This study utilizes the Apriori algorithm for association rule mining, aiming to deeply explore the intrinsic connection between college students’ physical health and sports performance. The relevant definitions of association rule mining and the application process of Apriori algorithm in this study are elaborated in detail, including data preprocessing, frequent item set generation, and association rule extraction. Through empirical analysis, various combinations of physical fitness factors affecting college students’ athletic performance and the corresponding association rules are revealed. For example, under the condition of support degree of 0.598 and confidence level of 0.709, when male students’ “stiffness upward grade” is passing, their athletic performance is also passing. By mining the correlation rules between college students’ sports performance and physical health, it provides scientific basis and targeted suggestions for physical education and students’ health management in colleges and universities.