing our own pre-conceptions (a worthwhile endeavor in all areas of human thought) and holding accountable the too common seat-of-their pants analysis of the sports commentariat who think that because they say so, no further exploration (or explanation) is required.

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