Carl T Woods1, Wade Sinclair2, Sam Robertson3. 1. Discipline of Sport and Exercise Science, James Cook University, Australia. Electronic address: carl.woods@jcu.edu.au. 2. Discipline of Sport and Exercise Science, James Cook University, Australia. 3. Institute of Sport, Exercise & Active Living (ISEAL), Victoria University, Australia.
Abstract
OBJECTIVES: To examine the extent at which match outcome and ladder position could be explained using team performance indicators in the National Rugby League (NRL). METHODS: The dataset consisted of 13 performance indicators acquired from each NRL team across the 2016 season (n=376 observations). Data was sorted according to apriori match outcome (win/loss) and ladder position (one to 16). Given the binary and categorical nature of the response variables, two analysis approaches were used; a conditional interference classification tree and ordinal regression. RESULTS: Five performance indicators ('try assists', 'all run meters', 'offloads', 'line breaks' and 'dummy half runs') were retained within the classification tree, detecting 66% of the losses and 91% of the wins. A significant negative relationship was noted between ladder position and 'kick metres' (β (SE)=-0.002 (<0.001); 95% CI=-0.003 to <-0.001) and 'dummy half runs' (β (SE)=-0.017 (<0.012); 95% CI=-0.041 to 0.006), while a significant positive relationship was noted for 'missed tackles' (β (SE)=0.019 (0.006); 95% CI=0.006-0.032). CONCLUSIONS: A unique combination of primarily attacking performance indicators provided the greatest explanation of match outcome and ladder position in the NRL. These results could be used by NRL coaches and analysts as a basis for the development of practice conditions and game strategies that may increase their teams' likelihood of success. Beyond rugby league, this study presents analytical techniques that could be applied to other sports when examining the relationships between performance indicators and match derivatives. Crown
OBJECTIVES: To examine the extent at which match outcome and ladder position could be explained using team performance indicators in the National Rugby League (NRL). METHODS: The dataset consisted of 13 performance indicators acquired from each NRL team across the 2016 season (n=376 observations). Data was sorted according to apriori match outcome (win/loss) and ladder position (one to 16). Given the binary and categorical nature of the response variables, two analysis approaches were used; a conditional interference classification tree and ordinal regression. RESULTS: Five performance indicators ('try assists', 'all run meters', 'offloads', 'line breaks' and 'dummy half runs') were retained within the classification tree, detecting 66% of the losses and 91% of the wins. A significant negative relationship was noted between ladder position and 'kick metres' (β (SE)=-0.002 (<0.001); 95% CI=-0.003 to <-0.001) and 'dummy half runs' (β (SE)=-0.017 (<0.012); 95% CI=-0.041 to 0.006), while a significant positive relationship was noted for 'missed tackles' (β (SE)=0.019 (0.006); 95% CI=0.006-0.032). CONCLUSIONS: A unique combination of primarily attacking performance indicators provided the greatest explanation of match outcome and ladder position in the NRL. These results could be used by NRL coaches and analysts as a basis for the development of practice conditions and game strategies that may increase their teams' likelihood of success. Beyond rugby league, this study presents analytical techniques that could be applied to other sports when examining the relationships between performance indicators and match derivatives. Crown
Authors: Alexandru Nicolae Ungureanu; Corrado Lupo; Paolo Riccardo Brustio Journal: Int J Environ Res Public Health Date: 2021-12-02 Impact factor: 3.390