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Using cooperative networks to analyse behaviour in professional Australian Football
William B Sheehan1, Rhys Tribolet1, Mark L Watsford1
1Human Performance Research Centre, Faculty of Health, University of Technology Sydney, Australia.
Journal of Science and Medicine in Sport
|October 5, 2019
Summary
This study simplifies complex network analysis in Australian Football League (AFL) games using principal component analysis. It reveals key individual and team metrics for better coaching and player evaluation.
Area of Science:
- Sports Science
- Network Analysis
- Biomechanics
Background:
- Complex network analysis in Australian Football League (AFL) games generates numerous characteristics.
- These characteristics are often difficult to interpret and apply practically in coaching and performance analysis.
Purpose of the Study:
- To reduce the dimensionality of complex network characteristics from AFL games.
- To enhance the practical utility and interpretability of network data for coaches and practitioners.
Main Methods:
- Utilized a retrospective longitudinal design over three AFL seasons.
- Collected data on player interactions via kicks and handballs.
- Applied principal component analysis (PCA) to simplify network characteristics.
Main Results:
- PCA identified two individual-based components related to in- and out-degree importance.
- PCA revealed three team-based components concerning connectedness and centralization.
- Derived metrics offer insights into player and team dynamics.
Conclusions:
- Presents a novel, simplified method for analyzing AFL network structures.
- Generated team- and individual-derived metrics provide actionable insights.
- Findings can inform opposition analysis, training, player ratings, and selection.
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