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The fact that self-organized physical education teaching systems in universities should have diversity and imbalance has been weakened, and we need to focus on the self-thinking, self-learning, and uncertain factors in the teaching process. The components of the entire teaching system are known as teaching elements. We cannot understand the integrity of teaching elements without understanding system theory. The teaching in physical education classes is the same way. This paper analyzes the elements and overall optimization of university self-organizing physical education teaching system using the methods of literature review and logical argumentation, starting from the perspective of holism and combining with the characteristics of physical education. The effectiveness and superiority of this model are tested by comparing sports performance data with ACOA (Ant Colony Optimization Algorithm) to optimize the sports video of SVM (Support Vector Machine). The findings show that the model can improve sports performance prediction accuracy, and the prediction results are more reliable, providing useful information for sports training.

Elements and Overall Optimization of University Self-Organizing Physical Education Teaching System Based on Holistic Theory