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.
| Autorius: | Rabiu Muazu Musa, Anwar P. P. Abdul Majeed, Noor Azuan Abu Osman, Mohd Azraai Mohd Razman, Mohamad Razali Abdullah, Muhammad Zuhaili Suhaimi, |
| Serija: | SpringerBriefs in Applied Sciences and Technology |
| Leidėjas: | Springer Nature Singapore |
| Išleidimo metai: | 2021 |
| Knygos puslapių skaičius: | 64 |
| ISBN-10: | 9811631913 |
| ISBN-13: | 9789811631917 |
| Formatas: | Knyga minkštu viršeliu |
| Kalba: | Anglų |
| Žanras: | Machine learning |
Parašykite atsiliepimą apie „Machine Learning in Elite Volleyball: Integrating Performance Analysis, Competition and Training Strategies“
