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.

翻译：棒球统计数据“Wins Above Replacement”（WAR）已成为最流行的评估指标之一。但该指标并非直接观测和汇总得出：WAR是对一个定义模糊的模型中某个参数的估计值，附带着模型的所有假设。FanGraphs和Baseball Reference等业界标准模型均假设赛季平均数据足以概括投手表现。这一数学基础存在诸多缺陷，尤其因为WAR不应与任何计数统计量呈线性关系。为修补这一缺陷及其他问题，我们提出新度量“网格WAR”（Grid WAR），该指标可基于单场比赛准确估算先发投手的WAR值。网格WAR的凸性降低了“崩盘局”的影响，同时提升了极端出色比赛的价值，从而对桑迪·库法克斯、怀蒂·福特和猫鱼·亨特等表现出显著单场波动性的投手给出更高估值。网格WAR旨在精准衡量历史表现，同时具备预测价值——投手的网格WAR对未来表现的预测能力优于传统WAR。最后，我们在https://gridwar.xyz 部署了Shiny应用，展示自1952年以来每场MLB比赛的网格WAR结果（含职业生涯、赛季及单场数据），该应用每日清晨自动更新。