We consider the problem of localizing a moving ball from a single calibrated perspective image; after showing that ordinary algorithms fail in analyzing motion blurred scenes, we describe a theoretically-sound model for the blurred image of a ball. Then, we present an algorithm capable of recovering both the ball 3D position and its velocity. The algorithm is experimentally validated both on real and synthetic images.