For ball tracking, we apply a two stage algorithm. At the first stage, a ball image matching method is applied, finding all the candidate regions for the position of the ball in the field. At the second stage, the detected regions are analysed in relation with the dynamics of the previously detected ball candidates, and their similarity with regions in the previous frames, rejecting candidates when the current region is more similar to previous no-ball regions in comparison to previous ball regions. If the ball is occluded by players or camouflaged by field lines, we apply a new additional method for recovering the position of the ball. The main contributions of our method are: the incorporation of the ball distortion to the ball model, and a new algorithm for the detection of the ball in occlusion situations. We have tested our approach in real benchmark sequences, facing complex challenges related to occlusion, low resolution, distortion due to speed, and illumination problems, with very competitive results.