Suggesting pitches in Major League Baseball

Date

2020-03-26

Authors

Palomares, Javier, Jr.

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Abstract

Pitchers in Major League Baseball need to keep batters from anticipating the next pitch. They do this by selecting a good pitch type and zone to throw. Pitchers often make this selection haphazardly. In this paper, we present a machine learning model using the data from the PITCHf/x system installed in Major League stadiums to first predict good and bad pitches, and then to suggest the following pitch type to throw that will result in good outcomes

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