Open Access

Feature Selection to Win the Point of ATP Tennis Players Using Rally Information


Cite

Clarke, S. R., & Dyte, D. (2000). Using official ratings to simulate major tennis tournaments. International transactions in operational research, 7(6), 585-594.10.1111/j.1475-3995.2000.tb00218.xSearch in Google Scholar

Clowes, S., Cohen, G. L., & Tomljanovic, L. (2002). Dynamic evaluation of conditional probabilities of winning a tennis match. In Sixth Australian Conference on Mathematics and Computers in Sport. UTS.Search in Google Scholar

de Araujo Fernandes, M. (2017). Using Soft Computing Techniques for Prediction of Winners in Tennis Matches. Machine Learning Research, 2(3), 86-98.Search in Google Scholar

Klaassen, F. J., & Magnus, J. R. (2003). Forecasting the winner of a tennis match. European Journal of Operational Research, 148(2), 257-267.10.1016/S0377-2217(02)00682-3Search in Google Scholar

Knottenbelt, W. J., Spanias, D., & Madurska, A. M. (2012). A common-opponent stochastic model for predicting the outcome of professional tennis matches. Computers & Mathematics with Applications, 64(12), 3820-3827.10.1016/j.camwa.2012.03.005Search in Google Scholar

Ma, S. M., Liu, C. C., Tan, Y., & Ma, S. C. (2013). Winning matches in Grand Slam men’s singles: An analysis of player performance-related variables from 1991 to 2008. Journal of sports sciences, 31(11), 1147-1155.10.1080/02640414.2013.77547223458278Search in Google Scholar

McHale, I., & Morton, A. (2011). A Bradley-Terry type model for forecasting tennis match results. International Journal of Forecasting, 27(2), 619-630.10.1016/j.ijforecast.2010.04.004Search in Google Scholar

Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., ... Vanderplas, J. (2011). Scikit-learn: Machine learning in Python. Journal of machine learning research, 12(Oct), 2825-2830.Search in Google Scholar

Sipko, M., & Knottenbelt, W. (2015). Machine learning for the prediction of professional tennis matches. MEng computing-final year project, Imperial College London.Search in Google Scholar

Wei, X., Lucey, P., Morgan, S., Reid, M., & Sridharan, S. (2016). The thin edge of the wedge:Accurately predicting shot outcomes in tennis using style and context priors. In Proceedings of the 10th Annu MIT Sloan Sport Anal Conf, Boston, MA, USA (pp.1-11).Search in Google Scholar

eISSN:
1684-4769
Language:
English
Publication timeframe:
2 times per year
Journal Subjects:
Computer Sciences, Databases and Data Mining, other, Sports and Recreation, Physical Education