- Presenter
- Date
- Thursday 10 Dec 2020, 16:00 - 17:00
- Type
- Seminar
- Location
Online (ZOOM)
- Ticket information
Please contact principe@ese.eur.nl for the link to this seminar.
Moneyball (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, notably walks, singles, doubles, triples and home runs. Using a dataset of every event in every game from 1994 to 2015, we show that the 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 contributions of each player, regardless of the source of those contributions (walks, singles, doubles and home runs). We find this was true both before and after the publication of Moneyball, suggesting that the labor market for free agent batters in Major League Baseball operated efficiently with respect to run value contributions across our entire sample period.
- More information
The ECASE team
Jan van Ours, Thomas Peeters, Stefan Szymanski, Francesco Principe and Sam Hoey- Related links
- Erasmus Centre for Applied Sports Economics