Characterization of Immediate Pressing Tactics in Soccer in the Age of Artificial Intelligence

Abstract

Abstract This paper focuses on the use of feature extraction techniques as well as parameter estimation to analyze the immediate pressing tactics in soccer games. The motion target detection method is used to capture the movements of the soccer player. By setting the rotation angle of the point cloud, the soccer movement action is represented in the form of a coordinate system. By combining the inter-frame difference method and setting the motion image threshold, the motion target can be obtained. Utilize Hu moments to extract the features of soccer motion. Combine the center of mass and velocity of soccer motion to reduce the error rate of motion feature extraction. Pairwise quaternions are utilized to represent soccer motion parameters to improve motion estimation. The results show that the soccer team has the greatest success rate of practicing immediate pressing tactics in 3s-4s, and the success rate of applying immediate pressing tactics after 4s is significantly lower. Team C has the highest success rate of huddling with defensive immediate pressing tactics, which reaches 56.1%. The success rate of huddling is closest to that of team A and team B, which are 43.54% and 43.97%, respectively.