Performance indicators contributing to success at the group and play-off stages of the 2019 Rugby World Cup
DOI:
https://doi.org/10.14198/jhse.2022.173.18Keywords:
Decision rules, Rugby Union, Sport performance analysis, Machine learning, Non-parametric statistics, RIPPERAbstract
Performance indicators that contributed to success at the group and play-off stages of the 2019 Rugby World Cup were analysed using publicly available data obtained from the official tournament website using both a non-parametric statistical technique, Wilcoxon’s signed rank test, and a decision rules technique from machine learning called RIPPER. Our statistical results found that ball carry effectiveness (percentage of ball carries that penetrated the opposition gain-line) and total metres gained (kick metres plus carry metres) were found to contribute to success at both stages of the tournament and that indicators that contributed to success during group stages (dominating possession, making more ball carries, making more passes, winning more rucks, and making less tackles) did not contribute to success at the play-off stage. Our results using RIPPER found that low ball carries and a low lineout success percentage jointly contributed to losing at the group stage, while winning a low number of rucks and carrying over the gain-line a sufficient number of times contributed to winning at the play-off stage of the tournament. The results emphasise the need for teams to adapt their playing strategies from group stage to the play-off stage at the tournament in order to be successful.
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