The intelligent simulation of Sports can match the actual game and is of great significance to the development of Sports. Sports is a system in which multiple agents work together. Compared with a single agent, the learning space of multiple agents increases sharply as the number of agents increases, so the learning difficulty increases. Therefore, based on machine learning technology, this study combines with the actual situation to build a Sports simulation system. Moreover, after establishing a more reasonable team defensive formation and strategy, the overall movement of the agent is optimized, and the corresponding structural model has been established in combination with various actions. In addition, this study designs a controlled trial to analyze the performance of the model. The research shows that the proposed method has certain effects and can provide theoretical reference for subsequent related research.

运动智能模拟可以匹配实际比赛，对运动的发展具有重要意义。体育是一个由多个特工共同工作的系统。与单个Agent相比，随着Agent数量的增加，多个Agent的学习空间急剧增加，因此学习难度增加。因此，本研究基于机器学习技术，结合实际，构建了运动仿真系统。此外，在建立更合理的团队防御结构和策略后，优化了特工的整体动作，并结合各种动作建立了相应的结构模型。此外，本研究设计了一个对照试验来分析模型的性能。