Complex Systems Group & GISC, Universidad Rey Juan Carlos, 28933, Madrid, Spain.
Laboratory of Biological Networks, Center for Biomedical Technology, UPM, Pozuelo de Alarcón, 28223, Madrid, Spain.
Sci Rep. 2020 Nov 12;10(1):19735. doi: 10.1038/s41598-020-76835-3.
We investigated the ability of football teams to develop a particular playing style by looking at their passing patterns. Using the information contained in the pass sequences during matches, we constructed the pitch passing networks of teams, whose nodes are the divisions of the pitch for a given spatial scale and links account for the number of passes from region to region. We translated football passings networks into their corresponding adjacency matrices. We calculated the correlations between matrices of the same team to quantify how consistent the passing patterns of a given team are. Next, we quantified the differences with other teams' matrices and obtained an identifiability parameter that indicates how unique are the passing patterns of a given team. Consistency and identifiability rankings were calculated during a whole season, allowing to detect those teams of a league whose passing patterns are different from the rest. Furthermore, we found differences between teams playing at home or away. Finally, we used the identifiability parameter to investigate what teams imposed their passing patterns over the rivals during a given match.
我们通过观察足球队伍的传球模式，研究了它们发展出特定比赛风格的能力。利用比赛中传球序列所包含的信息，我们构建了球队的球场传球网络，其节点是给定空间尺度的球场分区，而连接则表示区域之间传球的数量。我们将足球传球网络转化为它们相应的邻接矩阵。我们计算了同一支球队的矩阵之间的相关性，以量化一个给定球队的传球模式的一致性程度。接下来，我们量化了与其他球队矩阵之间的差异，得到了一个可识别性参数，该参数表示一个给定球队的传球模式的独特程度。在整个赛季中计算了一致性和可识别性排名，以检测联赛中那些传球模式与其他球队不同的球队。此外，我们还发现了主场和客场比赛之间的差异。最后，我们使用可识别性参数来研究在给定比赛中，哪些球队将自己的传球模式强加给了对手。
