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Forecasting National Football League Game Outcomes Relative to Betting Spreads

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  • William Mallios

    (California State University, Fresno)

Abstract

Cointegrated time processes measuring NFL playoff game performances relative to the betting spreads are graphed in terms of candlestick charts and forecast in terms of autoregressive systems with time varying coefficients. Coefficients are modeled in terms of linear regressions on lagged shocks. Estimation is non Bayesian. Forecasts provide measures of market efficiency/inefficiency and outcome volatility. Risk assessment utilizes GARCH-type modeling in estimating volatility. Applications are presented for the New York Giants 2012 playoff games based on a data backlog of three years.

Suggested Citation

  • William Mallios, 2012. "Forecasting National Football League Game Outcomes Relative to Betting Spreads," Journal of Gambling Business and Economics, University of Buckingham Press, vol. 6(3), pages 1-16, December.
    • Handle: RePEc:buc:jgbeco:v:6:y:2012:i:3:p:1-16
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    References listed on IDEAS

    as
    1. Figlewski, Stephen, 1979. "Subjective Information and Market Efficiency in a Betting Market," Journal of Political Economy, University of Chicago Press, vol. 87(1), pages 75-88, February.
    2. Johansen, Soren, 1995. "Likelihood-Based Inference in Cointegrated Vector Autoregressive Models," OUP Catalogue, Oxford University Press, number 9780198774501.
    3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    4. Engle, Robert & Granger, Clive, 2015. "Co-integration and error correction: Representation, estimation, and testing," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 39(3), pages 106-135.
    5. Vaughan Williams, Leighton, 1999. "Information Efficiency in Betting Markets: A Survey," Bulletin of Economic Research, Wiley Blackwell, vol. 51(1), pages 1-30, January.
    6. Ali, Mukhtar M, 1979. "Some Evidence of the Efficiency of a Speculative Market," Econometrica, Econometric Society, vol. 47(2), pages 387-392, March.
    7. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    8. Gwilym M. Jenkins & Athar S. Alavi, 1981. "Some Aspects Of Modelling And Forecasting Multivariate Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 2(1), pages 1-47, January.
    9. William Mallios, 2012. "Dynamic Modeling Forecasts Of Equity Price Movements In Cases Of Insider Trading," Journal of Prediction Markets, University of Buckingham Press, vol. 6(1), pages 1-30.
    10. P. Tryfos & S. Casey & S. Cook & G. Leger & B. Pylypiak, 1984. "The Profitability of Wagering on NFL Games," Management Science, INFORMS, vol. 30(1), pages 123-132, January.
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    More about this item

    Keywords

    sports gambling markets; gambling shocks; market inefficiencies; forecasting playoff games; cointegrated time processes; time-varying coefficients; adaptive drift modeling;
    All these keywords.

    JEL classification:

    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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