Abstract
This study aims to (a) quantify the movement patterns during rugby league match-play and (b) identify if differences exist by levels of competition within the movement patterns and units through the sequential movement pattern (SMP) algorithm. Global Positioning System data were analysed from three competition levels; four Super League regular (regular-SL), three Super League (semi-)Finals (final-SL) and four international rugby league (international) matches. The SMP framework extracted movement pattern data for each athlete within the dataset. Between competition levels, differences were analysed using linear discriminant analysis (LDA). Movement patterns were decomposed into their composite movement units; then Kruskal-Wallis rank-sum and Dunn post-hoc were used to show differences. The SMP algorithm found 121 movement patterns comprised mainly of "walk" and "jog" based movement units. The LDA had an accuracy score of 0.81, showing good separation between competition levels. Linear discriminant 1 and 2 explained 86% and 14% of the variance. The Kruskal-Wallis found differences between competition levels for 9 of 17 movement units. Differences were primarily present between regular-SL and international with other combinations showing less differences. Movement units which showed significant differences between competition levels were mainly composed of low velocities with mixed acceleration and turning angles. The SMP algorithm found 121 movement patterns across all levels of rugby league match-play, of which, 9 were found to show significant differences between competition levels. Of these nine, all showed significant differences present between international and domestic, whereas only four found differences present within the domestic levels. This study shows the SMP algorithm can be used to differentiate between levels of rugby league and that higher levels of competition may have greater velocity demands.
More Information
Identification Number: | https://doi.org/10.1080/17461391.2022.2027527 |
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Status: | Published |
Refereed: | Yes |
Publisher: | Taylor and Francis |
Uncontrolled Keywords: | Global positioning systems, data analytics, team sports, 0913 Mechanical Engineering, 1106 Human Movement and Sports Sciences, Sport Sciences, |
Depositing User (symplectic) | Deposited by Collins, Neil |
Date Deposited: | 25 Mar 2022 16:56 |
Last Modified: | 21 Jul 2024 22:10 |
Item Type: | Article |
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Read more research from the author(s):
- N Collins ORCID: 0000-0002-3081-3243
- R White
- A Palczewska ORCID: 0000-0002-6196-9582
- D Weaving ORCID: 0000-0002-4348-9681
- N Dalton-Barron
- B Jones ORCID: 0000-0002-4274-6236