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Attendance of ice hockey matches in the Czech Extraliga


  • Lahvicka, Jiri


This paper uses data about 3,640 matches played in the seasons 2000/01-2009/10 to explain individual match attendance of the top Czech ice hockey competition – the Extraliga. Some interesting results are that fans decide whether to attend based on the detailed information about the home team, but use just the easily observable information about the away team; that a match having no impact on the final season outcome is much less attended; that televising a match decreases attendances of all matches played on the same day, but there is no negative next-day effect; that both very good and very bad weather decreases attendance; and that if two home matches are played in a short time period, their attendance is lower with likely higher impact on the second match. Substitution of ice hockey with soccer is investigated on several different levels – while ice hockey and soccer are definitely long-term substitutes, there are mixed results for same-day substitution. Modernization of ice hockey arenas is identified as the key factor behind the almost 20% attendance growth in the analyzed period. This paper also presents a new realistic method of modeling seasonal uncertainty based on Monte Carlo simulation that does not rely on ex post information.

Suggested Citation

  • Lahvicka, Jiri, 2010. "Attendance of ice hockey matches in the Czech Extraliga," MPRA Paper 27653, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:27653

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    References listed on IDEAS

    1. Rodney J. Paul, 2003. "Variations in NHL Attendance," American Journal of Economics and Sociology, Wiley Blackwell, vol. 62(2), pages 345-364, April.
    2. Arabmazar, Abbas & Schmidt, Peter, 1982. "An Investigation of the Robustness of the Tobit Estimator to Non-Normality," Econometrica, Econometric Society, vol. 50(4), pages 1055-1063, July.
    3. Babatunde Buraimo, 2008. "Stadium attendance and television audience demand in English league football," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 29(6), pages 513-523.
    4. Dennis Coates & Thane Harrison, 2004. "Baseball Strikes and the Demand for Attendance," UMBC Economics Department Working Papers 04-101, UMBC Department of Economics.
    5. Dennis Coates & Thane Harrison, 2005. "Baseball Strikes and the Demand for Attendance," Journal of Sports Economics, , vol. 6(3), pages 282-302, August.
    6. Brian M. Mills & Jason A. Winfree & Mark S. Rosentraub & Ekaterina Sorokina, 2015. "Fan substitution between North American professional sports leagues," Applied Economics Letters, Taylor & Francis Journals, vol. 22(7), pages 563-566, May.
    7. 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 176-198, June.
    8. Jaume García & Plácido Rodríguez, 2002. "The Determinants of Football Match Attendance Revisited," Journal of Sports Economics, , vol. 3(1), pages 18-38, February.
    9. David Forrest & Rob Simmons & Stefan Szymanski, 2004. "Broadcasting, Attendance and the Inefficiency of Cartels," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 24(3), pages 243-265, May.
    10. 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 317-333, August.
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    12. Men-Andri Benz & Leif Brandes & Egon Franck, 2009. "Do Soccer Associations Really Spend On A Good Thing? Empirical Evidence On Heterogeneity In The Consumer Response To Match Uncertainty Of Outcome," Contemporary Economic Policy, Western Economic Association International, vol. 27(2), pages 216-235, April.
    13. Peter Kennedy, 2003. "A Guide to Econometrics, 5th Edition," MIT Press Books, The MIT Press, edition 5, volume 1, number 026261183x, January.
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    More about this item


    attendance demand; ice hockey; Czech Republic; seasonal uncertainty; Monte Carlo;

    JEL classification:

    • D12 - Microeconomics - - Household Behavior - - - Consumer Economics: Empirical Analysis
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • L83 - Industrial Organization - - Industry Studies: Services - - - Sports; Gambling; Restaurants; Recreation; Tourism

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