In our previous blogs on pitch framing (Part 1, Part 2), we explored the ability of some machine learning techniques to capture nonlinear behavior and promised that by controlling for more factors (pitcher, umpire, etc.) we could improve our model. Within DataRobot, we reran our process from the previous blog posts, included handedness and pitch type in the…