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Review
. 2022 Aug;15(4):283-290.
doi: 10.1007/s12178-022-09763-6. Epub 2022 Apr 29.

Current State of Data and Analytics Research in Baseball

Joshua Mizels  1 , Brandon Erickson  2 , Peter Chalmers  3
Affiliations
Review

Current State of Data and Analytics Research in Baseball

Joshua Mizels et al. Curr Rev Musculoskelet Med. 2022 Aug.

Abstract

Purpose of review: Baseball has become one of the largest data-driven sports. In this review, we highlight the historical context of how big data and sabermetrics began to transform baseball, the current methods for data collection and analysis in baseball, and a look to the future including emerging technologies.

Recent findings: Machine learning (ML), artificial intelligence (AI), and modern motion-analysis techniques have shown promise in predicting player performance and preventing injury. With the advent of the Health Injury Tracking System (HITS), numerous studies have been published which highlight the epidemiology and performance implications for specific injuries. Wearable technologies allow for the prospective collection of kinematic data to improve pitching mechanics and prevent injury. Data and analytics research has transcended baseball over time, and the future of this field remains bright.

Keywords: Artificial intelligence; Baseball; Machine learning; Motion analysis; Sabermetrics.

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Conflict of interest statement

The authors declare no competing interests.

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