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This paper builds up the optimization model of a soccer player’s movement trajectory, which provides good support and method for the player’s soccer tactics training. The player movement trajectory optimization model mainly covers two major functions of player movement trajectory extraction and optimization. The multi-target tracking problem in the soccer game video is transformed into a data association problem, and the similarity matrix is constructed by comprehensively considering the target’s motion information, detection features and apparent features, and the Hungarian algorithm is used to deal with the assignment problem and extract the motion trajectory. Using a genetic algorithm to plan and optimize the player’s movement trajectory, the path is optimized by three genetic operators, namely selection, crossover, and mutation, to find an optimal movement path. Taking the players of the Shandong soccer team of China University Games as the experimental objects to carry out soccer tactics training practice, the average number of passes and successful passes of the experimental group increased by 3.43 times and 21 times compared with the control group and showed stronger aggressiveness and mobility in the soccer playing test. Among the soccer tactical awareness indicators, the mean values of the experimental group were all greater than those of the control group, with the tactical knowledge indicator being the largest, greater than that of the control class by 0.837, showing a significant difference (P |
