Voir la notice de l'article provenant de la source Library of Science
@article{IJAMCS_2021_31_3_a11, author = {\v{S}ar\v{c}evi\'c, Ana and Vrani\'c, Mihaela and Pintar, Damir}, title = {A combinatorial approach in predicting the outcome of tennis matches}, journal = {International Journal of Applied Mathematics and Computer Science}, pages = {525--538}, publisher = {mathdoc}, volume = {31}, number = {3}, year = {2021}, language = {en}, url = {http://geodesic.mathdoc.fr/item/IJAMCS_2021_31_3_a11/} }
TY - JOUR AU - Šarčević, Ana AU - Vranić, Mihaela AU - Pintar, Damir TI - A combinatorial approach in predicting the outcome of tennis matches JO - International Journal of Applied Mathematics and Computer Science PY - 2021 SP - 525 EP - 538 VL - 31 IS - 3 PB - mathdoc UR - http://geodesic.mathdoc.fr/item/IJAMCS_2021_31_3_a11/ LA - en ID - IJAMCS_2021_31_3_a11 ER -
%0 Journal Article %A Šarčević, Ana %A Vranić, Mihaela %A Pintar, Damir %T A combinatorial approach in predicting the outcome of tennis matches %J International Journal of Applied Mathematics and Computer Science %D 2021 %P 525-538 %V 31 %N 3 %I mathdoc %U http://geodesic.mathdoc.fr/item/IJAMCS_2021_31_3_a11/ %G en %F IJAMCS_2021_31_3_a11
Šarčević, Ana; Vranić, Mihaela; Pintar, Damir. A combinatorial approach in predicting the outcome of tennis matches. International Journal of Applied Mathematics and Computer Science, Tome 31 (2021) no. 3, pp. 525-538. http://geodesic.mathdoc.fr/item/IJAMCS_2021_31_3_a11/
[1] [1] Albright, S.C. (1993). A statistical analysis of hitting streaks in baseball, Journal of the American Statistical Association 88(424): 1175–1183.
[2] [2] Attali, Y. (2013). Perceived hotness affects behavior of basketball players and coaches, Psychological Science 24(7): 1151–1156.
[3] [3] Baker, R.D. and McHale, I.G. (2014). A dynamic paired comparisons model: Who is the greatest tennis player?, European Journal of Operational Research 236(2): 677–684.
[4] [4] Baker, R.D. and McHale, I.G. (2017). An empirical Bayes model for time-varying paired comparisons ratings: Who is the greatest women’s tennis player?, European Journal of Operational Research 258(1): 328–333.
[5] [5] Ballı, S. and Korukoğlu, S. (2014). Development of a fuzzy decision support framework for complex multi-attribute decision problems: A case study for the selection of skilful asketball players, Expert Systems 31(1): 56–69.
[6] [6] Barnett, T. and Brown, A. (2012). The Mathematics of Tennis, http://www.strategicgames.com.au/.
[7] [7] Barnett, T., Brown, A. and Clarke, S. (2006). Developing a model that reflects outcomes of tennis matches, Proceedings of the 8th Australasian Conference on Mathematics and Computers in Sport, Coolangatta, Australia, pp. 3–5.
[8] [8] Barnett, T. and Clarke, S.R. (2005). Combining player statistics to predict outcomes of tennis matches, IMA Journal of Management Mathematics 16(2): 113–120.
[9] [9] Barnett, T.J. and Clarke, S.R. (2002). Using Microsoft Excel to model a tennis match, 6th Conference on Mathematics and Computers in Sport, Queensland, Australia, pp. 63–68.
[10] [10] Boulier, B.L. and Stekler, H.O. (1999). Are sports seedings good predictors? An evaluation, International Journal of Forecasting 15(1): 83–91.
[11] [11] Boulier, B.L. and Stekler, H.O. (2003). Predicting the outcomes of national football league games, International Journal of Forecasting 19(2): 257–270.
[12] [12] Bradley, R.A. and Terry, M.E. (1952). Rank analysis of incomplete block designs. I: The method of paired comparisons, Biometrika 39(3/4): 324–345.
[13] [13] Carbone, J., Corke, T. and Moisiadis, F. (2016). The rugby league prediction model: Using an Elo-based approach to predict the outcome of National Rugby League (NRL) matches, International Educational Scientific Research Journal 2(5): 26–30.
[14] [14] Carrari, A., Ferrante, M. and Fonseca, G. (2017). A new Markovian model for tennis matches, Electronic Journal of Applied Statistical Analysis 10(3): 693–711.
[15] [15] Chang, J.C. (2019). Predictive Bayesian selection of multistep Markov chains, applied to the detection of the hot hand and other statistical dependencies in free throws, Royal Society Open Science 6(3): 182174.
[16] [16] Clarke, S.R. and Dyte, D. (2000). Using official ratings to simulate major tennis tournaments, International Transactions in Operational Research 7(6): 585–594.
[17] [17] Croucher, J.S. (1986). The conditional probability of winning games of tennis, Research Quarterly for Exercise and Sport 57(1): 23–26.
[18] [18] Dadelo, S., Turskis, Z., Zavadskas, E.K. and Dadeliene, R. (2014). Multi-criteria assessment and ranking system of sport team formation based on objective-measured values of criteria set, Expert Systems with Applications 41(14): 6106–6113.
[19] [19] Dangauthier, P., Herbrich, R., Minka, T. and Graepel, T. (2007). Trueskill through time: Revisiting the history of chess, Advances in Neural Information Processing Systems 20: 337–344.
[20] [20] Dietl, H. and Nesseler, C. (2017). Momentum in tennis: Controlling the match, UZH Business Working Paper Series, University of Zurich, Zurich.
[21] [21] EGBA (2020). EU Market: Gambling is becoming more and more an online activity, https://www.egba.eu/eu-market/.
[22] [22] Elo, A.E. (1978). The Rating of Chessplayers, Past and Present, Arco Pub., New York.
[23] [23] Gilovich, T., Vallone, R. and Tversky, A. (1985). The hot hand in basketball: On the misperception of random sequences, Cognitive Psychology 17(3): 295–314.
[24] [24] Glickman, M.E. (1999). Parameter estimation in large dynamic paired comparison experiments, Journal of the Royal Statistical Society: Series C (Applied Statistics) 48(3): 377–394.
[25] [25] Glickman, M.E. (2001). Dynamic paired comparison models with stochastic variances, Journal of Applied Statistics 28(6): 673–689.
[26] [26] Green, B. and Zwiebel, J. (2017). The hot-hand fallacy: Cognitive mistakes or equilibrium adjustments? Evidence from major league baseball, Management Science 64(11): 5315–5348.
[27] [27] Hvattum, L.M. and Arntzen, H. (2010). Using Elo ratings for match result prediction in association football, International Journal of Forecasting 26(3): 460–470.
[28] [28] Iso-Ahola, S.E. and Mobily, K. (1980). Psychological momentum: A phenomenon and an empirical (unobtrusive) validation of its influence in a competitive sport tournament, Psychological Reports 46(2): 391–401.
[29] [29] Keller, J.B. (1984). Probability of a shutout in racquetball, SIAM Review 26(2): 267–268.
[30] [30] Klaassen, F.J. and Magnus, J.R. (2001). Are points in tennis independent and identically distributed? Evidence from a dynamic binary panel data model, Journal of the American Statistical Association 96(454): 500–509.
[31] [31] Klaassen, F.J. and Magnus, J.R. (2003). Forecasting the winner of a tennis match, European Journal of Operational Research 148(2): 257–267.
[32] [32] Knottenbelt, W.J., Spanias, D. and 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.
[33] [33] Kovalchik, S.A. (2016). Searching for the goat of tennis win prediction, Journal of Quantitative Analysis in Sports 12(3): 127–138.
[34] [34] Kovalchik, S. and Reid, M. (2019). A calibration method with dynamic updates for within-match forecasting of wins in tennis, International Journal of Forecasting 35(2): 756–766.
[35] [35] Lebovic, J.H. and Sigelman, L. (2001). The forecasting accuracy and determinants of football rankings, International Journal of Forecasting 17(1): 105–120.
[36] [36] Leitner, C., Zeileis, A. and Hornik, K. (2010). Forecasting sports tournaments by ratings of (prob) abilities: A comparison for the Euro 2008, International Journal of Forecasting 26(3): 471–481.
[37] [37] Liu, Y. (2001). Random walks in tennis, Missouri Journal of Mathematical Sciences 13(3): 1–9.
[38] [38] Martin, D.E. (2006). A recursive algorithm for computing the distribution of the number of successes in higher-order Markovian trials, Computational Statistics Data Analysis 50(3): 604–610.
[39] [39] McHale, I. and Morton, A. (2011). A Bradley–Terry type model for forecasting tennis match results, International Journal of Forecasting 27(2): 619–630.
[40] [40] Morris, B., Bialik, C. and Boice, J. (2016). How we’re forecasting the 2016 US Open, https://fivethirtyeight.com/features/how-were-forecasting-the-2016-us-open/.
[41] [41] Newton, P.K. and Aslam, K. (2009). Monte Carlo tennis: A stochastic Markov chain model, Journal of Quantitative Analysis in Sports 5(3): 1–44.
[42] [42] Newton, P.K. and Keller, J.B. (2005). Probability of winning at tennis. I: Theory and data, Studies in Applied Mathematics 114(3): 241–269.
[43] [43] O’Malley, A.J. (2008). Probability formulas and statistical analysis in tennis, Journal of Quantitative Analysis in Sports 4(2): 1–23.
[44] [44] Percy, D.F. (2015). Strategy selection and outcome prediction in sport using dynamic learning for stochastic processes, Journal of the Operational Research Society 66(11): 1840–1849.
[45] [45] Pollard, G. (1983). An analysis of classical and tie-breaker tennis, Australian Journal of Statistics 25(3): 496–505.
[46] [46] Radicchi, F. (2011). Who is the best player ever? A complex network analysis of the history of professional tennis, PloS ONE 6(2): e17249.
[47] [47] Renick, J. (1976). Optimal strategy at decision points in singles squash, Research Quarterly. American Alliance for Health, Physical Education and Recreation 47(3): 562–568.
[48] [48] Ryall, R. and Bedford, A. (2010). An optimized ratings-based model for forecasting Australian rules football, International Journal of Forecasting 26(3): 511–517.
[49] [49] Šarčević, A., Pintar, D., Vranić, M. and Gojsalić, A. (2021). Modeling in-match sports dynamics using the evolving probability method, Applied Sciences 11(10): 4429.
[50] [50] Schutz, R.W. (1970). A mathematical model for evaluating scoring systems with specific reference to tennis, Research Quarterly: American Association for Health, Physical Education and Recreation 41(4): 552–561.
[51] [51] Silver, N. and Fischer-Baum, R. (2015). How we calculate NBA Elo ratings, https://fivethirtyeight.com/features/how-we-calculate-nba-elo-rating s/.
[52] [52] Spanias, D. and Knottenbelt, W. J. (2013). Predicting the outcomes of tennis matches using a low-level point model, IMA Journal of Management Mathematics 24(3): 311–320.
[53] [53] Tversky, A. and Gilovich, T. (1989). The cold facts about the “hot hand” in basketball, Chance 2(1): 16–21.
[54] [54] Wetzels, R., Tutschkow, D., Dolan, C., Van der Sluis, S., Dutilh, G. and Wagenmakers, E.-J. (2016). A Bayesian test for the hot hand phenomenon, Journal of Mathematical Psychology 72: 200–209.
[55] [55] Wozniak, J. (2011). Inferring tennis match progress from in-play betting odds, Project report, Imperial College London, London.