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  • Sports Strategy Analytics Using Probabilistic Reasoning

    Author(s)
    Dong, JS
    Shi, L
    Chuong, LVN
    Jiang, K
    Sun, J
    Griffith University Author(s)
    Dong, Jin-Song
    Year published
    2016
    Metadata
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    Abstract
    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 ...
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    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.
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    Conference Title
    Proceedings of the IEEE International Conference on Engineering of Complex Computer Systems, ICECCS
    Volume
    2016-January
    DOI
    https://doi.org/10.1109/ICECCS.2015.28
    Subject
    Software engineering not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/172934
    Collection
    • Conference outputs

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