Machine Learning in Elite Volleyball

Integrating Performance Analysis, Competition and Training Strategies

Mohd Azraai Mohd Razman, Anwar P. P. Abdul Majeed, Rabiu Muazu Musa, et al.

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Springer Singapore img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Informatik

Beschreibung

This brief highlights the use of various Machine Learning (ML) algorithms to evaluate training and competitional strategies in Volleyball, as well as to identify high-performance players in the sport. Several psychological elements/strategies coupled with human performance parameters are discussed in view to ascertain their impact on performance in elite Volleyball competitions. It presents key performance indicators as well as human performance parameters that can be used in future evaluation of team performance and players. The details outlined in this brief are vital to coaches, club managers, talent identification experts, performance analysts as well as other important stakeholders in the evaluation of performance and to foster improvement in this sport.

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Schlagwörter

Psychological training, Elite Volleyball players, Anthropometric variables, Sport performance indicators, Volleyball training, High-performance players, Volleyball performance