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Previsão da eficácia ofensiva do futebol profissional: Um caso Português

Author

Listed:
  • Caiado, Jorge
  • Vieira, Aníbal
  • Bonito, Ana
  • Reis, Carlos
  • Fernandes, Francisco

Abstract

The forecast plays an important role in the planning, the decision-making and control in any domain of activity, including the sportive phenomenon of the soccer. The experience has shown that the extrapolative or not casual models (univariate models), that use only the information of its past values to forecast the future, can often predict future with more accuracy than causal or multivariate models. In this paper, we model and forecast the offensive effectiveness of the soccer team Sport Lisbon and Benfica, in Portuguese soccer league, by using deterministic methods (linear trend, moving average, exponential smoothing, holt, naïve) and stochastic models (ARMA models, random walk). The model selection criteria used in our study were the mean squared error, the mean absolute error and the mean absolute percentage error based in a one-step forecast of the last three observations.

Suggested Citation

  • Caiado, Jorge & Vieira, Aníbal & Bonito, Ana & Reis, Carlos & Fernandes, Francisco, 2006. "Previsão da eficácia ofensiva do futebol profissional: Um caso Português," MPRA Paper 2185, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:2185
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    References listed on IDEAS

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    1. Gandar, John M. & Zuber, Richard A. & Lamb, Reinhold P., 2001. "The home field advantage revisited: a search for the bias in other sports betting markets," Journal of Economics and Business, Elsevier, vol. 53(4), pages 439-453.
    2. Roger Vergin, 2001. "Overreaction in the NFL point spread market," Applied Financial Economics, Taylor & Francis Journals, vol. 11(5), pages 497-509.
    3. Claudio Lucifora & Rob Simmons, 2003. "Superstar Effects in Sport," Journal of Sports Economics, , vol. 4(1), pages 35-55, February.
    4. Gray, Philip K & Gray, Stephen F, 1997. "Testing Market Efficiency: Evidence from the NFL Sports Betting Market," Journal of Finance, American Finance Association, vol. 52(4), pages 1725-1737, September.
    5. Andersson, Patric & Ekman, Mattias & Edman, Jan, 2003. "Forecasting the fast and frugal way: A study of performance and information-processing strategies of experts and non-experts when predicting the World Cup 2002 in soccer," SSE/EFI Working Paper Series in Business Administration 2003:9, Stockholm School of Economics.
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    More about this item

    Keywords

    Exponential smoothing; Soccer; Moving average; ARMA model; Forecast;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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