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Spatial movement pattern recognition in soccer based on relative player movements

机译：基于相对球员运动的足球运动模式识别

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Knowledge of spatial movement patterns in soccer occurring on a regular basis can give a soccer coach, analyst or reporter insights in the playing style or tactics of a group of players or team. Furthermore, it can support a coach to better prepare for a soccer match by analysing (trained) movement patterns of both his own as well as opponent players. We explore the use of the Qualitative Trajectory Calculus (QTC), a spatiotemporal qualitative calculus describing the relative movement between objects, for spatial movement pattern recognition of players movements in soccer. The proposed method allows for the recognition of spatial movement patterns that occur on different parts of the field and/or at different spatial scales. Furthermore, the Levenshtein distance metric supports the recognition of similar movements that occur at different speeds and enables the comparison of movements that have different temporal lengths. We first present the basics of the calculus, and subsequently illustrate its applicability with a real soccer case. To that end, we present a situation where a user chooses the movements of two players during 20 seconds of a real soccer match of a 2016–2017 professional soccer competition as a reference fragment. Following a pattern matching procedure, we describe all other fragments with QTC and calculate their distance with the QTC representation of the reference fragment. The top- k most similar fragments of the same match are presented and validated by means of a duo-trio test. The analyses show the potential of QTC for spatial movement pattern recognition in soccer.
机译：经常发生的足球运动模式的知识可以为一群球员或团队的演奏风格或策略提供足球教练，分析师或记者见解。此外，它可以通过分析（训练的）运动模式和对手球员来支持教练来更好地为足球比赛做好准备。我们探讨了定性轨迹微积分（QTC），一种空间运动模式识别足球运动员运动的空间运动模式识别的空间运动模式识别的时空定性光跳的使用。所提出的方法允许识别在场的不同部分和/或不同空间尺度上发生的空间移动模式。此外，Levenshtein距离度量标准支持以不同速度发生的类似运动，并且能够比较具有不同时间长度的运动。我们首先介绍微积分的基础知识，随后用真正的足球案说明其适用性。为此，我们展示了一个情况，其中用户在2016-2017专业足球竞争的真实足球比赛的20秒内选择了两个球员的动作作为参考片段。在模式匹配过程之后，我们描述具有QTC的所有其他片段，并使用参考片段的QTC表示计算它们的距离。通过DUO-TRIO测试呈现和验证相同匹配的顶部k最相似的片段。分析显示QTC在足球中空间运动模式识别的潜力。

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