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Are differences in ranks good predictors for Grand Slam tennis matches?

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  • del Corral, Julio
  • Prieto-Rodríguez, Juan

Abstract

This paper tests whether the differences in rankings between individual players are good predictors for Grand Slam tennis outcomes. We estimate separate probit models for men and women using Grand Slam tennis match data from 2005 to 2008. The explanatory variables are divided into three groups: a player's past performance, a player's physical characteristics, and match characteristics. We estimate three alternative probit models. In the first model, all of the explanatory variables are included, whereas in the other two specifications, either the player's physical characteristics or the player's past performances are not considered. The accuracies of the different models are evaluated both in-sample and out-of-sample by computing Brier scores and comparing the predicted probabilities with the actual outcomes from the Grand Slam tennis matches from 2005 to 2008 and from the 2009 Australian Open. In addition, using bootstrapping techniques, we also evaluate the out-of-sample Brier scores for the 2005-2008 data.

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Bibliographic Info

Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 26 (2010)
Issue (Month): 3 (July)
Pages: 551-563

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Handle: RePEc:eee:intfor:v:26:y::i:3:p:551-563

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Web page: http://www.elsevier.com/locate/ijforecast

Related research

Keywords: Sports forecasting Probit models Prediction intervals Tennis Brier scores Bootstrapping;

References

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  1. Andersson, Patric & Edman, Jan & Ekman, Mattias, 2005. "Predicting the World Cup 2002 in soccer: Performance and confidence of experts and non-experts," International Journal of Forecasting, Elsevier, vol. 21(3), pages 565-576.
  2. Forrest, David & Goddard, John & Simmons, Robert, 2005. "Odds-setters as forecasters: The case of English football," International Journal of Forecasting, Elsevier, vol. 21(3), pages 551-564.
  3. Abrevaya, Jason, 2002. "Ladder tournaments and underdogs: lessons from professional bowling," Journal of Economic Behavior & Organization, Elsevier, vol. 47(1), pages 87-101, January.
  4. Lebovic, James H. & Sigelman, Lee, 2001. "The forecasting accuracy and determinants of football rankings," International Journal of Forecasting, Elsevier, vol. 17(1), pages 105-120.
  5. Klaassen F. J G M & 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, American Statistical Association, vol. 96, pages 500-509, June.
  6. Boulier, Bryan L. & Stekler, H. O., 1999. "Are sports seedings good predictors?: an evaluation," International Journal of Forecasting, Elsevier, vol. 15(1), pages 83-91, February.
  7. Forrest, David & Simmons, Robert, 2000. "Forecasting sport: the behaviour and performance of football tipsters," International Journal of Forecasting, Elsevier, vol. 16(3), pages 317-331.
  8. Goddard, John, 2005. "Regression models for forecasting goals and match results in association football," International Journal of Forecasting, Elsevier, vol. 21(2), pages 331-340.
  9. Boulier, Bryan L. & Stekler, H. O., 2003. "Predicting the outcomes of National Football League games," International Journal of Forecasting, Elsevier, vol. 19(2), pages 257-270.
  10. Klaassen, Franc J. G. M. & Magnus, Jan R., 2003. "Forecasting the winner of a tennis match," European Journal of Operational Research, Elsevier, vol. 148(2), pages 257-267, July.
  11. Ruth N. Bolton & Randall G. Chapman, 1986. "Searching for Positive Returns at the Track: A Multinomial Logit Model for Handicapping Horse Races," Management Science, INFORMS, vol. 32(8), pages 1040-1060, August.
  12. David Forrest & Ian Mchale, 2007. "Anyone for Tennis (Betting)?," The European Journal of Finance, Taylor & Francis Journals, vol. 13(8), pages 751-768.
  13. Ioannis Asimakopoulos & John Goddard, 2004. "Forecasting football results and the efficiency of fixed-odds betting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(1), pages 51-66.
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Cited by:
  1. Halkos, George & Tzeremes, Nickolaos, 2012. "Evaluating professional tennis players’ career performance: A Data Envelopment Analysis approach," MPRA Paper 41516, University Library of Munich, Germany.
  2. McHale, Ian & Morton, Alex, 2011. "A Bradley-Terry type model for forecasting tennis match results," International Journal of Forecasting, Elsevier, vol. 27(2), pages 619-630, April.
  3. Stefan M. Herzog & Ralph Hertwig, 2011. "The wisdom of ignorant crowds: Predicting sport outcomes by mere recognition," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 6(1), pages 58-72, February.

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