论文标题
通过估计概率，使用国防的广义估值对欧洲欧洲前欧洲欧洲橄榄球运动员的位置分析
Location analysis of players in UEFA EURO 2020 and 2022 using generalized valuation of defense by estimating probabilities
论文作者
论文摘要
由于事件数据有限，分析团队运动中的防守通常具有挑战性。研究人员以前提出了通过预测球增益的事件并使用所有球员和球的位置攻击的方法来评估足球队防守的方法。但是，他们没有考虑这些事件的重要性，而是对所有22名玩家的完美观察，也没有充分研究多样性的影响（例如国籍和性别）。在这里，我们通过得分缩放事件的预测概率提出了一种防守团队的广义评估方法。我们使用男子2020年欧洲杯和2022年女子欧洲杯的足球比赛中所有玩家的开源位置数据，我们调查了玩家人数对预测的影响，并通过分析游戏来验证我们的方法。结果表明，为了预测受到攻击，得分和承认，所有球员的信息并不是必需的，而球获得的信息则需要三到四个进攻和防守球员的信息。通过游戏分析，我们解释了2020年欧洲杯决赛球队捍卫决赛球队的卓越表现。我们的方法可能适用于足球比赛中广播视频框架的位置数据。
Analyzing defenses in team sports is generally challenging because of the limited event data. Researchers have previously proposed methods to evaluate football team defense by predicting the events of ball gain and being attacked using locations of all players and the ball. However, they did not consider the importance of the events, assumed the perfect observation of all 22 players, and did not fully investigated the influence of the diversity (e.g., nationality and sex). Here, we propose a generalized valuation method of defensive teams by score-scaling the predicted probabilities of the events. Using the open-source location data of all players in broadcast video frames in football games of men's Euro 2020 and women's Euro 2022, we investigated the effect of the number of players on the prediction and validated our approach by analyzing the games. Results show that for the predictions of being attacked, scoring, and conceding, all players' information was not necessary, while that of ball gain required information on three to four offensive and defensive players. With game analyses we explained the excellence in defense of finalist teams in Euro 2020. Our approach might be applicable to location data from broadcast video frames in football games.
