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A method to inform team sport training activity duration with change point analysis

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  • Ben Teune
  • Carl Woods
  • Alice Sweeting
  • Mathew Inness
  • Sam Robertson

Abstract

Duration is a key component in the design of training activities in sport which aim to enhance athlete skills and physical qualities. Training duration is often a balance between reaching skill development and physiological targets set by practitioners. This study aimed to exemplify change point time-series analyses to inform training activity duration in Australian Football. Five features of player behaviour were included in the analyses: disposal frequency, efficiency, pressure, possession time and player movement velocity. Results of the analyses identified moments of change which may be used to inform minimum or maximum activity durations, depending on a practitioner’s objectives. In the first approach, a univariate analysis determined change points specific to each feature, allowing practitioners to evaluate activities according to a single metric. In contrast, a multivariate analysis considered interactions between features and identified a single change point, reflecting the moment of overall change during activities. Six iterations of a training activity were also evaluated resulting in common change point locations, between 196 and 252 seconds, which indicated alterations to player behaviour between this time period in the training activities conduction. Comparisons of feature segments before and after change points revealed the extent to which player behaviour changed and can guide such duration decisions. These methods can be used to evaluate athlete behaviour and inform training activity durations.

Suggested Citation

  • Ben Teune & Carl Woods & Alice Sweeting & Mathew Inness & Sam Robertson, 2022. "A method to inform team sport training activity duration with change point analysis," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-11, March.
  • Handle: RePEc:plo:pone00:0265848
    DOI: 10.1371/journal.pone.0265848
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    References listed on IDEAS

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    1. Zeileis, Achim & Grothendieck, Gabor, 2005. "zoo: S3 Infrastructure for Regular and Irregular Time Series," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i06).
    2. Killick, Rebecca & Eckley, Idris A., 2014. "changepoint: An R Package for Changepoint Analysis," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 58(i03).
    3. Peter R Browne & Carl T Woods & Alice J Sweeting & Sam Robertson, 2020. "Applications of a working framework for the measurement of representative learning design in Australian football," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-10, November.
    4. Martinique Sparks & Ben Coetzee & J. Tim Gabbett, 2016. "Variations in high-intensity running and fatigue during semi-professional soccer matches," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 16(1), pages 122-132, April.
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