Book, 288 pages.
This may be the most important book — and certainly one of the most influential books — that I read this summer.
While this book, on the surface, is about Billy Beane, the General Manager of the Oakland A’s and his successful rebuilding of a team on a shoestring budget, it also introduced me to the history of “sabermetrics” (also “sabremetrics” and “sabrmetrics”) that Beane used as his manifesto. Sabermetrics (which derives its name from the Society of American Baseball Research (SABR) was created by Bill James in the late 1970s (see http://www.baseball1.com/c-sabr.html for a good overview of the subject).
James, who to the best of my knowledge, was neither a statistician, mathematician or computer programmer, after pouring over thousands of pages of statistical data discovered an extraordinarily important, simple truth about baseball that had been overlooked for over 150 years: outs are bad for the team at bat. Anything that creates outs was to be eliminated; anything that decreased outs was to be encouraged. From this simple statement an entirely new concept in baseball was created that said, “batting averages are irrelevant, RBIs are irrelevant, and the only thing that mattered was a player’s On Base Percentage (OBP). About 15 years later Voros McCracken, a disciple of James, discovered the corollary for pitching: the only things that are actually under the pitcher’s control are strikeouts, walks and homerun balls; everything else is luck. Consequently, the Earned Run Average (ERA) is irrelevant.
Obviously any science (or cult for that matter) that produced thousands of pages of statistics and theory was going to be a bit more complex than my simple summing up in the above paragraph but I have captured the heart of Sabermetrics: Outs bad, OBP important, ERA irrelevant.
There is also one other important fact that I learned from this book: Conventional baseball wisdom was wrong. This was an epiphany for me.
Previously, if I had been hired by a computer game company to write the AI for a baseball simulation I would have written it using the complicated (and sometimes contradictory) rules of conventional baseball wisdom that I had been taught since my youth. For some time I had suspected that many of these conventional baseball rules were wrong — they had just felt wrong — but I certainly would never have jumped to the conclusions that James had. However, the results of Sabermetrics are irrefutable.
Now, what intrigues me is this: to write a computer program that crunched all the data that James did by hand is not a big programming accomplishment (indeed there’s a nice little C program at http://www.baseball1.com/bbdata/grabiner/brock2.c that will do that) rather it was the conclusion that James arrived at that interested me and I asked myself, “Is it possible to write a computer program that given the rules of baseball and the same data set that James had would arrive at a similar solution?” Of course, the next logical step if such a program was created would be to ask: Could an ‘all-purpose’ (universal, generic) version of this program be written that would:
- Load in a (game/simulation) rule set.
- Load in data files (which could include maps, statistics, etc.).
- Derive an optimum winning strategy.
I can only assume that this is not an original idea.
Internet searches for “optimum strategy reasoning software” return “agent based systems” and “game theory.”
Internet searches for “universal [strategy] reasoning software” return “case based reasoning”, “Forbus’s “Qualitative Spatial Reasoning”, “Universal Learning Machines” and “computational reasoning.”