Abstract

 


 



The Penalty-Kick Game Under Incomplete Information


German Coloma


University of CEMA

May 1, 2012

University of CEMA Economics Serie Documentos de Trabajo No. 487

Abstract:     
This paper presents a model of the penalty-kick game between a soccer goalkeeper and a kicker, in which there is uncertainty about the kicker’s type (and there are two possible types of kicker). To find a solution for this game we use the concept of Bayesian equilibrium, and we find that, typically, one of the kicker’s types will play a mixed strategy while the other type will choose a pure strategy (or, sometimes, a “restricted mixed strategy”). The model has a simpler version in which the players can only choose between two strategies (right and left), and a more complex version in which they can also choose a third strategy (the center of the goal). Comparing the incomplete-information Bayesian equilibria with the corresponding complete-information Nash equilibria, we find that in all cases the expected scoring probability increases (so that, on average, the goalkeeper is worse off under incomplete information). The three-strategy model is also useful to explain why it could be optimal for a goalkeeper never to choose the center of the goal (although at the same time there were some kickers who always chose to shoot to the center).

Number of Pages in PDF File: 32

Keywords: soccer penalty kicks, mixed strategies, Bayesian equilibrium, incomplete information

JEL Classification: C72, L83

working papers series


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Date posted: July 25, 2012  

Suggested Citation

Coloma, German, The Penalty-Kick Game Under Incomplete Information (May 1, 2012). University of CEMA Economics Serie Documentos de Trabajo No. 487 . Available at SSRN: http://ssrn.com/abstract=2117476 or http://dx.doi.org/10.2139/ssrn.2117476

Contact Information

German Coloma (Contact Author)
University of CEMA ( email )
Department of Economics Cordoba 374 - Piso 7
1054 Buenos Aires
Argentina
+54 11 4314-2269 (Phone)
+54 11 4314-1654 (Fax)
Feedback to SSRN (Beta)


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