Document Type : Research Paper
Authors
1
Department of Sport injury and biomechanics, Faculty of Sport Scienses and Health, Alborz Campus, University of Tehran, Tehran, Iran.
2
Professor of the Department of Sports Injury and Biomechanics, Faculty of Sport Sciences and Health, University of Tehran, Tehran, Iran
3
Professor of Sports Physiology Department, Faculty Sports Sciences Health, University of Tehran ,Tehran, Iran
4
Professor at the Faculty of Sports Sciences, University of Extremadura, Spain
10.22084/rsr.2023.28033.1701
Abstract
Background and aim: Elite soccer players endure significant physical pressures during training and competition to reach their highest performance level. These pressures consist of internal and external loads, each of which can contribute to injuries and a decrease in the athlete's performance. Therefore, this study aims to investigate the possibility of predicting injuries in elite football players associated with internal and external training loads and competition.
Materials and Method: This study is a prospective, descriptive cohort study. Data related to 41 players active in the Iranian Premier League in the 1400-1401 season were gathered in a targeted and accessible manner. Data on internal load was collected through the perceived pressure scale, and data on external load was collected by registering data through GPS technology. Logistic regression was used to predict the occurrence of injuries using statistical methods.
Results: The results in the final prediction model of injury showed that the variables of maximum speed, total distance, duration, acceleration zone 3, deceleration in zone 1, and work rate intervals could predict injury (p<0.05). However, variables such as average speed, deceleration in zone 3, sprint repeated, sprint maximum acceleration, and RPE cannot predict injury (p>0.05).
Conclusion: Based on the findings of this study, it can be concluded that predicting injuries in football players should not rely on a single factor. Instead, various aspects of injury occurrences should be considered, such as maximum speed, total distance, acceleration increase and decrease, and workload volume during training and competition.
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