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Using Monte Carlo simulation to calculate match importance: the case of English Premier League

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  • Lahvicka, Jiri

Abstract

This paper presents a new method of calculating match importance (a common variable in sports attendance demand studies) using Monte Carlo simulation. Using betting odds and actual results of 12 seasons of English Premier League, it is shown that the presented method is based on realistic predictions of match results and season outcomes. The Monte Carlo method provides results closest to Jennett’s approach; however, it does not require ex-post information and can be used for any type of season outcome.

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File URL: http://mpra.ub.uni-muenchen.de/40998/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 40998.

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Date of creation: 01 Sep 2012
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Handle: RePEc:pra:mprapa:40998

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Keywords: sports attendance; match importance; seasonal uncertainty; Monte Carlo;

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  1. Men-Andri Benz & Leif Brandes & Egon Franck, 2006. "Do Soccer Associations Really Spend on a Good Thing? Empirical Evidence on Heterogeneity in the Consumer Response to Match Uncertainty of Outcome," Working Papers 0009, University of Zurich, Center for Research in Sports Administration (CRSA), revised 2008.
  2. Rodney J. Paul, 2003. "Variations in NHL Attendance," American Journal of Economics and Sociology, Wiley Blackwell, vol. 62(2), pages 345-364, 04.
  3. Jennett, Nicholas I, 1984. "Attendances, Uncertainty of Outcome and Policy in Scottish League Football," Scottish Journal of Political Economy, Scottish Economic Society, vol. 31(2), pages 176-98, June.
  4. Feddersen, Arne & Humphreys, Brad & Soebbing, Brian, 2012. "Cost Incentives in European Football," Working Papers 2012-13, University of Alberta, Department of Economics.
  5. Peel, David A & Thomas, Dennis A, 1992. "The Demand for Football: Some Evidence on Outcome Uncertainty," Empirical Economics, Springer, vol. 17(2), pages 323-31.
  6. Baimbridge, Mark & Cameron, Samuel & Dawson, Peter, 1996. "Satellite Television and the Demand for Football: A Whole New Ball Game?," Scottish Journal of Political Economy, Scottish Economic Society, vol. 43(3), pages 317-33, August.
  7. Ioannis Asimakopoulos & John Goddard, 2004. "Forecasting football results and the efficiency of fixed-odds betting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(1), pages 51-66.
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