The Sabermetric Revolution: Assessing the Growth of Analytics in Baseball

5. The Moneyball Diaspora

5 The Moneyball Diaspora Baseball was the first professional team sport in the United States. It was also the first sport to introduce collective bargaining and free agency in the players’ market. And, it was the first sport to spawn the use of critical analytics to assess player performance and game and franchise business strategy. The other team sports have always followed baseball, and the case with analytics is no different. Baseball, of course, lends itself to the use of statistical analysis to evaluate player performance, among other reasons, because it is easier to isolate the productivity of individual players in baseball.1 This is true both because the success of a player depends directly on the actions of only one or two opposing players, and because there are a limited number of discrete outcomes from a play in baseball (as well as discrete possibilities leading up to a play). Hockey, basketball, soccer, and football plays are more interdependent and more continuous, and measurement of individual performance productivity is confounded by a host of complications. Nonetheless, especially after the publication of Moneyball, the development of analytics in other team sports has accelerated. Interestingly, unlike in baseball, analytics practitioners in the other sports emerged roughly at the same time as the interest in analytics surfaced in team front offices. In baseball, the hobby of sabermetrics surfaced decades before the profession of sabermetrics. Thus, from the 1970s (or earlier) a growing group of intellectually curious stat heads began communicating with each other, trying to parse the myths and mysteries of the game. Later, in the 1990s, following the lead of 86 Chapter 5 Sandy Alderson, Larry Lucchino, Dan Duquette, and others, the avocation of sabermetrics became the vocation of sabermetrics. This succession in baseball meant that the first two decades of dialogue and insights occurred in broad daylight, in the public domain. In contrast, basketball and football analytics was quickly absorbed in the teams’ front offices , and much of the statistical work in these sports has proceeded as proprietary , in the realm of commercial secrets. Another obstacle has confronted statistical analysis in basketball and football. The best measure of performance is not total output, but total output per number of attempts, or efficiency. In baseball, measuring runs (or some other output) per inning is straightforward. In basketball or football, measuring points per possession is less so. In part this is because offense and defense can run together; that is, the ball can move in both directions on the same play. According to some basketball metricians, settling on a consistent definition of a possession is necessary before a reliable measure of efficiency can be developed. So, for instance, if we want to determine the value of taking a shot in basketball, we must know both the number of points a successfully executed shot brings and the cost of either making or missing the shot (one leads to a change in possession and the other may lead to a change in possession). To know this, we must estimate the value of a possession—that is, how many points result from an average possession. But to know this, we first have to know how many possessions a team has in a game. This number is connected to the pace of the game and it is not as easy to quantify as one might imagine. Let us assume that we can measure the number of possessions and that the average possession yields one point to the offensive team. In this case, when a player sinks a three-point shot, the shot gives the other team possession and, hence, one point on average. So, the expected net value of the three-point conversion is two points. (This observation is mitigated by the existence of the shot clock in professional basketball which mandates that the ball will change possession every twenty-four seconds, whether or not a shot is taken and/or made. Thus, a three-point shot at or near the buzzer does not really cause a change in possession.2 Although there is no possession clock in football, football shares the characteristic with basketball that a score The Moneyball Diaspora 87 necessarily leads to a change in possession.) A similar netting out procedure would not have to be performed for a hit (or run) in baseball, because the hit (or run) does not bring that inning closer to an end. It would, however, have...