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?

EDITPrecisions on the model I plan to use I realized reading the comment that my first message was not precise enough. I do not have a specific distribution in mind, myMy initial idea is to adapt the Maher modelMaher Model 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 followedfollow 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 macimummaximum likelihood.

To answer one question from the comment; from there, I am looking for a distribution different from the Poisson distribution (fatter tails) which generalizes suchthe Maher model to the distribution of corners. A distribution for which estimating the parameters via maximal likelihood is possible would be perfect.

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?

EDIT I realized reading the comment that my first message was not precise enough. I do not have a specific distribution in mind, my initial idea is to adapt the Maher model for the number of goals in soccer matches. In this model the number of corners of team $$T$$ vs team $$T'$$ is assumed to followed 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 macimum likelihood.

To answer one question from the comment; from there, I am looking for a distribution different from the Poisson distribution which generalizes such model to the distribution of corners. A distribution for which estimating the parameters via maximal likelihood is possible would be perfect.

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 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.

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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?

EDIT I realized reading the comment that my first message was not precise enough. I do not have a specific distribution in mind, my initial idea is to adapt the Maher model for the number of goals in soccer matches. In this model the number of corners of team $$T$$ vs team $$T'$$ is assumed to followed 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 macimum likelihood.

To answer one question from the comment; from there, I am looking for a distribution different from the Poisson distribution which generalizes such model to the distribution of corners. A distribution for which estimating the parameters via maximal likelihood is possible would be perfect.

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?

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?

EDIT I realized reading the comment that my first message was not precise enough. I do not have a specific distribution in mind, my initial idea is to adapt the Maher model for the number of goals in soccer matches. In this model the number of corners of team $$T$$ vs team $$T'$$ is assumed to followed 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 macimum likelihood.

To answer one question from the comment; from there, I am looking for a distribution different from the Poisson distribution which generalizes such model to the distribution of corners. A distribution for which estimating the parameters via maximal likelihood is possible would be perfect.

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# Modeling the number of corners in soccer

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?