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Measuring Consensus in Binary Forecasts: NFL Game Predictions

Author

Listed:
  • ChiUng Song

    () (Science and Technology Policy Institute)

  • Bryan L. Boulier

    () (Department of Economics The George Washington University)

  • Herman O. Stekler

    () (Department of Economics The George Washington University)

Abstract

Previous research on defining and measuring consensus (agreement) among forecasters has been concerned with evaluation of forecasts of continuous variables. This previous work is not relevant when the forecasts involve binary decisions: up-down or win-lose. In this paper we use Cohen¡¯s kappa coefficient, a measure of inter-rater agreement involving binary choices, to evaluate forecasts of National Football League games. This statistic is applied to the forecasts of 74 experts and 31 statistical systems that predicted the outcomes of games during two NFL seasons. We conclude that the forecasters, particularly the systems, displayed significant levels of agreement and that levels of agreement in picking game winners were higher than in picking against the betting line. There is greater agreement among statistical systems in picking game winners or picking winners against the line as the season progresses, but no change in levels of agreement among experts. High levels of consensus among forecasters are associated with greater accuracy in picking game winners, but not in picking against the line.

Suggested Citation

  • ChiUng Song & Bryan L. Boulier & Herman O. Stekler, 2008. "Measuring Consensus in Binary Forecasts: NFL Game Predictions," Working Papers 2008-006, The George Washington University, Department of Economics, Research Program on Forecasting.
    • Handle: RePEc:gwc:wpaper:2008-006
    as

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    File URL: https://www2.gwu.edu/~forcpgm/2008-006.pdf
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    References listed on IDEAS

    as
    1. Victor Zarnowitz & Louis A. Lambros, 1983. "Consensus and Uncertainty in Economic Prediction," NBER Working Papers 1171, National Bureau of Economic Research, Inc.
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    6. Song, ChiUng & Boulier, Bryan L. & Stekler, Herman O., 2007. "The comparative accuracy of judgmental and model forecasts of American football games," International Journal of Forecasting, Elsevier, vol. 23(3), pages 405-413.
    7. Gregory, Allan W. & Yetman, James, 2004. "The evolution of consensus in macroeconomic forecasting," International Journal of Forecasting, Elsevier, vol. 20(3), pages 461-473.
    8. Lahiri, Kajal & Teigland, Christie & Zaporowski, Mark, 1988. "Interest Rates and the Subjective Probability Distribution of Inflation Forecasts," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 20(2), pages 233-248, May.
    9. Gregory, Allan W & Smith, Gregor W & Yetman, James, 2001. "Testing for Forecast Consensus," Journal of Business & Economic Statistics, American Statistical Association, vol. 19(1), pages 34-43, January.
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    11. Schnader, M. H. & Stekler, H. O., 1991. "Do consensus forecasts exist?," International Journal of Forecasting, Elsevier, vol. 7(2), pages 165-170, August.
    12. Clements, Michael P., 2008. "Consensus and uncertainty: Using forecast probabilities of output declines," International Journal of Forecasting, Elsevier, vol. 24(1), pages 76-86.
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    Cited by:

    1. Leitner, Christoph & Zeileis, Achim & Hornik, Kurt, 2010. "Forecasting sports tournaments by ratings of (prob)abilities: A comparison for the EUROÂ 2008," International Journal of Forecasting, Elsevier, vol. 26(3), pages 471-481, July.
    2. repec:amu:wpaper:2013-04 is not listed on IDEAS

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