Understanding Residuals Plots

I have a residuals plot:

Definitions: let's call blue_line the line that would exist if I were to draw a straight line by fitting to the blue dots (predictions).

My expectation is that if there were some features that contributed to y_real, blue_line would be parallel to dotted_red_line, but there might be any amount of noise centered around blue_line based on other features I'm not taking into account which contribute to y_real.

What can I make about the model's ability to predict y_real, here? And has the model fully fitted? The fact that blue_line is not quite vertical suggests to me that it's found at least something in the data to help with predictions, but if it's found osmething, why isn't it parallel to dotted red line?

My model is LightGBM, boosting_type: 'dart', objective: 'regression'.