Literature DB >> 35486325

Current State of Data and Analytics Research in Baseball.

Joshua Mizels1, Brandon Erickson2, Peter Chalmers3.   

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.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

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

Year:  2022        PMID: 35486325      PMCID: PMC9276858          DOI: 10.1007/s12178-022-09763-6

Source DB:  PubMed          Journal:  Curr Rev Musculoskelet Med        ISSN: 1935-9748


  36 in total

Review 1.  Machine Learning and Artificial Intelligence: Definitions, Applications, and Future Directions.

Authors:  J Matthew Helm; Andrew M Swiergosz; Heather S Haeberle; Jaret M Karnuta; Jonathan L Schaffer; Viktor E Krebs; Andrew I Spitzer; Prem N Ramkumar
Journal:  Curr Rev Musculoskelet Med       Date:  2020-02

2.  Performance and Return to Sport After Latissimus Dorsi and Teres Major Tears Among Professional Baseball Pitchers.

Authors:  Brandon J Erickson; Peter N Chalmers; John D'Angelo; Kevin Ma; Anthony A Romeo
Journal:  Am J Sports Med       Date:  2019-03-21       Impact factor: 6.202

Review 3.  A Clinician's Guide to Analysis of the Pitching Motion.

Authors:  Daniel J Christoffer; Heath P Melugin; Chad E Cherny
Journal:  Curr Rev Musculoskelet Med       Date:  2019-06

Review 4.  Artificial Intelligence for the Orthopaedic Surgeon: An Overview of Potential Benefits, Limitations, and Clinical Applications.

Authors:  Eric C Makhni; Sonya Makhni; Prem N Ramkumar
Journal:  J Am Acad Orthop Surg       Date:  2021-03-15       Impact factor: 3.020

5.  A Novel Risk Calculator Predicts 90-Day Readmission Following Total Joint Arthroplasty.

Authors:  Daniel E Goltz; Sean P Ryan; Thomas J Hopkins; Claire B Howell; David E Attarian; Michael P Bolognesi; Thorsten M Seyler
Journal:  J Bone Joint Surg Am       Date:  2019-03-20       Impact factor: 5.284

6.  Epidemiology of Major League Baseball injuries.

Authors:  Matthew Posner; Kenneth L Cameron; Jennifer Moriatis Wolf; Philip J Belmont; Brett D Owens
Journal:  Am J Sports Med       Date:  2011-06-27       Impact factor: 6.202

7.  Epidemiology of Spine-Related Neurologic Injuries in Professional Baseball Players.

Authors:  Melvin C Makhni; Frank C Curriero; Caleb M Yeung; Eric Leung; Anton Kvit; Tom Mroz; Christopher S Ahmad; Ronald A Lehman
Journal:  Spine (Phila Pa 1976)       Date:  2022-03-15       Impact factor: 3.468

8.  Analysis of Non-Game Injuries in Major League Baseball.

Authors:  Amanda Esquivel; Michael T Freehill; Frank C Curriero; Kevin L Rand; Stan Conte; Thomas Tedeschi; Stephen E Lemos
Journal:  Orthop J Sports Med       Date:  2019-12-27

9.  Combining Radar and Optical Sensor Data to Measure Player Value in Baseball.

Authors:  Glenn Healey
Journal:  Sensors (Basel)       Date:  2020-12-24       Impact factor: 3.576

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