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An automatic pitch type recognition system has been developed. It is difficult to determine the pitch type automatically from a baseball broadcast video, so the decision is currently made by specialists that have expertise and experience in baseball. We developed a system incorporating expertise of professionals. The system identifies pitch type, such as straight balls and curveballs, from single-view pitching sequences in a live baseball broadcast. It analyses ball trajectories by using automatic ball tracking and the catcherpsilas stance by tracking the mitt region as well as recognizing the ball speed numbers superimposed on the screen, and it classifies the pitch type using the random forests ensemble-learning algorithm. The system achieved about 90% recognition accuracy in the experiment.