Peak movement and collision demands of professional rugby league competition |
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| Authors: | Rich D Johnston Dan Weaving Billy T Hulin Kevin Till Ben Jones Grant Duthie |
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| Institution: | 1. School of Behavioural and Health Sciences, Australian Catholic University, Brisbane, Australia;2. Institute for Sport, Physical Activity and Leisure, Leeds Beckett University, Leeds, UKrichard.johnston@acu.edu.au;4. Institute for Sport, Physical Activity and Leisure, Leeds Beckett University, Leeds, UK;5. Leeds Rhinos Rugby League Club, Leeds, UK;6. School of Human Movement and Nutrition Sciences, University of Queensland, Brisbane, Australia;7. Football Department, St. George Illawarra Dragons Rugby League Football Club, Wollongong, Australia;8. Yorkshire Carnegie Rugby Union club, Leeds, UK;9. The Rugby Football League, Leeds, UK |
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| Abstract: | ABSTRACTTo quantify the peak movement and contact demands of National Rugby League (NRL) and European Super League (ESL) competition players were tracked during 10 NRL (166 files) and 10 ESL (143 files) matches using microtechnology devices. The peak 1- to 5-min periods were then calculated for average match speed (m·min?1), and acceleration (m·s?2) when 0, 1, 2, and ≥3 collisions per min occurred. Linear mixed effect models and Cohen’s effect size statistic (± 90%CI) were used to determine the differences in movement profiles when collisions occurred. Compared to no collision periods, as frequency of collisions per minute increased, there were progressive reductions in running speed for most positional groups. The addition of 1 or more collisions per min resulted in average effect size reductions in match speed of ?0.14 for NRL forwards, ?0.89 for NRL backs, ?0.48 for ESL forwards, and ?2.41 for ESL backs. ESL forwards had the highest frequency of peak periods involving 3 or more collisions per min, 22% of all periods, followed by NRL forwards (14%), NRL backs (10%) and ESL backs (8%). This study highlights the peak movement and collision demands of professional rugby league competition and allows practitioners to develop training drills that reflect worst case scenarios. |
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| Keywords: | GPS microtechnology activity profiles moving average contact acceleration |
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