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Machine learning in team sportsperfo...
~
Muazu Musa, Rabiu.
Machine learning in team sportsperformance analysis and talent identification in beach soccer and sepak-takraw /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Machine learning in team sportsby Rabiu Muazu Musa ... [et al.].
Reminder of title:
performance analysis and talent identification in beach soccer and sepak-takraw /
other author:
Muazu Musa, Rabiu.
Published:
Singapore :Springer Singapore :2020.
Description:
x, 61 p. :ill., digital ;24 cm.
Contained By:
Springer eBooks
Subject:
SportsData processing.
Online resource:
https://doi.org/10.1007/978-981-15-3219-1
ISBN:
9789811532191$q(electronic bk.)
Machine learning in team sportsperformance analysis and talent identification in beach soccer and sepak-takraw /
Machine learning in team sports
performance analysis and talent identification in beach soccer and sepak-takraw /[electronic resource] :by Rabiu Muazu Musa ... [et al.]. - Singapore :Springer Singapore :2020. - x, 61 p. :ill., digital ;24 cm. - SpringerBriefs in applied sciences and technology,2191-530X. - SpringerBriefs in applied sciences and technology..
An Overview of Beach Soccer, Sepak Takraw and the Application of Machine Learning in Team Sports -- Key performance indicators in elite beach soccer -- Technical and tactical performance indicators determining successful and unsuccessful team in elite beach soccer -- Identifying talent in sepak takraw via Anthropometry indexes -- Physical fitness parameters in the identification of high potential sepak takraw players -- Relationship between psycho-maturity and performance of sepak takraw -- Concluding Remarks.
This brief highlights the application of performance analysis tools in data acquisition, and various machine learning algorithms for evaluating team performance as well as talent identification in beach soccer and sepak takraw. Numerous performance indicators and human performance parameters are considered based on their relevance to each sport. The findings presented here demonstrate that the key performance indicators as well as human performance parameters can be used in the future evaluation of team performance as well as talent identification in these sports. Accordingly, they offer a valuable resource for coaches, club managers, talent identification experts, performance analysts and other relevant stakeholders involved in performance assessments.
ISBN: 9789811532191$q(electronic bk.)
Standard No.: 10.1007/978-981-15-3219-1doiSubjects--Topical Terms:
709084
Sports
--Data processing.
LC Class. No.: GV568
Dewey Class. No.: 796.0285631
Machine learning in team sportsperformance analysis and talent identification in beach soccer and sepak-takraw /
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An Overview of Beach Soccer, Sepak Takraw and the Application of Machine Learning in Team Sports -- Key performance indicators in elite beach soccer -- Technical and tactical performance indicators determining successful and unsuccessful team in elite beach soccer -- Identifying talent in sepak takraw via Anthropometry indexes -- Physical fitness parameters in the identification of high potential sepak takraw players -- Relationship between psycho-maturity and performance of sepak takraw -- Concluding Remarks.
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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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Intelligent Technologies and Robotics (Springer-42732)
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電子館藏
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1
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電子館藏
1圖書
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EB GV568 .M149 2020 2020
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1 records • Pages 1 •
1
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https://doi.org/10.1007/978-981-15-3219-1
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