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Publicado por Springer-Nature New York Inc, 2021
ISBN 10: 9811631913 ISBN 13: 9789811631917
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Añadir al carritoPaperback. Condición: Brand New. 63 pages. 9.25x6.10x0.13 inches. In Stock.
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Publicado por Springer Nature Singapore, Springer Nature Singapore Jun 2021, 2021
ISBN 10: 9811631913 ISBN 13: 9789811631917
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Añadir al carritoTaschenbuch. Condición: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 64 pp. Englisch.
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Publicado por Springer Nature Singapore, Springer Nature Singapore, 2021
ISBN 10: 9811631913 ISBN 13: 9789811631917
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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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Añadir al carritoTaschenbuch. Condición: Neu. Machine Learning in Elite Volleyball | Integrating Performance Analysis, Competition and Training Strategies | Rabiu Muazu Musa (u. a.) | Taschenbuch | SpringerBriefs in Applied Sciences and Technology | x | Englisch | 2021 | Springer | EAN 9789811631917 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Publicado por Springer Nature Singapore Jun 2021, 2021
ISBN 10: 9811631913 ISBN 13: 9789811631917
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 64 pp. Englisch.
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Publicado por Springer, Berlin|Springer Nature Singapore|Springer, 2021
ISBN 10: 9811631913 ISBN 13: 9789811631917
Librería: moluna, Greven, Alemania
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Añadir al carritoKartoniert / Broschiert. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. It presents key performance indicators as well as human performance parameters that can be used in future evaluation of team performance and players.This brief highlights the use of various Machine Learning (ML) algorithms to evaluate training and compe.