A1011
Title: Comparing baseball players across eras via the novel full house model
Authors: Daniel Eck - University of Illinois (United States) [presenting]
Abstract: A new methodological framework for era-adjusting baseball statistics is motivated. The proposed methodology is a crystallization of the conceptual ideas put forward by Stephen Jay Gould. This methodology is named the Full House Model in his honour. The Full House Model works by balancing the achievements of Major League Baseball (MLB) players within a given season and the size of the MLB-eligible population. The utility of the Full House Model in an application of comparing baseball players' performance statistics across eras is demonstrated. The results reveal a radical reranking of baseball's greatest players that is consistent with what one would expect under a sensible uniform talent generation assumption. Most importantly, it is found that the greatest modern players, including several African American, Latino, and Asian players, now sit atop the greatest all-time lists of historical baseball players, while conventional wisdom ranks such players lower. The conclusions largely refute a consensus of baseball greatness that is reinforced by nostalgic bias, recorded statistics, and statistical methodologies, which it is argued are not suited to the task of comparing players across eras.