The first part of this series took a look at the GS match rating model. The post described, how you are able to identify a non-linear relationship between the predictor variables and the outcome variable. The same methods will now be applied to the PPG match rating model, so that we are able to compare the two different polynomial regression models. On top, I want to show, how you are able to figure out, whether outliers in your data have an influence on your regression model.
The next 10 match days are played in the German Bundesliga and so it is time for the next summary of the current betting history of my Poisson prediction model. During my summary about the first 10 match days I faced a really big loss. This trend continued also for the next match days, but some interesting observations can be made.