Quantifying Consistency: Developing New Metrics for MLB Player Valuation

Abstract

This study investigates how performance consistency during a player’s pre-arbitration years in Major League Baseball (MLB) influences their first-year arbitration salary, offering novel insights for player valuation. Consistency is quantified based on three categories: short-term volatility, in-season adaptability, and environmental consistency (home/away performance). Statistical models, including both OLS and Lasso regressions and Random Forests, show that consistency metrics hold statistically significant explanatory power even when controlling for traditional performance metrics, previous salary, and league conditions. The results also indicate that away performance holds significantly more weight than home performance when determining salary value. These findings suggest that while teams heavily consider known metrics, they also implicitly or explicitly recognize the potential of consistency as a signal of future success. This study contributes to the field by introducing quantifiable consistency measures to highlight a previously under-examined aspect of MLB player value.