Football (soccer) has been an immensely important part of my life from which friendships have been made and a great appreciation has been developed through watching and analyzing the game. More specifically, there are an infinite amount of aspects that can be considered including space, passing patterns, and player synergy or connections. Relating to CSCC46: Social and Information Networks, one would think some of these ideas can be directly related to network science. With the increased collection size of sport statistics collected throughout every game a soccer team plays, there surely must be someone who has applied network science to soccer, right?
J.M. Buldu et al. are a team of researchers who have done just that, and in their paper, Using network science to analyze football passing networks: dynamics, space, time and the multilayer nature of the game, they discuss in more detail this connection. The paper details multiple and more complex concepts, but here I will describe some of these concepts and how they relate to CSCC46. Specifically, for one network model, they constructed a network based on passing from player to player for one game. To construct this network, they used statistics collected for the team FC Barcelona in a game against Real Madrid CF in 2018 (Figure 1).
Similar to concepts introduced in CSCC46, some of the key ideas J.M. Buldu et al. discuss are the directed and weighted nature of the network representing the direction and quantity of passing from player to player, the betweenness of edges which accounts how many times a given player passing connection is necessary for completing a passing route between any two players in the team, and the clustering coefficient which measures the number of neighbours of a player that have passing connections between themselves.
So, what meaning or practical information can be derived from these network attributes? Well it is hard to say exactly as this connection between network and soccer is relatively new, but some possible conclusions can be speculated. For example, most obviously and simplistically, highly weighted edges in both directions between two given players means they share many passes and might suggest these two players have strong synergy. Additionally (or alternatively), it may suggest that the two positions in which each of these two players play share a commonly used passing lane or connection. Perhaps some of these conclusions can assist coaches and managers to better construct their teams and develop tactics. On the other hand, opposition teams could also use this information to devise counter plans.
Either way, its clear that a plenitude of information can produced by applying network science to soccer statistics and perhaps this connection can be a useful tool in further analyzing the beautiful game.
Source: https://arxiv.org/ftp/arxiv/papers/1807/1807.00534.pdf