Predicting the Duration of Professional Tennis Matches Using MLR, CART, SVR and ANN Techniques
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-70018-7_37
Reference10 articles.
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3. Yue, J.C., Chou, E.P., Hsieh, M.H., Hsiao, L.C.: A study of forecasting tennis matches via the Glicko model. PLoS ONE 17, e0266838 (2022). https://doi.org/10.1371/JOURNAL.PONE.0266838
4. Jhawar, S.: Predicting tennis match outcomes. In: 2022 International Conference on Futuristic Technologies, INCOFT 2022 (2022). https://doi.org/10.1109/INCOFT55651.2022.10094479
5. Lisi, F., Grigoletto, M.: Modeling and simulating durations of men’s professional tennis matches by resampling match features. J. Sports Anal. 7(2), 57–75 (2021)
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