Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professio...Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) loop.In addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making.展开更多
目的:为了综合提高高校足球训练成绩,丰富高校足球训练方式,通过实验分组干预的形式,观察组合训练对高校学生参与足球训练成绩的影响。方法:选取某高校60名男生,平均分为对照组与实验组,每组30人。对照组采取传统教学方法,实验组选取组...目的:为了综合提高高校足球训练成绩,丰富高校足球训练方式,通过实验分组干预的形式,观察组合训练对高校学生参与足球训练成绩的影响。方法:选取某高校60名男生,平均分为对照组与实验组,每组30人。对照组采取传统教学方法,实验组选取组合训练的形式开展为期15周的足球教学与训练。最后通过教考分离的形式对学生身体素质、一般技能与专项技能进行考核。结果:相对于传统训练法而言,实验组学生身体素质指标中的肺活量、最大摄氧量、20 m加速跑、立定跳远,以及基础技能指标中的接控球、抢断球、运球突破、传球、1 min 1v1区域内对抗的进攻次数、1 min 1v1区域内对抗的防守次数、移动中双定点射门成功次数(20球)、运球绕杆射门指标均得到显著提升,P<0.01。结论:组合训练能够提高学生身体素质、足球一般技能与专项技能,可以作为足球教学与训练的方法。展开更多
基金supported by the National Key Research,Development Program of China (2020AAA0103404)the Beijing Nova Program (20220484077)the National Natural Science Foundation of China (62073323)。
文摘Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) loop.In addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making.
文摘目的:为了综合提高高校足球训练成绩,丰富高校足球训练方式,通过实验分组干预的形式,观察组合训练对高校学生参与足球训练成绩的影响。方法:选取某高校60名男生,平均分为对照组与实验组,每组30人。对照组采取传统教学方法,实验组选取组合训练的形式开展为期15周的足球教学与训练。最后通过教考分离的形式对学生身体素质、一般技能与专项技能进行考核。结果:相对于传统训练法而言,实验组学生身体素质指标中的肺活量、最大摄氧量、20 m加速跑、立定跳远,以及基础技能指标中的接控球、抢断球、运球突破、传球、1 min 1v1区域内对抗的进攻次数、1 min 1v1区域内对抗的防守次数、移动中双定点射门成功次数(20球)、运球绕杆射门指标均得到显著提升,P<0.01。结论:组合训练能够提高学生身体素质、足球一般技能与专项技能,可以作为足球教学与训练的方法。
