Knowledge Commons of Institute of Automation,CAS
All for Goals: a Stylized Automated Analysis Framework in Football Matches | |
Chen M(陈敏)![]() ![]() ![]() | |
2023-03 | |
会议名称 | International Joint Conference on Neural Networks 2023 |
会议日期 | June 18 - 23, 2023 |
会议地点 | Gold Coast Convention and Exhibition Centre Queensland, Australia |
出版地 | New York |
出版者 | IEEE |
摘要 | Automated analysis in football matches is meaningful for player and team evaluation. However, most related works ignore match style and team strength. In this paper, a novel stylized automated analysis framework termed All for Goals (AFG) is proposed for football matches, which considers match style and team strength to better quantify the relationship of all match states and player actions respectively with potential goals. AFG is composed of an automatic labeling module, a potential goal prediction module, and a state and player evaluation module. Specifically, in the automatic labeling module, relevant samples are given the same label to avoid manual labeling. In the potential goal prediction module, we introduce the Pretrain-Finetune paradigm. Based on labeled data, an average model learning to identify scoring difficulty is obtained in the first pre-training procedure, and tuned models learning specific styles are obtained in the second fine-tuning procedure. In the state and player evaluation module, the evaluation mechanisms of state, on-ball action, and off-ball running based on potential goal prediction result are designed for match review and tactics mining. Finally, we validate the rationality and validity of AFG on multiple tasks. On the goal prediction task, the models show high recall rates and remarkable difference in style. On real-time situation analysis, credit assignment for football events, and off-ball running analysis tasks, the evaluation mechanisms give the results consistent with football domain knowledge. |
七大方向——子方向分类 | 机器学习 |
国重实验室规划方向分类 | 虚实融合与迁移学习 |
是否有论文关联数据集需要存交 | 否 |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/52210 |
专题 | 复杂系统认知与决策实验室 |
作者单位 | 1.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 2.Institute of Automation, Chinese Academy of Sciences, Beijing 3.Beijing Sport University 4.China Football College |
推荐引用方式 GB/T 7714 | Chen M,Pu ZQ,Pan Y,et al. All for Goals: a Stylized Automated Analysis Framework in Football Matches[C]. New York:IEEE,2023. |
条目包含的文件 | ||||||
文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
AFG_IEEE.pdf(1485KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 |
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