Comparing baseball players across eras via novel Full House Modeling

TL;DR

This paper introduces Full House Models, a new framework for era-adjusting baseball statistics that accounts for talent pool size, enabling more accurate cross-era player comparisons and revealing modern players among the greatest of all time.

Contribution

The paper develops and demonstrates Full House Models, a novel approach for adjusting baseball statistics across eras by considering talent pool size, improving player ranking accuracy.

Findings

Modern players rank higher due to larger talent pools.

Full House Models produce a revised all-time player ranking.

Sensitivity analyses show results depend on talent pool estimates.

Abstract

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. Sensitivity and multiverse analyses which investigate the how results change with changes to modeling inputs including the estimate of the talent pool are presented.