Background The application of artificial intelligence (AI) opens an interesting perspective for
predicting injury risk and performance in team sports. A better understanding of the …

Purpose Injuries are common in sports and can have significant physical, psychological and
financial consequences. Machine learning (ML) methods could be used to improve injury …

Background To conduct a systematic review and meta-analysis of epidemiological data of
injuries in male and female youth football players. Methods Searches were performed in …

The rapid transformation of our communities and our way of life due to modern technologies
has impacted sports as well. Artificial intelligence, computational intelligence, data mining …

Purpose: To assess injury risk in elite-level youth football players based on anthropometric,
motor coordination and physical performance measures with a machine learning approach …

Background An increasing number of musculoskeletal injury prediction models are being
developed and implemented in sports medicine. Prediction model quality needs to be …

In the last decade, the number of studies about machine learning algorithms applied to
sports, eg, injury forecasting and athlete performance prediction, have rapidly increased …

We implemented a machine learning approach to investigate individual indicators of training
load and wellness that may predict the emergence or development of overuse injuries in …

Attempts to better understand the relationship between training and competition load and
injury in football are essential for helping to understand adaptation to training programmes …

Due to the chaotic nature of soccer, the predictive statistical models have become in a
current challenge to decision-making based on scientific evidence. The aim of the present …