« »
July 16, 2003 » 9:43 pm

Moneyball

I had many reasons for reading Michael Lewis’s latest book, Moneyball: The Art of Winning an Unfair Game. The book is about baseball, which I love, and more specifically, about the Oakland A’s recent run of success. I’ve been living in the Bay Area for about seven years now, and have adopted the A’s as my American League team. (Becoming a Giants‘ fan was not an option, as I remain loyal to my hometown Dodgers.) The book also talks a lot about Paul De Podesta, a fellow alumnus who graduated one year before me.    (1K)

After finishing the book, I discovered another reason for reading Moneyball: It offers insight that’s relevant to my interest in understanding collaboration and a compelling case study of one particular community.    (1L)

Metrics    (1M)

Moneyball is about how economics have changed the game of baseball. Up until the late 1990s, evaluating ballplayers had been an exercise in hand-waving, gut instincts, and misleading measurements of things like speed, strength, and even the structure of a player’s face. These practices had long been institutionalized, and there was little incentive to change.    (1N)

Market forces created that incentive. First, player salaries skyrocketed. It was more acceptable to risk $10,000 on a prospect than it was to risk $10 million. Second, market imbalances created a league of haves and have-nots, where the richest teams could spend triple the amount on salaries than the poorest. For small market teams — like the A’s — to compete, they had no choice but to identify undervalued (i.e. cheap), overachieving players.    (1O)

This new need led baseball executives like Oakland’s Billy Beane to the work of Bill James, a longtime baseball writer with a cult following. James castigated the professional baseball community for its fundamental lack of understanding of the game, and set about to reform the way it was measured. One problem was an overreliance on subjective observation. James wrote:    (1P)

Think about it. One absolutely cannot tell, by watching, the difference between a .300 hitter and a .275 hitter. The difference is one hit every two weeks. It might be that a reporter, seeing every game that the team plays, could sense that difference over the course of the year if no records were kept, but I doubt it. Certainly, the average fan, seeing perhaps a tenth of the team’s games, could never gauge two performances that accurately — in fact if you see both 15 games a year, there is a 40% chance that the .275 hitter will have more hits than the .300 hitter in the games that you see. The difference between a good hitter and an average hitter is simply not visible — it is a matter of record.    (1Q)

James was not simply a lover of numbers. Baseball was already replete with those. He was an advocate for numbers with meaning. The game had far less of these. Errors, for example, are a subjective measure, determined by a statistician watching the game, of whether or not a player should have made a defensive play. They do not account for a player’s ability to get in position to make a play in the first place. As a result, errors are a misleading measure of defensive ability.    (1R)

Lewis makes an important point about James’s work:    (1S)

James’s first proper essay was the preview to an astonishing literary career. There was but one question he left unasked, and it vibrated between his lines: if gross miscalculations of a person’s value could occur on a baseball field, before a live audience of thirty thousand, and a television audience of millions more, what did that say about the measurement of performance in other lines of work? If professional baseball players could be over- or under-valued, who couldn’t? Bad as they may have been, the statistics used to evaluate baseball players were probably far more accurate than anything used to measure the value of people who didn’t play baseball for a living.    (1T)

Extending this line of thinking further, how do we measure the effectiveness of collaboration? If we can’t measure this accurately, then how do we know if we’re getting better or worse at it? Baseball has the advantage of having well-defined rules and objectives. The same does not hold with most other areas, including collaboration. Is it even possible to measure anything in these areas in a meaningful way?    (1U)

The Sabermetrics Community    (1V)

James called his search for objective measures in baseball “sabermetrics,” named after the Society for American Baseball Research. Out of his work emerged a community of hard-core fans dedicated to studying sabermetrics. Lewis writes:    (1W)

James’s literary powers combined with his willingness to answer his mail to create a movement. Research scientists at big companies, university professors of physics and economics and life sciences, professional statisticians, Wall Street analysts, bored lawyers, math wizards unable to hold down regular jobs — all these people were soon mailing James their ideas, criticisms, models, and questions.    (1X)

…    (1Y)

Four years into his experiment James was still self-publishing his Baseball Abstract but he was overwhelmed by reader mail. What began as an internal monologue became, first, a discussion among dozens of resourceful people, and then, finally, a series of arguments in which fools were not tolerated.    (1Z)

…    (20)

The swelling crowd of disciples and correspondents made James’s movement more potent in a couple of ways. One was that it now had a form of peer review: by the early 1980s all the statistical work was being vetted by people, unlike James, who had a deep interest in, and understanding of, statistical theory. Baseball studies, previously an eccentric hobby, became formalized along the lines of an academic discipline. In one way it was an even more effective instrument of progress: all these exquisitely trained, brilliantly successful scientists and mathematicians were working for love, not money. And for a certain kind of hyperkinetic analytical, usually male mind there was no greater pleasure than searching for new truths about baseball.    (21)

Bill James had three important effects on the community. First, his writing created a Shared Language that enabled the community to grow and thrive. Second, he Led By Example, which gave him added credibility and created a constant flow of ideas and activity. Third, he answered his mail, and in such a way, transformed his monologue into a community dialogue.    (22)

The story of the sabermetrics community’s constant battle with baseball insiders provides a lesson on the dissemination of new ideas. Lewis describes how Major League Baseball largely ignored sabermetricians, even in the face of indisputable evidence, and explains how even today, the impediments continue. Sadly, the forces of institutionalization have prevented progress in many organizations and communities, not just baseball.    (23)

A Brief Review    (24)

Moneyball isn’t just a thought-provoking treatise on the objective nature of human affairs. At its core, it’s simply a great baseball book. Lewis is an excellent story-teller, and his retelling of interactions with players such as David Justice, Scott Hatteberg, and Chad Bradford make you feel like you’re in the clubhouse. More than anything, Moneyball is a fascinating portrayal of Billy Beane, the can’t-miss prospect who missed, and who then turned the Oakland A’s into baseball’s biggest success story.    (25)

Tags: , ,

« »

2 Responses to “Moneyball”

  1. […] incredible that this is still an issue in professional sports, 14 years after Moneyball was first published and several championships were won by analytics-driven franchises (including two […]

  2. […] it’s incredible that this is still an issue in professional sports, 14 years after Moneyball was first published and several championships were won by analytics-driven franchises (including two “cursed” […]

Leave a Reply