Journal article 547 views 161 downloads
Classifying Winning Performances in International Women’s Rugby Union
,
Mark Waldron ,
Eifion Roberts,
David B. Pyne ,
Jocelyn Mara ,
Christian Cook ,
Laura Mason ,
Rowan Brown ,
Liam Kilduff
International Journal of Sports Physiology and Performance, Volume: 18, Issue: 9, Pages: 1 - 7
Swansea University Authors:
Georgia Scott, Neil Bezodis , Mark Waldron , Laura Mason , Rowan Brown , Liam Kilduff
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DOI (Published version): 10.1123/ijspp.2023-0086
Abstract
Purpose: The efficacy of isolated and relative performance indicators (PIs) has been compared within Rugby Union; the latter more effective at discerning match outcomes. However, this methodology has not been applied within women’s rugby. The aim of this study was to identify PIs that maximize predi...
| Published in: | International Journal of Sports Physiology and Performance |
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| ISSN: | 1555-0265 1555-0273 |
| Published: |
Human Kinetics
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa63875 |
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| Abstract: |
Purpose: The efficacy of isolated and relative performance indicators (PIs) has been compared within Rugby Union; the latter more effective at discerning match outcomes. However, this methodology has not been applied within women’s rugby. The aim of this study was to identify PIs that maximize prediction accuracy of match outcome, from isolated and relative datasets, in Women’s Rugby Union. Methods: Twenty-six PIs were selected from 110 women’s international rugby matches between 2017-2022 to form an isolated dataset, with relative datasets determined by subtracting corresponding opposition PIs. Random forest classification was completed on both datasets, and feature selection and importance used to simplify models and interpret key PIs. Models were used in prediction on the 2021 World Cup to evaluate performance on unseen data. Results: The isolated full model correctly classified 75% of outcomes (CI (65%, 82%)), whereas the relative full model correctly classified 78% (CI (69%, 86%)). Reduced respective models correctly classified 74% (CI (65%, 82%)) and 76% (CI (67%, 84%)). Reduced models correctly predicted 100% and 96% of outcomes for isolated and relative test datasets, respectively. No significant difference in accuracy was found between datasets. Within the relative reduced model, metres made, clean breaks, missed tackles, lineouts lost, carries and kicks from hand were significant. Conclusions: Increased relative metres made, clean breaks, carries, kicks from hand, and decreased relative missed tackles and lineouts lost were associated with success. This information can be utilized to inform physical and tactical preparation and direct physiological studies in women’s rugby. |
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| Keywords: |
Game Statistics, Decision Modelling, Multivariate Analysis, Team Sports, Women’s Sports. |
| College: |
Faculty of Science and Engineering |
| Issue: |
9 |
| Start Page: |
1 |
| End Page: |
7 |