Machine Learning Outperforms Regression Analysis to Predict Next-Season Major League Baseball Player Injuries: Epidemiology and Validation of 13,982 Player-Years From Performance and Injury Profile Trends, 2000-2017

BACKGROUND: Machine learning (ML) allows for the development of a predictive algorithm capable of imbibing historical data on a Major League Baseball (MLB) player to accurately project the player's future availability. PURPOSE: To determine the validity of an ML model in predicting the next-sea...

Descripción completa

Detalles Bibliográficos
Autores principales: Karnuta, Jaret M., Luu, Bryan C., Haeberle, Heather S., Saluan, Paul M., Frangiamore, Salvatore J., Stearns, Kim L., Farrow, Lutul D., Nwachukwu, Benedict U., Verma, Nikhil N., Makhni, Eric C., Schickendantz, Mark S., Ramkumar, Prem N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7672741/
https://www.ncbi.nlm.nih.gov/pubmed/33241060
http://dx.doi.org/10.1177/2325967120963046

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7672741/
https://www.ncbi.nlm.nih.gov/pubmed/33241060
http://dx.doi.org/10.1177/2325967120963046

Ejemplares similares