Performance and healthcare analysis in elite sports teams using artificial intelligence: a scoping review
IntroductionIn competitive sports, teams are increasingly relying on advanced systems for improved performance and results. This study reviews the literature on the role of artificial intelligence (AI) in managing these complexities and encouraging a system thinking shift. It found various AI applic...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-04-01
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| Series: | Frontiers in Sports and Active Living |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fspor.2024.1383723/full |
| _version_ | 1827278422193209344 |
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| author | A. A. Munoz-Macho A. A. Munoz-Macho M. J. Domínguez-Morales J. L. Sevillano-Ramos |
| author_facet | A. A. Munoz-Macho A. A. Munoz-Macho M. J. Domínguez-Morales J. L. Sevillano-Ramos |
| author_sort | A. A. Munoz-Macho |
| collection | DOAJ |
| description | IntroductionIn competitive sports, teams are increasingly relying on advanced systems for improved performance and results. This study reviews the literature on the role of artificial intelligence (AI) in managing these complexities and encouraging a system thinking shift. It found various AI applications, including performance enhancement, healthcare, technical and tactical support, talent identification, game prediction, business growth, and AI testing innovations. The main goal of the study was to assess research supporting performance and healthcare.MethodsSystematic searches were conducted on databases such as Pubmed, Web of Sciences, and Scopus to find articles using AI to understand or improve sports team performance. Thirty-two studies were selected for review.ResultsThe analysis shows that, of the thirty-two articles reviewed, fifteen focused on performance and seventeen on healthcare. Football (Soccer) was the most researched sport, making up 67% of studies. The revised studies comprised 2,823 professional athletes, with a gender split of 65.36% male and 34.64% female. Identified AI and non-AI methods mainly included Tree-based techniques (36%), Ada/XGBoost (19%), Neural Networks (9%), K-Nearest Neighbours (9%), Classical Regression Techniques (9%), and Support Vector Machines (6%).ConclusionsThis study highlights the increasing use of AI in managing sports-related healthcare and performance complexities. These findings aim to assist researchers, practitioners, and policymakers in developing practical applications and exploring future complex systems dynamics. |
| first_indexed | 2024-04-24T07:58:42Z |
| format | Article |
| id | doaj.art-d417906c18a447229e11025c99f3f5fe |
| institution | Directory Open Access Journal |
| issn | 2624-9367 |
| language | English |
| last_indexed | 2024-04-24T07:58:42Z |
| publishDate | 2024-04-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Sports and Active Living |
| spelling | doaj.art-d417906c18a447229e11025c99f3f5fe2024-04-18T04:38:24ZengFrontiers Media S.A.Frontiers in Sports and Active Living2624-93672024-04-01610.3389/fspor.2024.13837231383723Performance and healthcare analysis in elite sports teams using artificial intelligence: a scoping reviewA. A. Munoz-Macho0A. A. Munoz-Macho1M. J. Domínguez-Morales2J. L. Sevillano-Ramos3Computer Architecture and Technology Department, University of Seville, Seville, SpainPerformance and Medical Department, Real Club Deportivo Mallorca SAD, Palma, SpainComputer Architecture and Technology Department, University of Seville, Seville, SpainComputer Architecture and Technology Department, University of Seville, Seville, SpainIntroductionIn competitive sports, teams are increasingly relying on advanced systems for improved performance and results. This study reviews the literature on the role of artificial intelligence (AI) in managing these complexities and encouraging a system thinking shift. It found various AI applications, including performance enhancement, healthcare, technical and tactical support, talent identification, game prediction, business growth, and AI testing innovations. The main goal of the study was to assess research supporting performance and healthcare.MethodsSystematic searches were conducted on databases such as Pubmed, Web of Sciences, and Scopus to find articles using AI to understand or improve sports team performance. Thirty-two studies were selected for review.ResultsThe analysis shows that, of the thirty-two articles reviewed, fifteen focused on performance and seventeen on healthcare. Football (Soccer) was the most researched sport, making up 67% of studies. The revised studies comprised 2,823 professional athletes, with a gender split of 65.36% male and 34.64% female. Identified AI and non-AI methods mainly included Tree-based techniques (36%), Ada/XGBoost (19%), Neural Networks (9%), K-Nearest Neighbours (9%), Classical Regression Techniques (9%), and Support Vector Machines (6%).ConclusionsThis study highlights the increasing use of AI in managing sports-related healthcare and performance complexities. These findings aim to assist researchers, practitioners, and policymakers in developing practical applications and exploring future complex systems dynamics.https://www.frontiersin.org/articles/10.3389/fspor.2024.1383723/fullartificial intelligencesports teamscomplex systemssports performanceinjury preventionhealthcare |
| spellingShingle | A. A. Munoz-Macho A. A. Munoz-Macho M. J. Domínguez-Morales J. L. Sevillano-Ramos Performance and healthcare analysis in elite sports teams using artificial intelligence: a scoping review Frontiers in Sports and Active Living artificial intelligence sports teams complex systems sports performance injury prevention healthcare |
| title | Performance and healthcare analysis in elite sports teams using artificial intelligence: a scoping review |
| title_full | Performance and healthcare analysis in elite sports teams using artificial intelligence: a scoping review |
| title_fullStr | Performance and healthcare analysis in elite sports teams using artificial intelligence: a scoping review |
| title_full_unstemmed | Performance and healthcare analysis in elite sports teams using artificial intelligence: a scoping review |
| title_short | Performance and healthcare analysis in elite sports teams using artificial intelligence: a scoping review |
| title_sort | performance and healthcare analysis in elite sports teams using artificial intelligence a scoping review |
| topic | artificial intelligence sports teams complex systems sports performance injury prevention healthcare |
| url | https://www.frontiersin.org/articles/10.3389/fspor.2024.1383723/full |
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