The aim of this study was to investigate whether volleyball-specific skills, physical performance, and general cognitive functions differ between players of different competitive levels. Twenty-six female volleyball players competing at 2 different levels were tested on volleyball-specific skills (accuracy and technique of setting, passing, spiking, and serving), change of direction speed (COD) by the modified T-test, countermovement jump (CMJ) and general cognitive functions (executive control by Flanker task and perceptual speed by visual search task). Four machine learningmodels were tested to detect the best one to predict players’ level. Regional players presented higher passing, spiking, serving accuracy and setting, passing, spiking, and serving technique than provincial players. Regional players had also better performance in COD and CMJ than provincial players. Regional players presented lower response time than provincial players in both congruent and incongruent conditions of the Flanker task, and in both 10 items and 15 items conditions of the visual search task. Decision tree classifier was the machine learning model with the highest performance to discriminate regional and provincial players (93% precision and 73% recall) by considering passing technique, congruent and incongruent condition of the Flanker task, 15 items and 10 items condition of the visual search task, and spiking technique. These findings demonstrated the importance of assessing volleyball-specific skills and cognitive functions as playing a role to discriminate players of different competitive levels.