  We can construct passing networks when we regard a player as a node and a
pass as a link in football games. Thus, we can analyze the networks by using
tools developed in network science. Among various metrics characterizing a
network, centrality metrics have often been used to identify key players in a
passing network. However, a tolerance to players being marked or passes being
blocked in a passing network, namely the robustness of the network, has been
poorly understood so far. Because the robustness of a passing network can be
connected to the increase of ball possession, it would be deeply related to the
outcome of a game. Here, we developed position-dependent passing networks of 45
matches by 18 teams belonging to the Japan Professional Football League. Then,
nodes or links were continuously removed from the passing networks by two
removal methods so that we could evaluate the robustness of these networks
against the removals. The results show that these passing networks commonly
contain hubs (key players making passes). Then, we analyzed the most robust
networks in detail and found that their full backs increase the robustness by
often invoking a heavier emphasis on attack. Moreover, we showed that the
robustness of the passing networks and the team performance have a positive
correlation.
