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• W2152290682 abstract "From the viewpoint of networks, a ranking system for players or teams in sports is equivalent to a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score of a player (or team) fluctuates over time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. We derive a set of linear online update equations for the score of each player. The proposed ranking system predicts the outcome of the future games with a higher accuracy than the static counterparts." @default.
• W2152290682 created "2016-06-24" @default.
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• W2152290682 date "2012-12-05" @default.
• W2152290682 modified "2023-10-16" @default.
• W2152290682 title "A network-based dynamical ranking system for competitive sports" @default.
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• W2152290682 doi "https://doi.org/10.1038/srep00904" @default.
• W2152290682 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/3514705" @default.
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