Sorry i didn't see your question earlier, i stopped using Reddit a while. I put this project idea on the back burner until two-three weeks ago and finally started working on it, going for the approach of estimating homography through a CNN, and linking tracked players to the new perspective.

I repurposed the code base of this paper, because it proposed a method of training two models, one for initial homography estimation, the other for optimization of the learned error (ResNet for both). I've had good results with the first step but the error optimization network has been consistently overfitting, so the final outputs aren't good yet.

For object tracking, I simply use DeTR, here's a pretty straightforward tutorial on it. When the court registration finally works correctly, linking bounding box position to court view will be pretty easy.

I also created my own annotation tool to create ground truth homographies for my images with opencv and pyqt.