COMPARING BASEBALL PLAYERS ACROSS ERAS VIA NOVEL FULL HOUSE MODELING
成果类型：
Article
署名作者：
Yan, Shen; Burgos Jr, Adrian; Kinson, Christopher; Eck, Daniel J.
署名单位：
University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign
刊物名称：
ANNALS OF APPLIED STATISTICS
ISSN/ISSBN：
1932-6157
DOI：
10.1214/24-AOAS1992
发表日期：
2025
页码：
1778-1799
关键词：
摘要：
A new methodological framework suitable for era-adjusting baseball statistics is developed in this article. Within this methodological framework specific models are motivated. We call these models Full House Models. Full House Models work by balancing the achievements of Major League Baseball (MLB) players within a given season and the size of the MLB talent pool from which a player came. We demonstrate the utility of Full House Models in an application of comparing baseball players' performance statistics across eras. Our results reveal a new ranking of baseball's greatest players which include several modern players among the top all-time players. Modern players are elevated by Full House Modeling because they come from a larger talent pool. We present sensitivity and multiverse analyses to examine how changes in modeling inputs, including the estimate of the talent pool, affect the results.
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