In this article a method is proposed for ball tracking using 100 Hz computer vision in a semi-automated foosball table. In this application the behavior of the ball is highly dynamic with speeds up to 10 m/s and frequent bounces occur against the sides of the table and the puppets. Moreover, in the overhead camera view of the field the ball is often fully or partially occluded and there are other objects present that resemble the ball. The table is semi-automated to enable single user game play. This article shows that it is possible to perform fast and robust ball tracking by combining efficient image processing algorithms with a priori knowledge of the stationary environment and position information of the automated rods. Key words: computer vision, automated foosball table, visual servoing, ball segmentation, object tracking, perspective projection, Kalman observer, real-time systems