AbstractIn elite soccer, monitoring training and match load using Global Navigation Satellite System (GNSS) devices is well established and provides insight to assist practitioners to plan training that optimises performance and minimises injury risk. The influx in available GNSS data enables practitioners and researchers to more easily interrogate data and push the boundaries of performance. However, it also introduces communication challenges to provide coaches with succinct messages to effect training decisions. This thesis aims to investigate the applicability of GNSS devices to accurately provide data and instigate the subsequent analysis process to provide insight to the association between training load, injury and performance.
Results showed position tracking devices to acceptably measure team-sport specific movement with caution recommended when measuring high complexity movements. This element of the thesis was carried out early in the PhD and the author notes that providers can now externally certify accuracy through FIFA standardised testing.
Training load data from an English Premier League club was contextualised using a match data reference method and then simplified using dimensionality reduction which identified three pertinent components of training load. This methodology was used using data from Australian A-League soccer players and showed that conscious manipulation of training loads over an extended multi-season period may be able to influence team injury rates in professional soccer. Analysis on the same group of player across the same time period showed that training load did not offer any additional insight into performance estimation over simple forecasting models. Additionally, none of the models within the study performed well enough to be a useful practical tool to predict performance.
This research offers insight into training analysis techniques and applied case studies of load, providing practitioners with examples of how to manipulate GNSS data for effective use to inform strategic decisions.
|Date of Award
|2 Dec 2020
|Keith Stokes (Supervisor) & Dario Cazzola (Supervisor)