Artificial intelligence for team sports: a survey

被引:58
作者
Beal, Ryan [1 ]
Norman, Timothy J. [1 ]
Ramchurn, Sarvapali D. [1 ]
机构
[1] Univ Southampton, Sch Elect & Comp Sci, Southampton SO17 1BJ, Hants, England
基金
英国工程与自然科学研究理事会;
关键词
FOOTBALL; INJURIES; MODEL; RISK; PREDICTION; UNCERTAINTY; PERFORMANCE; EFFICIENCY; FRAMEWORK; MATCHES;
D O I
10.1017/S0269888919000225
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The sports domain presents a number of significant computational challenges for artificial intelligence (AI) and machine learning (ML). In this paper, we explore the techniques that have been applied to the challenges within team sports thus far. We focus on a number of different areas, namely match outcome prediction, tactical decision making, player investments, fantasy sports, and injury prediction. By assessing the work in these areas, we explore how AI is used to predict match outcomes and to help sports teams improve their strategic and tactical decision making. In particular, we describe the main directions in which research efforts have been focused to date. This highlights not only a number of strengths but also weaknesses of the models and techniques that have been employed. Finally, we discuss the research questions that exist in order to further the use of AI and ML in team sports.
引用
收藏
页数:37
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