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Recent algorithms for the football team composition problem take into account the skill proficiency of players but not the interactions between players that contribute to winning the championship. To automate the composition of a cohesive team, we consider the internal collaborations among football players. Specifically, we propose a Team Composition based on the Football Players\u2019 Attributed Collaboration Network (TC-FPACN) model, aiming to identify a cohesive football team by maximizing football players\u2019 capabilities and their collaborations via three network metrics, namely, network ability, network density and network heterogeneity&amp;homogeneity. Solving the optimization problem is NP-hard; we develop an approximation method based on greedy algorithms and then improve the method through pruning strategies given a budget limit. We conduct experiments on two popular football simulation platforms. 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