@peter_michel your profiler has the hallmarks of highly correlated factors. The most prevalent being the almost vertical nature of several of your model lines. The other is that where you do see gray confidence bands more easily they look like bowties.
What this all leads to is that you have too many highly correlated factors in your model. You can check this a couple of ways. One is to use the Multivariate platform and put all of your continuous variables/factors in for test. You are looking for variables having a correlation coefficient closer to +1 or -1. Just a reminder, a given factor is completely correlated with itself and will show a value of +1 in blue. Negative correlations show in red. The advantage here is that you can usually tell which factors are correlated with each other and the Scatter Plot under the red hot spot is a good way to visualize the correlation
Using the Variance Inflation Factor (VIF) in your model fit platform will also direct you to highly correlated factors. A value above +10 is a good indication a given factor is correlated with another factor. If the multicollinearity is really high you can see VIF values reaching into the millions. You can turn on VIF by right clicking in the parameter estimates report, selecting Columns and then selecting VIF.
Finding the correlated factors and removing the one(s) with the highest VIF or correlation coefficients will clean up your model and the Profiler. This will change your fit statistics, but you will have more confidence that your model is not overfit or is fitting noise.
Hope this is helpful.
Best,
Bill