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Forecasting exact scores in National Football League games

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  • Baker, Rose D.
  • McHale, Ian G.

Abstract

The paper presents a point process model for predicting exact end-of-match scores in the premier league of American football, the National Football League. The hazards of scoring are allowed to vary with team statistics from previous games and/or the bookmaker point spread and over-under. The model is used to generate out-of-sample forecasts, which are evaluated using several criteria, including a Kelly betting strategy. In predicting the results of games, the model is marginally outperformed by the betting market. However, when it is used to forecast exact scores, the model proves to do at least as well as the market.

Suggested Citation

  • Baker, Rose D. & McHale, Ian G., 2013. "Forecasting exact scores in National Football League games," International Journal of Forecasting, Elsevier, vol. 29(1), pages 122-130.
    • Handle: RePEc:eee:intfor:v:29:y:2013:i:1:p:122-130
    DOI: 10.1016/j.ijforecast.2012.07.002
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    References listed on IDEAS

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    Cited by:

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    4. Marc Garnica-Caparrós & Daniel Memmert & Fabian Wunderlich, 2022. "Artificial data in sports forecasting: a simulation framework for analysing predictive models in sports," Information Systems and e-Business Management, Springer, vol. 20(3), pages 551-580, September.
    5. Wunderlich, Fabian & Memmert, Daniel, 2020. "Are betting returns a useful measure of accuracy in (sports) forecasting?," International Journal of Forecasting, Elsevier, vol. 36(2), pages 713-722.
    6. Yazan F. Roumani, 2023. "Sports analytics in the NFL: classifying the winner of the superbowl," Annals of Operations Research, Springer, vol. 325(1), pages 715-730, June.
    7. Singh, Aaditya & Scarf, Phil & Baker, Rose, 2023. "A unified theory for bivariate scores in possessive ball-sports: The case of handball," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1099-1112.
    8. Hubáček, Ondřej & Šír, Gustav, 2023. "Beating the market with a bad predictive model," International Journal of Forecasting, Elsevier, vol. 39(2), pages 691-719.

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