Preprint / Version 1

Which GPS variables can predict non-contact injuries in soccer players?

A systematic review


  • Dimitrios Angelidis



football, football injuries, GPS, GPS variables, injuries prediction, non-contact injuries, soccer, soccer injuries


Background: Non-contact injuries in soccer is a big concern for soccer clubs and Global
Positioning System (GPS) has recently been used to predict them. This review is aiming to
find out which GPS variables can potentially predict non-contact injuries in soccer players.
Methods: PubMed and Google Scholar were chosen to find observational studies. Inclusion
criteria included: soccer players and GPS usage. Total distance, high-speed running, total
load, accelerations, decelerations, new body load, meters per minute, and sprinting were
the identified GPS variables. Risk Ratio (RR) and Odds Ratio (OR) outcomes were computed
for the most addressed variables in the studies, high-speed running and total distance, for
determining the probability of the variables to predict non-contact injuries. A modified
version of the Downs and Black were used to assess the methodological quality.
Results: All variables were predictors of non-contact injuries. High-speed running (RR=1.48,
OR=5.58) and total distance (RR=1.64, OR=16.3) were the best predictors variables for noncontact injuries, with total load, accelerations, decelerations, new body load, meters per
minute and sprinting to have positive predictions, but they were presented in fewer than
two articles, and as a result, no computation of the RR and OR was done.
Limitations: They were few articles for soccer athletes, and many of these articles did not
use a GPS system or did not present relevant outcomes.
Conclusion: High-speed running and total distance variables were the most addressed noncontact injuries predictors, being present in the most articles. There was a poverty of articles
regarding soccer players and the use of the GPS system, posing major limitations. Findings
can give a better understanding to practitioners about the variables that can potentially
predict injuries and consequently try to aid the athletes to minimize injury risk.