More Than Meets the Eye: Moneyball and Poker

Last Christmas Vera got me a Kindle. Since then I’ve managed to read a half-dozen titles or so on the device, although whenever I find myself desirous to pick up a new read I still more often than not choose a used hard copy (often cheap) over an electronic one (sometimes cheap, sometimes not).

For instance, Jonathan Lethem’s Motherless Brooklyn (1999) was recently recommended to me, and I ended up ordering a used paperback rather than go for the Kindle version. It’s a cool read, a very inventive and smart example of “hard-boiled” fiction. Also shares some of the same territory I tried to cover in my Same Difference (which is why Lethem’s book was recommended to me).

With Amazon Prime, though, I get to take a book out of the “Kindle Lending Library” each month, and for August I chose Moneyball (2003) by Michael Lewis. That’s the best-seller telling the story of general manager Billy Beane guiding the Oakland A’s to success on the field despite spending relatively little on salaries via innovative methods of evaluating talent. (A well-regarded film adaptation starring Brad Pitt appeared last year.)

The book is about more than just Beane, though, relating the whole history of so-called “sabermetrics” or the analysis of baseball statistics pioneered by Bill James and others. I’ve written here about James and his Baseball Abstract before, noting how as a young person I was fairly fascinated by James and his unique way of crunching baseball’s endless numbers to come up with new and different ways of interpreting what exactly is happening when we watch a baseball game.

I’m about halfway through Moneyball and so far am appreciating Lewis’ way of telling the story as well as his understanding of the historical context of baseball, generally speaking, and sabermetrics in particular. And -- perhaps unsurprisingly -- I’m finding myself struck time and again with how the question of evaluating players’ talent in baseball overlaps with similar questions about the skill of poker players.

The parallels are seemingly endless. In both cases there exists objective evidence from which come ideas about performers’ skills. We see poker players win hands. We see baseball players make plays. And in both cases stats are produced which can be later examined and from which further conclusions might be drawn.

But there’s mystery in both cases, too, as well as other factors that cloud our judgment, making it harder to understand the significance of, say, a baseball player earning a walk or a poker player making a well-timed three-bet and forcing a fold.

Here’s just one short passage from early in Moneyball illustrating three different points of comparison. It comes in the context of characterizing how scouts tended to evaluate talent prior to the rise of sabermetrics and advances in technology that enabled a lot more depth and breadth when it came to statistical analyses:

“There was, for starters, the tendency of everyone who actually played the game to generalize wildly from his own experience. People always thought their own experience was typical when it wasn’t. There was also a tendency to be overly influenced by a guy’s most recent performance: what he did last was not necessarily what he would do next. Thirdly -- but not lastly -- there was the bias toward what people saw with their own eyes, or thought they had seen. The human mind played tricks on itself when it relied exclusively on what it saw, and every trick it played was a financial opportunity for someone who saw through the illusion to the reality. There was a lot you couldn’t see when you watched a baseball game.”

The parallels to poker here are obvious. Most of us interpret others’ decisions at the poker table by comparing them to our own, sometimes to our detriment. Our views of others are also often swayed heavily by what happened recently, with what happened on the last hand often given undue importance. And there are many examples in poker where we see something clearly yet interpret it wrongly.

That latter point becomes kind of a theme in the book, what Beane comes to refer to as being “victimized by what we see.” The work of James and others helped Beane realize that “the naked eye was an inadequate tool for learning what you needed to know to evaluate baseball players and baseball games.”

Poker has seen its own version of “sabermetrics” emerge over the last decade with the rise of online poker and tracking programs like PokerTracker and Hold’em Manager that yield all sorts of additional information about players’ tendencies, performance, and -- if interpreted correctly -- skill. Ideas that in some cases challenge the received wisdom of the old guard, represented in Moneyball by the fraternity of old scouts whose methods were challenged by Beane and his statistical-minded cohorts.

I’m glad I chose Moneyball as my Kindle read for this month. I suspect other poker players -- especially those who happen also to be baseball fans -- would like it, too.