Using network science to analyse football passing networks: Dynamics, space, time, and the multilayer nature of the game.

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During the last decade, Network Science has become one of the most active fields in applied physics
and mathematics (Newman, 2010). From all its possible applications, in this Opinion paper we
are concerned about the analysis of one of the most extended sports, football (soccer in U.S.
terminology) (Sumpter, 2016), since it allows addressing different aspects of the team organization
and performance not captured by classical analyses based on the performance of individual players.
The reason behind relies on the complex nature of the game, which, paraphrasing the foundational
paradigm of complexity sciences “can not be analyzed by looking at its components (i.e., players)
individually but, on the contrary, considering the system as a whole” or, in the classical words of
after-match interviews “it’s not just me, it’s the team.”
The recent ability of obtaining datasets of all events occurring during a match allows analysing
and quantifying the behavior of a team as a whole, together with the role of each single player
(Gudmundsson and Horton, 2017). Under this framework, the organization of a team can be
considered as the result of the interaction between its players, creating passing networks, which
are directed (i.e., links between players go in one direction), weighted (the weight of the links is
based on the number of passes between players), spatially embedded (i.e., the Euclidean position of
the ball and players is highly relevant) and time evolving (i.e., the network continuously changes its
structure).