Michael Lewis’ 2003 book “Moneyball,” a profile of Billy Beane, the exceptionally successful general manager of the Oakland A’s, was almost immediately read as an economic parable with implications far beyond baseball. In telling Beane’s story, Lewis showed the possibilities of a quantitative approach to running an organization just as the term “big data” was coming into vogue as well as the deep institutional resistance to such management.
Christopher Phillips takes Lewis’ opposition between scouts and statheads as the starting point for his book “Scouting and Scoring: How We Know What We Know About Baseball,” which the Carnegie Mellon University history professor discussed on this week’s Drinks With The Deal podcast. Like Lewis, Phillips used baseball as a way of examining how organizations create and use data.
Statistics were an integral part of baseball from the time the sport was invented, Phillips said, but they took on greater importance in the major leagues with the advent of free agency in 1976, which made valuing players a far more important exercise for team management.
But statistics have their limitations, which is why major league teams continue to scout amateur players, as Phillips discussed. That scouting hasn’t improved much over the last generation; only about two-thirds of the first-round draft picks in baseball’s amateur draft make it to the majors. Even in a sport dominate by numbers, talent evaluation remains an impressionistic, uncertain exercise.
Here’s the podcast: