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Estimating the Effect of the Red Card in Soccer: When to Commit an Offense in Exchange for Preventing a Goal Opportunity

Author

Listed:
  • Vecer Jan

    (Columbia University)

  • Kopriva Frantisek

    (CERGE-EI, Charles University and The Academy of Sciences, Prague, Czech Republic)

  • Ichiba Tomoyuki

    (Columbia University)

Abstract

We study the effect of the red card in a soccer game. A red card is given by a referee to signify that a player has been sent off following serious misconduct. The player who has been sent off must leave the game immediately and cannot be replaced during the game. His team must continue the game with one player fewer. We estimate the effect of the red card from betting data on the FIFA World Cup 2006 and Euro 2008, showing that the scoring intensity of the penalized team drops significantly, while the scoring intensity of the opposing team increases slightly. We show that a red card typically leads to a smaller number of goals scored during the game when a stronger team is penalized, but it can lead to an increased number of goals when a weaker team is punished. We also show when it is better to commit a red card offense in exchange for the prevention of a goal opportunity.

Suggested Citation

  • Vecer Jan & Kopriva Frantisek & Ichiba Tomoyuki, 2009. "Estimating the Effect of the Red Card in Soccer: When to Commit an Offense in Exchange for Preventing a Goal Opportunity," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(1), pages 1-20, January.
    • Handle: RePEc:bpj:jqsprt:v:5:y:2009:i:1:n:8
    DOI: 10.2202/1559-0410.1146
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    References listed on IDEAS

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    1. Forsythe, Robert & Forrest Nelson & George R. Neumann & Jack Wright, 1992. "Anatomy of an Experimental Political Stock Market," American Economic Review, American Economic Association, vol. 82(5), pages 1142-1161, December.
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    Cited by:

    1. Jakub Červený & Jan C. Ours & Martin A. Tuijl, 2018. "Effects of a red card on goal-scoring in World Cup football matches," Empirical Economics, Springer, vol. 55(2), pages 883-903, September.
    2. Feng Guanhao & Polson Nicholas & Xu Jianeng, 2016. "The market for English Premier League (EPL) odds," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 12(4), pages 167-178, December.
    3. Douglas N. VanDerwerken & Jacek Rothert & Brice M. Nguelifack, 2018. "Does the Threat of Suspension Curb Dangerous Behavior in Soccer? A Case Study From the Premier League," Journal of Sports Economics, , vol. 19(6), pages 759-785, August.
    4. Raphael Flepp & Tim Pawlowski & Travis Richardson, 2025. "Suspense and Surprise in European Football," Papers 2506.21253, arXiv.org.
    5. Travis Richardson & Georgios Nalbantis & Tim Pawlowski, 2023. "Emotional Cues and the Demand for Televised Sports: Evidence from the UEFA Champions League," Journal of Sports Economics, , vol. 24(8), pages 993-1025, December.
    6. A. C. Titman & D. A. Costain & P. G. Ridall & K. Gregory, 2015. "Joint modelling of goals and bookings in association football," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 178(3), pages 659-683, June.
    7. Sebastian del Bano Rollin & Zsolt Bihari & Tomaso Aste, 2018. "Risk-Neutral Pricing and Hedging of In-Play Football Bets," Papers 1811.03931, arXiv.org.
    8. Babatunde Buraimo & David Forrest & Ian G. McHale & J.D. Tena, 2020. "Unscripted Drama: Soccer Audience Response To Suspense, Surprise, And Shock," Economic Inquiry, Western Economic Association International, vol. 58(2), pages 881-896, April.
    9. Sarkar Sumit, 2018. "Paradox of crosses in association football (soccer) – a game-theoretic explanation," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 14(1), pages 25-36, March.
    10. Mark Richard & Jan Vecer, 2021. "Efficiency Testing of Prediction Markets: Martingale Approach, Likelihood Ratio and Bayes Factor Analysis," Risks, MDPI, vol. 9(2), pages 1-20, February.

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