Machine Learning in Team Sports - Performance Analysis and Talent Identification in Beach Soccer & Sepak-takraw (Paperback, 1st ed. 2020)

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This brief highlights the application of performance analysis tools in data acquisition, and various machine learning algorithms for evaluating team performance as well as talent identification in beach soccer and sepak takraw. Numerous performance indicators and human performance parameters are considered based on their relevance to each sport. The findings presented here demonstrate that the key performance indicators as well as human performance parameters can be used in the future evaluation of team performance as well as talent identification in these sports. Accordingly, they offer a valuable resource for coaches, club managers, talent identification experts, performance analysts and other relevant stakeholders involved in performance assessments.

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Product Description

This brief highlights the application of performance analysis tools in data acquisition, and various machine learning algorithms for evaluating team performance as well as talent identification in beach soccer and sepak takraw. Numerous performance indicators and human performance parameters are considered based on their relevance to each sport. The findings presented here demonstrate that the key performance indicators as well as human performance parameters can be used in the future evaluation of team performance as well as talent identification in these sports. Accordingly, they offer a valuable resource for coaches, club managers, talent identification experts, performance analysts and other relevant stakeholders involved in performance assessments.

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Product Details

General

Imprint

Springer Verlag, Singapore

Country of origin

Singapore

Series

SpringerBriefs in Applied Sciences and Technology

Release date

February 2020

Availability

Expected to ship within 10 - 15 working days

First published

2020

Authors

, , ,

Dimensions

235 x 155mm (L x W)

Format

Paperback

Pages

61

Edition

1st ed. 2020

ISBN-13

978-981-15-3218-4

Barcode

9789811532184

Categories

LSN

981-15-3218-4



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