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arXiv · 1304.1756

Trouble With The Curve: Improving MLB Pitch Classification

Michael A. Pane·Samuel L. Ventura·Rebecca C. Steorts·A. C. Thomas
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Abstract

The PITCHf/x database has allowed the statistical analysis of of Major League Baseball (MLB) to flourish since its introduction in late 2006. Using PITCHf/x, pitches have been classified by hand, requiring considerable effort, or using neural network clustering and classification, which is often difficult to interpret. To address these issues, we use model-based clustering with a multivariate Gaussian mixture model and an appropriate adjustment factor as an alternative to current methods. Furthermore, we describe a new pitch classification algorithm based on our clustering approach to address the problems of pitch misclassification. We illustrate our methods for various pitchers from the PITCHf/x database that covers a wide variety of pitch types.

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Michael A. Pane, Samuel L. Ventura, Rebecca C. Steorts, A. C. Thomas. 2013-04-05. Trouble With The Curve: Improving MLB Pitch Classification. https://arxiv.org/abs/1304.1756

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