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Using Monte Carlo Simulation to Calculate Match Importance

Author

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  • Jiří LahviÄ ka
Abstract
This article presents a new method of calculating match importance. Match importance is defined as strength of relationship between the match result and a given season outcome. Probabilities of all necessary match result-season outcome combinations are estimated by Monte Carlo simulation. Using actual results of 12 seasons of English Premier League and betting odds, it is shown that both match result and season outcome predictions are realistic. The method provides results that are close to Jennett’s approach; however, it does not require ex post information and can be used for any type of season outcome.

Suggested Citation

  • Jiří LahviÄ ka, 2015. "Using Monte Carlo Simulation to Calculate Match Importance," Journal of Sports Economics, , vol. 16(4), pages 390-409, May.
    • Handle: RePEc:sae:jospec:v:16:y:2015:i:4:p:390-409
    DOI: 10.1177/1527002513490172
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    References listed on IDEAS

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    Cited by:

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    2. Lahvicka, Jiri, 2013. "Does Match Uncertainty Increase Attendance? A Non-Regression Approach," MPRA Paper 48571, University Library of Munich, Germany.
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    4. Brad R. Humphreys & Li Zhou, 2015. "The Louis–Schmelling Paradox and the League Standing Effect Reconsidered," Journal of Sports Economics, , vol. 16(8), pages 835-852, December.
    5. Jiří LahviÄ ka, 2015. "The Impact of Playoffs on Seasonal Uncertainty in the Czech Ice Hockey Extraliga," Journal of Sports Economics, , vol. 16(7), pages 784-801, October.

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