Sports Strategy Analytics Using Probabilistic Reasoning
Author(s)
Dong, JS
Shi, L
Chuong, LVN
Jiang, K
Sun, J
Griffith University Author(s)
Year published
2016
Metadata
Show full item recordAbstract
The advance of analytics technology has attracted more attention and adoption from sports, although modeling and analyzing the dynamic (and uncertain) behaviors of sports are challenging. Formal methods have been strongly recommended to deal with complex systems by their rigorous semantics and powerful reasoning capabilities. In this paper, we present our initiative as the first to apply probabilistic model checking techniques to strategy analytics for tennis based on Markov Decision Processes (MDP). Our approach can derive insights such as prediction of winning chances and identification of best improvement. We evaluate the ...
View more >The advance of analytics technology has attracted more attention and adoption from sports, although modeling and analyzing the dynamic (and uncertain) behaviors of sports are challenging. Formal methods have been strongly recommended to deal with complex systems by their rigorous semantics and powerful reasoning capabilities. In this paper, we present our initiative as the first to apply probabilistic model checking techniques to strategy analytics for tennis based on Markov Decision Processes (MDP). Our approach can derive insights such as prediction of winning chances and identification of best improvement. We evaluate the effectiveness of our approach through real-life case study.
View less >
View more >The advance of analytics technology has attracted more attention and adoption from sports, although modeling and analyzing the dynamic (and uncertain) behaviors of sports are challenging. Formal methods have been strongly recommended to deal with complex systems by their rigorous semantics and powerful reasoning capabilities. In this paper, we present our initiative as the first to apply probabilistic model checking techniques to strategy analytics for tennis based on Markov Decision Processes (MDP). Our approach can derive insights such as prediction of winning chances and identification of best improvement. We evaluate the effectiveness of our approach through real-life case study.
View less >
Conference Title
Proceedings of the IEEE International Conference on Engineering of Complex Computer Systems, ICECCS
Volume
2016-January
Subject
Software engineering not elsewhere classified