The standing long jump is a standard test for primary school students. It can be used to evaluate the development of basic sports skills of a child. This paper presents a system that can automatically detect the motion during a standing long jump from a video sequence. The silhouette of the jumper in the film is segmented from the background first for all frames. A stick model is applied to the silhouette found in the first frame. Then a GA-based search algorithm is used to find the stick models for the rest of the frames. The stick model points out the important joints of a person and can be used to represent the pose of the jumper in each frame. From the pose change in consecutive frames, we will be able to analyze the movement of the jumper.