Methods of performance analysis in team invasion sports: A systematic review
| Autor: | Jocelyn K Mara, Felicity Lord, David B. Pyne, Marijke Welvaert |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Competitive Behavior
Knowledge management Team sport business.industry Sports science Data Collection Movement Automatic identification and data capture 030209 endocrinology & metabolism Physical Therapy Sports Therapy and Rehabilitation 030229 sport sciences Athletic Performance Group Processes 03 medical and health sciences 0302 clinical medicine Analytics Task Performance and Analysis Humans Orthopedics and Sports Medicine business Psychology Social network analysis Sports |
| Zdroj: | Journal of sports sciences. 38(20) |
| ISSN: | 1466-447X |
| Popis: | The objective of this review was to systematically describe the traditional and contemporary data capture and analytic methods employed in performance analysis research in team invasion sports, evaluate the practicality of these methods, and formulate practical recommendations on methods for analysing tactics and strategies in team invasion sports. A systematic search of the databases SPORTDiscus, Web of Science, Scopus, MEDLINE and PubMed was performed. Keywords addressed performance analysis methods and team invasion sports, with all other disciplines of sports science excluded. A total of 537 articles were included in the review and six main themes of research identified. Themes included game actions, dynamic game actions, movement patterns, collective team behaviours, social network analysis and game styles. Performance analysis research has predominantly focused on identifying key performance indicators related to success by analysing differences in game actions between successful and less successful teams. However, these measures are outcome-focused and only provide limited insight into winning team's strategy. Team invasion sports are now viewed as dynamic, complex systems with opposing teams as interacting parts. Strategies and tactics should be analysed using a holistic process-orientated approach by recording dynamic actions, collective team behaviours and passing networks, and viewing them in game styles. |
| Databáze: | OpenAIRE |
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