To provide rich viewing experience and assist pitcher training, we propose an automatic baseball pitch overlay system in this paper. Given multiple pitching video sequences, this system detects and tracks the ball to construct ball trajectories. Because of occlusion, motion blur, and background noise, the ball usually cannot be detected successfully. We propose a series of processes like initial compensation and polynomial fitting to construct complete trajectories. To make the overlay results more appealing, different sequences are weighted differently, and different trajectories are intentionally drawn in different colors. We believe this would be the first fully-automatic pitch overlay system that only takes pitching videos as inputs. Source code is at \\https://github.com/chonyy/ML-auto-baseball-pitching-overlay.