Forecasting National Football League Game Outcomes Relative to Betting Spreads

William Mallios
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William Mallios: California State University, Fresno

Journal of Gambling Business and Economics, 2012, vol. 6, issue 3, 1-16

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.

Keywords: sports gambling markets; gambling shocks; market inefficiencies; forecasting playoff games; cointegrated time processes; time-varying coefficients; adaptive drift modeling (search for similar items in EconPapers)
JEL-codes: L83 (search for similar items in EconPapers)
Date: 2012
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