Machine Learning in Elite Volleyball - Integrating Performance Analysis, Competition and Training Strategies (Paperback, 1st ed. 2021)

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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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Product Description

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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Product Details

General

Imprint

Springer Verlag, Singapore

Country of origin

Singapore

Series

SpringerBriefs in Applied Sciences and Technology

Release date

June 2021

Availability

Expected to ship within 10 - 15 working days

First published

2021

Authors

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Dimensions

235 x 155mm (L x W)

Format

Paperback

Pages

53

Edition

1st ed. 2021

ISBN-13

978-981-16-3191-7

Barcode

9789811631917

Categories

LSN

981-16-3191-3



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