Machine Learning in Elite Volleyball Integrating Performance Analysis, Competition and Training Strategies
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 i...
| Main Authors: | , , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Singapore
Springer Nature Singapore
2021, 2021
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| Edition: | 1st ed. 2021 |
| Series: | SpringerBriefs in Applied Sciences and Technology
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
| Summary: | 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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| Physical Description: | X, 53 p. 13 illus., 12 illus. in color online resource |
| ISBN: | 9789811631924 |