Introducing Grid WAR: Rethinking WAR for Starting Pitchers

TL;DR

This paper introduces Grid WAR, a new per-game metric for evaluating starting pitchers that addresses limitations of traditional WAR by accounting for game-by-game variance and exceptional performances.

Contribution

We develop Grid WAR, a mathematically sound, convex measure that improves past performance estimation and enhances predictive accuracy for starting pitchers.

Findings

Grid WAR better predicts future performance than traditional WAR.

Grid WAR reduces impact of blow-up games and emphasizes exceptional games.

The online platform displays comprehensive Grid WAR data since 1952.

Abstract

The baseball statistic "Wins Above Replacement" (WAR) has emerged as one of the most popular evaluation metrics. But it is not readily observed and tabulated; WAR is an estimate of a parameter in a vaguely defined model with all its attendant assumptions. Industry-standard models of WAR for starting pitchers from FanGraphs and Baseball Reference all assume that season-long averages are sufficient statistics for a pitcher's performance. This provides an invalid mathematical foundation for many reasons, especially because WAR should not be linear with respect to any counting statistic. To repair this defect, as well as many others, we devise a new measure, Grid WAR, which accurately estimates a starting pitcher's WAR on a per-game basis. The convexity of Grid WAR diminishes the impact of "blow-up" games and upweights exceptional games, raising the valuation of pitchers like Sandy Koufax, Whitey Ford, and Catfish Hunter who exhibit fundamental game-by-game variance. Grid WAR is designed to accurately measure past performance, but also has predictive value insofar as a pitcher's Grid WAR is better than WAR at predicting future performance. Finally, at https://gridwar.xyz we host a Shiny app which displays the Grid WAR results of each MLB game since 1952, including career, season, and game level results, which updates automatically every morning.