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Forecasting national team medal totals at the Summer Olympic Games

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Author Info

  • Forrest, David
  • Sanz, Ismael
  • Tena, J.D.

Abstract

The paper reports the results of an exercise to forecast national team medal totals at the Beijing Olympic Games, 2008. Forecasts were released to the media before the competitions commenced. The starting point was an established statistical model based on a regression analysis of medal totals in earlier Games, with past performance and GDP among the principal covariates. However, we based our own forecasts on a model with additional regressors, including a measure of public spending on recreation. This adaptation is shown to have improved the forecasting performance. We also made subjective, judgemental adjustments before releasing our final public forecasts, and we demonstrate that this led to a further increase in accuracy. These final forecasts were successful in predicting the principal changes in medal shares relative to the 2004 Games, namely the surge in medals for China and Great Britain and the substantial fall in medals for Russia.

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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: 576-588

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Handle: RePEc:eee:intfor:v:26:y::i:3:p:576-588

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

Related research

Keywords: Sports forecasting Olympic Games Medals;

References

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  1. Sauer, Raymond D, et al, 1988. "Hold Your Bets: Another Look at the Efficiency of the Gambling Market for National Football League Games: Comment," Journal of Political Economy, University of Chicago Press, vol. 96(1), pages 206-13, February.
  2. Hon-Kwong Lui & Wing Suen, 2008. "Men, Money, And Medals: An Econometric Analysis Of The Olympic Games," Pacific Economic Review, Wiley Blackwell, vol. 13(1), pages 1-16, 02.
  3. Todd E. Clark & Michael W. McCracken, 2000. "Tests of Equal Forecast Accuracy and Encompassing for Nested Models," Econometric Society World Congress 2000 Contributed Papers 0319, Econometric Society.
  4. 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.
  5. Andrew B. Bernard & Meghan R. Busse, 2004. "Who Wins the Olympic Games: Economic Resources and Medal Totals," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 413-417, February.
  6. 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.
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Cited by:
  1. Terence C. Mills & Peter Dawson & Paul Downward, 2013. "Olympic news and attitudes towards the Olympics: A compositional time-series analysis of how sentiment is affected by events," University of East Anglia Applied and Financial Economics Working Paper Series 046, School of Economics, University of East Anglia, Norwich, UK..
  2. Wladimir Andreff, 2012. "Is Hosting the Games Enough to Win? A predictive economic model of medal wins at 2014 Winter Olympics," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00794057, HAL.

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