Visualising the complexity of the athlete monitoring cycle through principal component analysis

Weaving, Dan; Beggs, Clive; Dalton-Barron, Nicholas; Jones, Ben; Abt, Grant

Abstract

Purpose: To discuss the use of principal-component analysis (PCA) as a dimension-reduction and visualization tool to assist in decision making and communication when analyzing complex multivariate data sets associated with the training of athletes. Conclusions: Using PCA, it is possible to transform a data matrix into a set of orthogonal composite variables called principal components (PCs), with each PC being a linear weighted combination of the observed variables and with all PCs uncorrelated to each other. The benefit of transforming the data using PCA is that the first few PCs generally capture the majority of the information (ie, variance) contained in the observed data, with the first PC accounting for the highest amount of variance and each subsequent PC capturing less of the total information. Consequently, through PCA, it is possible to visualize complex data sets containing multiple variables on simple 2D scatterplots without any great loss of information, thereby making it much easier to convey complex information to coaches. In the future, athlete-monitoring companies should integrate PCA into their client packages to better support practitioners trying to overcome the challenges associated with multivariate data analysis and interpretation. In the interim, the authors present here an overview of PCA and associated R code to assist practitioners working in the field to integrate PCA into their athlete-monitoring process.

Citation

Weaving, D., Beggs, C., Dalton-Barron, N., Jones, B., & Abt, G. (2019). Visualising the complexity of the athlete monitoring cycle through principal component analysis. International journal of sports physiology and performance : IJSPP, 14(9), 1304-1310. https://doi.org/10.1123/ijspp.2019-0045

• Journal Article Type: Article
• Acceptance Date: Jul 30, 2019
• Publication Date: 2019-10
• Deposit Date: Aug 1, 2019
• Publicly Available Date: Dec 1, 2019
• Journal: International Journal of Sports Physiology and Performance
• Print ISSN: 1555-0265
• Publisher: Human Kinetics
• Peer Reviewed: Peer Reviewed
• Volume: 14
• Issue: 9
• Pages: 1304-1310
• DOI: https://doi.org/10.1123/ijspp.2019-0045
• Public URL: https://hull-repository.worktribe.com/output/2283079
• Contract Date: Aug 1, 2019