At the topological microscale, the importance of each player has been related to: its degree, which is the number of passes made by a player (Cotta et al., 2013); eigenvector centrality, a measure of importance obtained from the eigenvectors of the adjacency matrix (Cotta et al., 2013); closeness, measuring the minimum number of steps that the ball has to undergo from one player to reach any other in the team (López-Peña and Touchette, 2012); or betweenness centrality, which accounts how many times a given player is necessary for completing the routes (made by the ball) connecting any other two players of its team (Duch et al., 2010; López-Peña and Touchette, 2012).
Other metrics, such as the clustering coefficient, which measures the number of “neighbors” of a player that also have passed the ball between them (i.e., the number of triangles around a player), has also been quantified to evaluate the contribution of a given player to the local robustness of the passing network (López-Peña and Touchette, 2012).