Real Time Quantification of Dangerousity in Football Using Spatiotemporal Tracking Data.
Real Time Quantification of Dangerousity in Football Using Spatiotemporal Tracking Data.
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DOI：
10.1371/journal.pone.0168768
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发表时间：
2016
期刊：
影响因子：
3.7
通讯作者：
Seidenschwarz P
中科院分区：
文献类型：
--
作者：
Link D;Lang S;Seidenschwarz P
本研究描述了一种量化足球进攻表现的方法。我们的程序确定了一个定量表示的概率进球得分的每一个点的时间，在这个时间点上，一名球员是在控球，我们称之为不确定性。该计算基于球员和球的空间星座，并且包括四个分量：（1）区域描述了从球员在球上的位置得分的危险，（2）控制代表球员在球的动力学基础上实现其战术意图的程度，（3）压力代表防守队阻止球员完成带球动作的可能性，（4）密度是在动作后能够防守球的机会。其他度量可以从可预测性中导出，通过这些度量可以回答与游戏分析有关的问题。动作值表示球员通过控球可以使情况变得更危险的程度。性能量化了一个团队在一段时间内攻击的数量和质量，而优势描述了团队之间的性能差异。评估使用赢得比赛的概率之间的相关性（来自投注赔率）和性能指标，并表明，在目标差异（r = .55），射门得分差异（r = 0.58），通过精度差异（r = 0.56）、抢断率（r = 0.24）、控球率（r = 0.71）和优势（r = 0.82），后者对解释球队技术水平的贡献最大。我们使用这些指标来分析比赛中的个人行为，描述比赛过程，并评估球队在赛季中的表现和效率。对于未来的研究，他们提供了一个标准，不依赖于机会或结果，以调查在一场比赛中的中心事件，各种比赛系统或战术组的概念对成功的影响。
This study describes an approach to quantification of attacking performance in football. Our procedure determines a quantitative representation of the probability of a goal being scored for every point in time at which a player is in possession of the ball–we refer to this as dangerousity. The calculation is based on the spatial constellation of the player and the ball, and comprises four components: (1) Zone describes the danger of a goal being scored from the position of the player on the ball, (2) Control stands for the extent to which the player can implement his tactical intention on the basis of the ball dynamics, (3) Pressure represents the possibility that the defending team prevent the player from completing an action with the ball and (4) Density is the chance of being able to defend the ball after the action. Other metrics can be derived from dangerousity by means of which questions relating to analysis of the play can be answered. Action Value represents the extent to which the player can make a situation more dangerous through his possession of the ball. Performance quantifies the number and quality of the attacks by a team over a period of time, while Dominance describes the difference in performance between teams. The evaluation uses the correlation between probability of winning the match (derived from betting odds) and performance indicators, and indicates that among Goal difference (r = .55), difference in Shots on Goal (r = .58), difference in Passing Accuracy (r = .56), Tackling Rate (r = .24) Ball Possession (r = .71) and Dominance (r = .82), the latter makes the largest contribution to explaining the skill of teams. We use these metrics to analyse individual actions in a match, to describe passages of play, and to characterise the performance and efficiency of teams over the season. For future studies, they provide a criterion that does not depend on chance or results to investigate the influence of central events in a match, various playing systems or tactical group concepts on success.
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影响因子：
3.7
作者：
Duch J;Waitzman JS;Amaral LA
通讯作者：
Amaral LA
DOI：
10.1016/j.compenvurbsys.2013.09.004
发表时间：
2014-09-01
影响因子：
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通讯作者：
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