This paper studies the optimization analysis method of the volleyball league schedule based on a Support Vector Machine (SVM). The rational arrangement of the volleyball league schedule is crucial for successfully managing teams and leagues. In this study, the scheduling problem is divided into two key parts: team transitions and team schedules, and SVM's classification ability is used to solve these problems. Experimental results show that the SVM-based method performs well in various team quantity situations, especially in large-scale schedule arrangements. This method provides an innovative and effective way to optimize volleyball league schedules, improving the quality and fairness of matches while reducing travel costs for teams.