Moneyball (
Lewis, 2003) claimed that data analytics enabled savvy operators to exploit inefficiencies in the market for baseball players. The economic analysis of
Hakes and Sauer (2006) appeared to show that the publication of Moneyball represented a watershed, after which inefficiencies had been competed away. In both cases analysis focused on composite statistics such as on base percentage (OBP) and slugging percentage (SLG). This paper relies on a more structural approach, associated with the statistical analysis of
Lindsey (1963) which identifies the run value of each individual event in a game. Using a dataset of every event in every game from 1996 to 2015, we show that run value of each event can be accurately calculated, as can the run value contribution of each player. We show that the compensation of free agents reliably reflects the run value contribution of each player, regardless of the source of those contributions (walks, singles, and home runs). We find this was true both before and after the publication of Moneyball, suggesting that the labor market for batters in Major League Baseball operated efficiently across our entire sample period.
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