Abstract In the face of the current dilemma and predicament of students’ physical health, it has become inevitable to incorporate health education into the national education system, with the help of physical training to reshape cognition, establish beliefs, guide behavior, and other effective means, so as to achieve the fundamental purpose of improving the physical health of students. This paper takes college students’ physical health as the research object, carries out the research on efficient association rule mining algorithm for BMI index, uses Apriori association rule algorithm in R language data mining to carry out in-depth mining of physical health test data, and carries out in-depth comparative analysis and exploration of intrinsic information of physical test data of two academic years of 2022 grade in a school in a more detailed and in-depth way. A scientific guidance program for physical training is created using the collaborative filtering algorithm to support the high-quality development of college students’ physical fitness and health. The results of the study found that the correlation coefficient between physical training behavior and BMI index r = -0.753, confidence test value P = 0.0004 < 0.05, indicating that there is a significant negative correlation between students’ physical training behavior and BMI. That is, physical education and sports can significantly promote the physical health of college students, and ultimately, their BMI should fall within the normal range.