Defining a historic football team: Using Network Science to analyze Guardiola's F.C. Barcelona

TL;DR

This study uses Network Science to analyze Guardiola's F.C. Barcelona, revealing unique network organization features that distinguish it from other teams and relate to its high performance.

Contribution

It combines multiple network metrics and temporal analysis to characterize the unique structure of Guardiola's team and its impact on game outcomes.

Findings

Guardiola's team shows significant differences in network metrics compared to opponents.

Temporal analysis reveals how network properties evolve during matches.

Certain network metrics correlate with scoring and receiving goals.

Abstract

The application of Network Science to social systems has introduced new methodologies to analyze classical problems such as the emergence of epidemics, the arousal of cooperation between individuals or the propagation of information along social networks. More recently, the organization of football teams and their performance have been unveiled using metrics coming from Network Science, where a team is considered as a complex network whose nodes (i.e., players) interact with the aim of overcoming the opponent network. Here, we combine the use of different network metrics to extract the particular signature of the F.C. Barcelona coached by Guardiola, which has been considered one of the best teams along football history. We have first compared the network organization of Guardiola's team with their opponents along one season of the Spanish national league, identifying those metrics with statistically significant differences and relating them with the Guardiola's game. Next, we have focused on the temporal nature of football passing networks and calculated the evolution of all network properties along a match, instead of considering their average. In this way, we are able to identify those network metrics that enhance the probability of scoring/receiving a goal, showing that not all teams behave in the same way and how the organization Guardiola's F.C. Barcelona is different from the rest, including its clustering coefficient, shortest-path length, largest eigenvalue of the adjacency matrix, algebraic connectivity and centrality distribution.