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 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 …

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 …

Objectives The purpose of this study was to examine whether the use of machine learning
improved the ability of a neuromuscular screen to identify injury risk factors in elite male …

The search for monitoring tools that provide early indication of injury and illness could
contribute to better player protection. The aim of the present study was to i) determine the …

This narrative review paper aimed to discuss the literature on machine learning applications
in soccer with an emphasis on injury risk assessment. A secondary aim was to provide …

Introduction Hamstring muscle injuries (HMI) continue to plague professional football.
Several scientific publications have encouraged a multifactorial approach; however, no …

The objectives of the study were to examine the incident rate (IR), characteristics, and
mechanisms of muscle injuries of 121 men amateur soccer players that voluntarily …