Liu Hongyou, Gomez Miguel-Ángel, Lago-Peñas Carlos, Sampaio Jaime
a Facultad de Ciencias de la Actividad Física y del Deporte , Universidad Politécnica de Madrid , Madrid , Spain.
J Sports Sci. 2015;33(12):1205-13. doi: 10.1080/02640414.2015.1022578. Epub 2015 Mar 20.
Identifying match statistics that strongly contribute to winning in football matches is a very important step towards a more predictive and prescriptive performance analysis. The current study aimed to determine relationships between 24 match statistics and the match outcome (win, loss and draw) in all games and close games of the group stage of FIFA World Cup (2014, Brazil) by employing the generalised linear model. The cumulative logistic regression was run in the model taking the value of each match statistic as independent variable to predict the logarithm of the odds of winning. Relationships were assessed as effects of a two-standard-deviation increase in the value of each variable on the change in the probability of a team winning a match. Non-clinical magnitude-based inferences were employed and were evaluated by using the smallest worthwhile change. Results showed that for all the games, nine match statistics had clearly positive effects on the probability of winning (Shot, Shot on Target, Shot from Counter Attack, Shot from Inside Area, Ball Possession, Short Pass, Average Pass Streak, Aerial Advantage and Tackle), four had clearly negative effects (Shot Blocked, Cross, Dribble and Red Card), other 12 statistics had either trivial or unclear effects. While for the close games, the effects of Aerial Advantage and Yellow Card turned to trivial and clearly negative, respectively. Information from the tactical modelling can provide a more thorough and objective match understanding to coaches and performance analysts for evaluating post-match performances and for scouting upcoming oppositions.
识别对足球比赛获胜有重大贡献的比赛统计数据,是迈向更具预测性和规范性的表现分析的非常重要的一步。本研究旨在通过广义线性模型,确定2014年巴西世界杯小组赛所有比赛及势均力敌比赛中24项比赛统计数据与比赛结果(胜、负、平)之间的关系。在模型中运行累积逻辑回归,将每项比赛统计数据的值作为自变量,以预测获胜几率的对数。关系评估为每个变量值增加两个标准差对球队赢得比赛概率变化的影响。采用基于非临床量级的推断,并使用最小有价值变化进行评估。结果表明,对于所有比赛,9项比赛统计数据对获胜概率有明显的积极影响(射门、射正、反击射门、禁区内射门、控球率、短传、平均传球次数、空中优势和抢断),4项有明显的负面影响(被封堵射门、传中、盘带和红牌),其他12项统计数据的影响微不足道或不明确。而对于势均力敌的比赛,空中优势和黄牌的影响分别变为微不足道和明显负面。战术建模提供的信息可以为教练和表现分析师提供更全面、客观的比赛理解,以评估赛后表现和侦察即将到来的对手。