The Team Winning Analysis Model Based on Network and Entropy Weight

This paper is a research on team winning. Considering the different configurations of teams and the differences between winning rates, this paper puts forward a model that affects the winning rate of teams, which can effectively improve the winning rate of teams. First, we built a passing network and used the Page rank algorithm to calculate the importance of players, then we sorted them out and changed the size of the nodes. Second, we determined the performance indicators and team level indicators that reflect the success of the teamwork, and then we chose seven factors: shooting percentage, passing rate, foul rate, offensive index, defensive index, shots and strategic factors. These seven factors are the ones that affect the team's success. Third, the entropy weight method was used to obtain the weight ratio of the seven factors. Finally, the passing network and entropy method were considered comprehensively, and the application examples were carried out through the 38 games of Huskies team's pairing. The conclusion was drawn that the results obtained by this method can effectively improve the team’s winning rate.