Hip Muscle Strength Ratios Predicting Groin Injury in Male Soccer Players Using Machine Learning and Multivariate Analysis—A Prospective Cohort Study

Abstract

Despite ongoing efforts, the relationship between groin strength and injury remains unclear. The challenge of accurately predicting injuries presents an opportunity for researchers to develop prevention strategies to reduce the occurrence of such injuries. Consequently, this issue requires further investigation to obtain insights into effective mitigation strategies. In 120 male soccer players, the maximum isometric strength of the hip muscle groups was measured, and the strength ratios were calculated. Previous injury and anthropometric data were registered. Injury data were collected following the FIFA/UEFA consensus. k-nearest neighbor (k-NN) was used to predict the incidence of injury, while the significant predictive variables of the k-NN algorithm were fitted into a multivariate logistic regression model (LR) to analyze the likelihood of players sustaining a groin injury. The LR model determined two variables as significant predictors of groin injury. Players were less likely to sustain a groin injury by 76% for each decrease of the adductor/abductor isometric strength ratio in the non-dominant limb (OR = 0.238, CI 95% = [(0.098–0.572]). Players with a history of previous injury had a 67% greater risk of sustaining an injury (OR = 0.333, CI 95% = [(0.1068–1.038]). Isometric hip adductor and abductor strength imbalances of the non-dominant lower limb and a history of previous injury were risk factors for groin injury in soccer players.

Keywords

• hip muscle strength ratios
• machine learning
• injury prediction
• soccer
• handheld dynamometer
• groin injury