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Sports forecasting

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  • Vaughan Williams, Leighton
  • Stekler, Herman O.

Abstract

A great amount of effort is spent in forecasting the outcome of sporting events, but few papers have focused exclusively on the characteristics of sports forecasts. Rather, many papers have been written about the efficiency of sports betting markets. As it turns out, it is possible to derive considerable information about the forecasts and the forecasting process from the studies that tested the markets for economic efficiency. Moreover, the huge number of observations provided by betting markets makes it possible to obtain robust tests of various forecasting hypotheses. This paper is concerned with a number of forecasting topics in horse racing and several team sports. The first topic involves the type of forecast that is made: picking a winner or predicting whether a particular team beats the point spread. Different evaluation procedures will be examined and alternative forecasting methods (models, experts, and the market) will be compared. The paper also examines the evidence about the existence of biases in the forecasts and concludes with the applicability of these results to forecasting in general.

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File URL: http://www.sciencedirect.com/science/article/B6V92-4YB27G9-1/2/b4c99d656d078b1e6789593f40ef10b7
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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: 445-447

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Handle: RePEc:eee:intfor:v:26:y::i:3:p:445-447

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

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References

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  1. Steven Caudill & Norman Godwin, 2002. "Heterogeneous skewness in binary choice models: Predicting outcomes in the men's NCAA basketball tournament," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(7), pages 991-1001.
  2. David J. Berri, 1999. "Who is 'most valuable'? Measuring the player's production of wins in the National Basketball Association," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 411-427.
  3. Crafts, Nicholas F R, 1985. "Some Evidence of Insider Knowledge in Horse Race Betting in Britain," Economica, London School of Economics and Political Science, vol. 52(27), pages 295-304, August.
  4. 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.
  5. 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.
  6. Camerer, Colin F, 1989. "Does the Basketball Market Believe in the 'Hot Hand'?," American Economic Review, American Economic Association, vol. 79(5), pages 1257-61, December.
  7. Brown, William O & Sauer, Raymond D, 1993. " Fundamentals or Noise? Evidence from the Professional Basketball Betting Market," Journal of Finance, American Finance Association, vol. 48(4), pages 1193-1209, September.
  8. Dare, William H. & MacDonald, S. Scott, 1996. "A generalized model for testing the home and favorite team advantage in point spread markets," Journal of Financial Economics, Elsevier, vol. 40(2), pages 295-318, February.
  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. 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.
  11. Ron Bird & Michael McCrae, 1987. "Tests of the Efficiency of Racetrack Betting Using Bookmaker Odds," Management Science, INFORMS, vol. 33(12), pages 1552-1562, December.
  12. Brown, William O & Sauer, Raymond D, 1993. "Does the Basketball Market Believe in the Hot Hand? Comment," American Economic Review, American Economic Association, vol. 83(5), pages 1377-86, December.
  13. Fiona Carmichael & Dennis Thomas & Robert Ward, 2000. "Team performance: the case of English Premiership football," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 21(1), pages 31-45.
  14. Busche, Kelly & Hall, Christopher D, 1988. "An Exception to the Risk Preference Anomaly," The Journal of Business, University of Chicago Press, vol. 61(3), pages 337-46, July.
  15. James D. Dana & Michael M. Knetter, 1994. "Learning and Efficiency in a Gambling Market," Management Science, INFORMS, vol. 40(10), pages 1317-1328, October.
  16. Avery, Christopher & Chevalier, Judith, 1999. "Identifying Investor Sentiment from Price Paths: The Case of Football Betting," The Journal of Business, University of Chicago Press, vol. 72(4), pages 493-521, October.
  17. William Dare & John Gandar & Richard Zuber & Robert Pavlik, 2005. "In search of the source of informed trader information in the college football betting market," Applied Financial Economics, Taylor & Francis Journals, vol. 15(3), pages 143-152.
  18. William Dare & A. Steven Holland, 2004. "Efficiency in the NFL betting market: modifying and consolidating research methods," Applied Economics, Taylor & Francis Journals, vol. 36(1), pages 9-15.
  19. Dixon, Mark J. & Pope, Peter F., 2004. "The value of statistical forecasts in the UK association football betting market," International Journal of Forecasting, Elsevier, vol. 20(4), pages 697-711.
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