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预测 2015 年橄榄球世界杯小组赛和淘汰赛阶段的表现。

Predicting performance at the group-phase and knockout-phase of the 2015 Rugby World Cup.

机构信息

Rugby Union of Russia, Moscow, Russia.

Applied Sport Technology Exercise and Medicine Research Centre (A-STEM), College of Engineering, Swansea University, Swansea, Wales.

出版信息

Eur J Sport Sci. 2021 Mar;21(3):312-320. doi: 10.1080/17461391.2020.1743764. Epub 2020 Apr 6.

Abstract

The primary aim of this paper was to produce a model that predicts outcome in the group-phase of the 2015 Rugby World Cup and to determine the relevance and importance of performance indicators (PIs) that are significant in predicting outcome. A secondary aim investigated whether this model accurately predicted match outcome in the knockout-phase of the competition. Data was the PIs from the 40 group-phase games of the 2015 RWC. Given the binary outcome (win/lose), a random forest classification model was built using the data sets. The outcome of the knockout-phase was predicted using this model and accuracy of prediction of the model from the group-phase. The model indicated that thirteen PIs were significant in predicting match outcome in the group-phase and provided accurate prediction of match outcome in the knockout-phase. These PIs were tackle-ratio, clean breaks, average carry, lineouts won, penalties conceded, missed tackles, lineouts won in the opposition 22, defenders beaten, metres carried, kicks from hand, lineout success, penalties in opposition 22 m and scrums won. For the group-phase matches tackle ratio, clean breaks and average carry were accurate standalone predictors of match outcome and respectively predicted 75%, 70% and 73% of match outcomes. The model based on the group-phase predicted correctly 7 from 8 (87.5%) knockout-phase matches. In the knockout-phase clean breaks predicted 7 from 8 outcomes, whilst tackle ratio and average carry predicted 6 from 8 outcomes.

摘要

本文的主要目的是建立一个预测 2015 年橄榄球世界杯分组阶段比赛结果的模型,并确定在预测比赛结果中具有重要意义的表现指标(PI)的相关性和重要性。次要目的是调查该模型是否能准确预测比赛淘汰赛阶段的比赛结果。数据来自 2015 年 RWC 的 40 场分组赛的 PI。鉴于二元结果(胜/负),使用数据集构建了随机森林分类模型。使用该模型预测淘汰赛阶段的结果,并预测分组阶段模型的预测准确性。该模型表明,在预测分组阶段的比赛结果时,有 13 个 PI 是重要的,并准确预测了淘汰赛阶段的比赛结果。这些 PI 是铲球率、干净突破、平均持球推进、成功争边球、罚踢、漏防、在对方 22 米区域成功争边球、突破防守、持球推进米数、手抛球踢球、争边球成功率、在对方 22 米区域罚踢、成功争达阵。对于分组阶段的比赛,铲球率、干净突破和平均持球推进是比赛结果的准确独立预测指标,分别预测了 75%、70%和 73%的比赛结果。基于分组阶段的模型正确预测了 8 场淘汰赛阶段比赛中的 7 场(87.5%)。在淘汰赛阶段,干净突破预测了 8 场比赛中的 7 场,而铲球率和平均持球推进分别预测了 8 场比赛中的 6 场。

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