Graduation Year
2025
Date of Submission
12-2024
Document Type
Open Access Senior Thesis
Degree Name
Bachelor of Arts
Department
Economics
Reader 1
Brian Bullard
Rights Information
Paul F Wendler
Abstract
This paper introduces a new baseball statistic, Weighted WAR (wWAR), designed to enhance Major League Baseball (MLB) roster optimization by incorporating team-specific factors into player valuation. Traditional WAR (Wins Above Replacement) offers a generalized measure of player performance relative to the league minimum salaried player. The study bridges the gap by developing wWAR, a customizable, team-specific framework for evaluating player impact. Taking player data, team data, and salary data from 2021-2023 the study proves the significance of wWAR’s impact relative to the traditional WAR statistic using case studies and regression analysis. The results demonstrate that wWAR outperforms traditional WAR in forecasting team regular season success, particularly for small and large-market teams where payroll efficiency and strategic resource allocation are critical. The research does not undermine the value of WAR, but rather provides an alternative way to look at a player's WAR based on team specific constraints. While limitations in data availability, data manipulation, and non-quantifiable factors remain, wWAR provides a transformative tool for enhancing team performance and competitive balance in the MLB
Recommended Citation
Wendler, Paul, "Weighted WAR: A Team-Specific Approach to Optimizing MLB Rosters" (2025). CMC Senior Theses. 3817.
https://scholarship.claremont.edu/cmc_theses/3817