|
|
|
|
| LEADER |
02885nmm a2200361 u 4500 |
| 001 |
EB001994239 |
| 003 |
EBX01000000000000001157141 |
| 005 |
00000000000000.0 |
| 007 |
cr||||||||||||||||||||| |
| 008 |
210702 ||| eng |
| 020 |
|
|
|a 9789811631924
|
| 100 |
1 |
|
|a Muazu Musa, Rabiu
|
| 245 |
0 |
0 |
|a Machine Learning in Elite Volleyball
|h Elektronische Ressource
|b Integrating Performance Analysis, Competition and Training Strategies
|c by Rabiu Muazu Musa, Anwar P. P. Abdul Majeed, Muhammad Zuhaili Suhaimi, Mohd Azraai Mohd Razman, Mohamad Razali Abdullah, Noor Azuan Abu Osman
|
| 250 |
|
|
|a 1st ed. 2021
|
| 260 |
|
|
|a Singapore
|b Springer Nature Singapore
|c 2021, 2021
|
| 300 |
|
|
|a X, 53 p. 13 illus., 12 illus. in color
|b online resource
|
| 505 |
0 |
|
|a Chapter 1. Nature of Volleyball Sport, Performance Analysis in Volleyball, and the Recent Advances of Machine Learning Application in Sports -- Chapter 2. The Effect of Competition strategies in influencing Volleyball performance -- Chapter 3. Identification of psychological training strategies essential for Volleyball performance -- Chapter 4. The Strategic competitional elements contributing to Volleyball performance -- Chapter 5. Anthropometric variables in the identification of high-performance Volleyball players -- Chapter 6. Performance Indicators predicting medalists and non-medalists in elite men Volleyball competition -- Chapter 7. Summary, Conclusion and Future Direction
|
| 653 |
|
|
|a Machine learning
|
| 653 |
|
|
|a Sports sciences
|
| 653 |
|
|
|a Machine Learning
|
| 653 |
|
|
|a Computational intelligence
|
| 653 |
|
|
|a Computational Intelligence
|
| 653 |
|
|
|a Sport Science
|
| 700 |
1 |
|
|a Abdul Majeed, Anwar P. P.
|e [author]
|
| 700 |
1 |
|
|a Suhaimi, Muhammad Zuhaili
|e [author]
|
| 700 |
1 |
|
|a Mohd Razman, Mohd Azraai
|e [author]
|
| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
|
| 989 |
|
|
|b Springer
|a Springer eBooks 2005-
|
| 490 |
0 |
|
|a SpringerBriefs in Applied Sciences and Technology
|
| 028 |
5 |
0 |
|a 10.1007/978-981-16-3192-4
|
| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-981-16-3192-4?nosfx=y
|x Verlag
|3 Volltext
|
| 082 |
0 |
|
|a 006.31
|
| 520 |
|
|
|a 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
|