大数据背景下基于位置数据的足球战术分析方法及发展趋势  

Soccer Tactical Analysis Methods and Development Tendency Based on Positional Data Under the Background of Big Data

作　　者：王泽军 游松辉[1] WANG Zejun;YOU Songhui(International College of Football,Tongji University,Shanghai 200092,China)

机构地区：[1]同济大学国际足球学院,上海200092

出　　处：《上海体育学院学报》2021年第9期60-69,98,共11页Journal of Shanghai University of Sport

基　　金：中央高校基本科研业务费专项资金资助课题(22120210233)。

摘　　要：对大数据背景下基于位置数据的足球战术分析方法进行分析发现:球队中心法可确定球队几何中心,空间控制法可计算球员所覆盖的区域,网络分析法可测量球队的传球行为,机器学习算法可自动识别球队战术的特征。鉴于大数据技术正在推动足球研究领域的革命,而位置数据只能提供单一空间模式的大数据,未来研究应通过整合关于训练需求、周期负荷、竞赛体系、球员体能和疲劳等信息,将生理、心理、位置、教练员、球探、观众等数据实时压缩成较小的变量,运用数据可视化与报告等手段,为教练员提供客观信息,在某种程度上优化对运动表现结果的预测。大数据技术栈和深度学习技术的AI新方法有望为足球战术研究提供新途径。Soccer tactical analysis based on the positional data has shown that the team centroid method can be used to determine the geometric center of the team,space control can calculate individual playing area and dominant region,network analysis can measure the team's pass behavior,and machine learning algorithms can automatically identify the characteristics of team tactics.Given that the big data technology is promoting the study revolution in the field of soccer,the positional data can merely singly provide a spatial pattern analysis value,future research shall integrate varied information including training demands,cycle load,competition system,players'fitness and degree of fatigue.By virtue of processing and compressing data of physiology,psychology,position,coach,scout and audience into smaller variables in real time,coaches can be provided objective information and promote the prediction of performance results to some extent after data visualization and reporting.As a result,the new AI method of big data technology stack and deep learning technology is expected to provide a new approach for the study of soccer tactics.

关 键 词：足球 战术分析 位置数据 深度学习 大数据 

分 类 号：G80-05[文化科学—运动人体科学]