Machine Learning in Team Sports: Performance Analysis and Talent Identification in Beach Soccer & Sepak-takraw (SpringerBriefs in Applied Sciences and Technology)
Book information
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.
Similar books
Machine Learning in Aquaculture: Hunger Classification of Lates calcarifer (SpringerBriefs in Applied Sciences and Technology)
2020 · PDF
Machine Learning in Elite Volleyball: Integrating Performance Analysis, Competition and Training Strategies (SpringerBriefs in Applied Sciences and Technology)
2021 · PDF
Data Mining and Machine Learning in High-Performance Sport: Performance Analysis of On-field and Video Assistant Referees in European Soccer Leagues (SpringerBriefs in Applied Sciences and Technology)
2022 · PDF
Data Mining and Machine Learning in Sports: Success Metrics for Elite Goalkeepers in European Football Leagues (SpringerBriefs in Applied Sciences and Technology)
2024 · PDF
Advancing Sports and Exercise via Innovation: Proceedings of the 9th Asian South Pacific Association of Sport Psychology International Congress (ASPASP) 2022, Kuching, Malaysia
2023 · PDF
Deep Learning in Cancer Diagnostics: A Feature-based Transfer Learning Evaluation
2023 · PDF
Machine Learning in Sports: Identifying Potential Archers
2019 · PDF
MySQL® Notes for Professionals book
2018 · PDF