#DigitalSkeptic: Moneyball May Not Be So 'Money' After All
PHOENIX, Ariz. ( TheStreet) -- Michael Lewis may have written "the" book on the power of numbers. But he's got no problem telling anyone who bothers to ask that, duh that power is not perfect.
"It's right there in there in the book: Billy Beane fired Jeremy Giambi because he pissed him off, not because of what the numbers told him," said the author of Moneyball: The Art of Winning an Unfair Game , about the manager and former outfielder of the Oakland Athletics.
I caught up with Lewis (more on that in a sec) as he rolls out what will probably be his next masterful deep dive, Flash Boys: A Wall Street Revolt , which shines a light into the dark-matter universe of high-frequency trading.
Lewis was kind enough take my questions on his 2003 classic account of how Beane, the quirky, numbers-obsessed Oakland A's manager, assembled a near-championship team using data and not just baseball common sense.
And I had to hand it to the man: Here was a legit literary heavyweight, with everything to lose and nothing to gain, having a highly technical conversation about the core thesis of Moneyball in an executive conference room full of top-level editors and writers as part the Society of American Business Editors and Writers annual conference. Lewis, it turned, out had no problem tiptoeing extemporaneously through the minefield of the theoretical limits of numbers, data and information.
"Anybody who wants to use data to not make a decision points to Moneyball," he said with some sadness. "And that is just not what the book does."
Moneyball never the answer?
I had first gotten wind of the limited case for information-based analysis in baseball -- and life itself -- about a year ago when meeting Randy Levine, president of the New York Yankees. With almost no prompting, Levine stated emphatically that even though Moneyball had become the brand for teams that use pure data to win, he knew for a fact that Billy Beane had not relied strictly on information when making baseball decisions for the near-championship run of the Oakland A's.
"Moneyball was a great movie," was the quote I jotted down. "But there was a lot of Hollywood in it. Baseball doesn't work that way." Levine declined interviews when I followed up to confirm. Since then I have been chasing after Lewis to comment on Levine's sense that numerical analysis in baseball is not the all-knowing, all-seeing force many hold it up to be.
Lewis not only confirmed Levine's skepticism about the be-all, end-all power of numbers, but in many ways was as articulate and measured a spokesman for the limits of data and information as I've ever spoken with.