Performance Perspectives Blog

Moneyball & performance measurement

by | Jun 10, 2009

This morning Patrick Fowler and I arrived in beautiful (though wet) Stockholm, Sweden for the Spring meeting of the European chapter of the Performance Measurement Forum. This site marks the fourth Scandinavian country we’ve held meetings in (previous ones were in Norway, Denmark, and Finland). I brought along a variety of books to read including Michael Lewis’ bestseller, Moneyball. I had read Liar’s Poker, which I enjoyed immensely, as well as his most recent offering, Panic: The Story of Modern Financial Insanity. Moneyball had been recommended by several colleagues, and I finally decided it was time to read it. Little did I know that it would provide me with references to exploit in my writing and teaching.

Early in the book Lewis describes the baseball player draft and explains that planning meetings are “all about minimizing risk,” (page 27) a topic near and dear to many of us in the investment world. But there’s much more to borrow from this text.

What the book is essentially about is a totally new way to evaluate the performance of baseball players, from hitters to fielders to pitchers. Rather than rely on the traditional statistics (such as batting average), alternative ones are proposed (such as on-base percentage). He suggests that you shouldn’t “believe a thing is true just because some famous baseball player says its true.” (page 98) Made me think of our long-standing affinity for calculations such as time-weighted return and standard deviation. Those of us who have recognized the superiority of money-weighted returns have had, at times, a difficult time convincing others that it’s better because of the universal acceptance of time-weighting, though we are making progress. He cites one baseball statistician who opined that “the world needs another offensive rating system like Custer needed more Indians.” (page 80) I’m sure that this is the reaction many have to some of the new ideas that have been proposed. But at the end of the day one should ask “is the new measure better?”

Not surprising, Lewis provides some history on the origin of baseball statistics and credits Henry Chadwick who first developed some in the mid 19th century. “Chadwick was better at popularizing baseball statistics than he was at thinking through their meaning.” (page 70) I will allow you to reflect on individuals in the world of performance measurement who might also be worthy of such a characterization. And while Lewis’ suggestion that Chadwick “created the greatest accounting scandal in professional sports” (page 71) might seem a bit strong, I suspect that this statement, too, might apply to some in our industry. (If you’re unconvinced about this, I suggest you read Taleb’s The Black Swan)

Lewis points out that “there had been fitful efforts to rethink old prejudices” (page 71), which clearly applies to our industry as well. The old ways die hard. But, those of us who have seen the light will continue to press on, even if we have to turn to baseball for help!

Hopefully THIS forum will further foster the advancement of new ideas and approaches.