For a project, I am looking for idea to model for the distribution of corners in football matches. I know that the number of goals can be model by a Poisson distribution, but for the number of corners, the distribution has
 larger tails. I think it is partly due to the fact that after a corner, the ball is put back in the game on one extrema of the field and this makes the probability of a second corner more likely. Would any of you have an idea of a model I could use?

**Precisions on the model I plan to use**
My initial idea  is to adapt the [Maher Model][1] for the number of goals in soccer matches.  In this model the number of corners of scored by team $T$ when playing vs team $T'$ is assumed to follow a Poisson distribution with Parameter $a_T d_{T'}$ where $a_T$ and $d_T$ are the attack and defense scores of team $T$ which are estimated from the data using maximum likelihood.

I am looking for a distribution different from the Poisson distribution (fatter tails) which generalizes the Maher model to the distribution of corners. A distribution for which estimating the parameters via maximal likelihood is possible would be perfect. 


  [1]: http://www.90minut.pl/misc/maher.pdf