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Machine learning in elite volleyball...

Muazu Musa, Rabiu.

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Machine learning in elite volleyball = integrating performance analysis, competition and training strategies /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Machine learning in elite volleyball/ by Rabiu Muazu Musa ... [et al.].
Reminder of title:	integrating performance analysis, competition and training strategies /
other author:	Muazu Musa, Rabiu.
Published:	Singapore :Springer Singapore : : 2021.,
Description:	x, 53 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Volleyball - Data processing. -
Online resource:	https://doi.org/10.1007/978-981-16-3192-4
ISBN:	9789811631924

Machine learning in elite volleyball = integrating performance analysis, competition and training strategies /
Machine learning in elite volleyballintegrating performance analysis, competition and training strategies /[electronic resource] :by Rabiu Muazu Musa ... [et al.]. - Singapore :Springer Singapore :2021. - x, 53 p. :ill., digital ;24 cm. - SpringerBriefs in applied sciences and technology,2191-530X. - SpringerBriefs in applied sciences and technology..

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.

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.

ISBN: 9789811631924

Standard No.: 10.1007/978-981-16-3192-4doiSubjects--Topical Terms:

3506138
Volleyball
--Data processing.

LC Class. No.: GV1015.3 / .M839 2021

Dewey Class. No.: 796.3250285

Machine learning in elite volleyball = integrating performance analysis, competition and training strategies /
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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.
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.
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