An Educational Review on Machine Learning: A SWOT Analysis for Implementing Machine Learning Techniques in Football.

IF 3.5 2区 医学 Q1 PHYSIOLOGY
Marco Beato, Mohamed Hisham Jaward, George P Nassis, Pedro Figueiredo, Filipe Manuel Clemente, Peter Krustrup
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引用次数: 0

Abstract

Purpose: The abundance of data in football presents both opportunities and challenges for decision making. Consequently, this review has 2 primary objectives: first, to provide practitioners with a concise overview of the characteristics of machine-learning (ML) analysis, and, second, to conduct a strengths, weaknesses, opportunities, and threats (SWOT) analysis regarding the implementation of ML techniques in professional football clubs. This review explains the difference between artificial intelligence and ML and the difference between ML and statistical analysis. Moreover, we summarize and explain the characteristics of ML learning approaches, such as supervised learning, unsupervised learning, and reinforcement learning. Finally, we present an example of a SWOT analysis that suggests some actions to be considered in applying ML techniques by medical and sport science staff working in football. Specifically, 4 dimensions are presented: the use of strengths to create opportunities and make the most of them, the use of strengths to avoid threats, working on weaknesses to take advantage of opportunities, and upgrading weaknesses to avoid threats.

Conclusion: ML analysis can be an invaluable tool for football clubs and sport-science and medical departments due to its ability to analyze vast amounts of data and extract meaningful insights. Moreover, ML can enhance performance by assessing the risk of injury, physiological parameters, and physical fitness, as well as optimizing training, recommending strategies based on opponent analysis, and identifying talent and assessing player suitability.

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来源期刊
CiteScore
5.80
自引率
12.10%
发文量
199
审稿时长
6-12 weeks
期刊介绍: The International Journal of Sports Physiology and Performance (IJSPP) focuses on sport physiology and performance and is dedicated to advancing the knowledge of sport and exercise physiologists, sport-performance researchers, and other sport scientists. The journal publishes authoritative peer-reviewed research in sport physiology and related disciplines, with an emphasis on work having direct practical applications in enhancing sport performance in sport physiology and related disciplines. IJSPP publishes 10 issues per year: January, February, March, April, May, July, August, September, October, and November.
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