I have a model that produces the expected points of every football (soccer) team for the following season, given the results from the previous season (the model considers the number of goals scored/conceded by each team when playing at home/away, using a Poisson distribution to determine the outcome of every game in the next season). I also have the data for the actual points each team achieved in the second season.
Given the predicted points for the next season, and the actual points, is it possible to calculate how likely each team is to finish in each position, out of 28 teams? (i.e. likelihood of coming 1st, 2nd, ..., 28th)
My initial thought was to create a range of points for each table position (i.e. 130+ points for first, 120-129 points for second, so on) and calculate the likelihood of a team falling within this range. I don't know how to implement this however.
Any replies would be much appreciated!
A portion of the table of actual vs predicted points is below: