Guglielmo Pillitteri, Luca Petrigna, Salvatore Ficarra, Valerio Giustino, Ewan Thomas, Alessio Rossi, Filipe Manuel Clemente, Antonio Paoli, Marco Petrucci, Marianna Bellafiore, Antonio Palma, Giuseppe Battaglia
This study verified the relationship between internal load (IL) and external load (EL) and their association on injury risk (IR) prediction considering machine learning (ML) approaches. Studies were included if: (1) participants were male professional soccer players; (2) carried out for at least 2 sessions, exercises, or competitions; (3) correlated training load (TL) with non-contact injuries; (4) applied ML approaches to predict TL and non-contact injuries. TL included: IL indicators (Rating of Perceived Exertion, RPE; Session-RPE, Heart Rate, HR) and EL indicators (Global Positioning System, GPS variables); the relationship between EL and IL through index, ratio, formula; ML indicators included performance measures, predictive performance of ML methods, measure of feature importance, relevant predictors, outcome variable, predictor variable, data pre-processing, features selection, ML methods...
December 26, 2023: Research in Sports Medicine