THE RELATIONSHIP BETWEEN STRENGTH CAPACITY AND MOTOR PERFORMANCE IN THE GYMNASTIC HANDSTAND: A MACHINE LEARNING STUDY

Abstract

The present study investigated the relationship between strength capacity and motor performance in the gymnastic handstand. The hypothesis stipulated a positive relationship between motor performance and strength capacity levels. Thirty-two university students, 16 female and 16 male (24.03 ± 4.74 years of age,) participated in the study. The handstand was assessed using the absolute error of the three angles produced by the model (video) and the three angles produced by the performer. We conducted four strength tests: explosive force, maximum right-hand grip strength, maximum left-hand grip strength, and resistance force. The machine learning model was trained using 10 of the folds and cross-validated, and a linear regression test was performed using motor performance (absolute error) and strength tests (explosive force, maximum force right-hand, maximum force left-hand, and resistance force). The results showed that the machine learning model indicated a low relationship between strength capacity and motor performance. Additionally, motor performance was not found to be related to strength capacity. The results may indicate that specific capacities and the interaction of factors such as task specificity, environment, and individual characteristics influence motor performance.