The Prediction of Batting Averages in Major League Baseball

The Prediction of Batting Averages in Major League Baseball

The prediction of yearly batting averages in Major League Baseball is a notoriously difficult problem where standard errors using the well-known PECOTA (Player Empirical Comparison and Optimization Test Algorithm) system are roughly 20 points. This paper considers the use of ball-by-ball data provid...

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Bibliographic Details
Main Authors: Sarah R. Bailey, Jason Loeppky, Tim B. Swartz
Format: Article
Language:English
Published: MDPI AG 2020-04-01
Series:Stats
Subjects:
big data
forecasting
logistic regression
PECOTA
Statcast
Online Access:https://www.mdpi.com/2571-905X/3/2/8

Internet

https://www.mdpi.com/2571-905X/3/2/8

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