Recent measurement technologies enable us to analyze baseball at higher levels of complexity. There are, however, still many unclear points around pitching strategy. There are two elements that make it difficult to measure the effect of a pitching strategy. First, most public datasets do not include location data where the catcher demands a ball, which is essential information to obtain the battery’s intent. Second, there are many confounders associated with pitching/batting results when evaluating pitching strategy. We here clarify the effect of pitching attempts to a specific location, e.g., inside or outside. We employ a causal inference framework called stratified analysis using a propensity score to evaluate the effects while removing the effect of confounding factors. We use a pitch-by-pitch dataset of Japanese professional baseball games held in 2014–2019, which includes location data where the catcher demands a ball. The results reveal that an outside pitching attempt is more effective than an inside one to minimize allowed run average. In addition, the stratified analysis shows that the outside pitching attempt is effective regardless of the magnitude of the estimated batter’s ability, and the proportion of pitched inside for pitcher/batter. Our analysis provides practical insights into selecting a pitching strategy to minimize allowed runs.

中文翻译：

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使用倾向得分通过分层分析评估投球策略

最近的测量技术使我们能够以更高的复杂度分析棒球。然而，围绕投球策略仍有许多不清楚的地方。有两个因素使衡量投球策略的效果变得困难。首先，大多数公共数据集不包括接球手需要球的位置数据，而这是获得电池意图的基本信息。其次，在评估投球策略时，有许多与投球/击球结果相关的混杂因素。我们在这里阐明了向特定位置（例如内部或外部）投球尝试的效果。我们采用称为分层分析的因果推理框架，使用倾向得分来评估效果，同时消除混杂因素的影响。我们使用 2014-2019 年举行的日本职业棒球比赛的逐场数据集，其中包括接球手要求球的位置数据。结果表明，外线投球尝试比内线投球更有效，可以最大限度地减少允许的平均得分。此外，分层分析表明，无论估计击球手的能力大小以及投手/击球手的内投比例如何，外线投球尝试都是有效的。我们的分析提供了有关选择投球策略以尽量减少允许跑动的实用见解。分层分析表明，无论估计击球手的能力大小以及投手/击球手的内投比例如何，外线投球尝试都是有效的。我们的分析提供了有关选择投球策略以尽量减少允许跑动的实用见解。分层分析表明，无论估计击球手的能力大小以及投手/击球手的内投比例如何，外线投球尝试都是有效的。我们的分析提供了有关选择投球策略以尽量减少允许跑动的实用见解。