The overload of sports information resources has greatly increased the difficulty for users to choose resources. To solve this problem, this paper proposes a sports digital teaching resource recommendation model based on collaborative filtering algorithm to achieve the optimization of sports teaching mode in the context of big data and multimedia. Based on the detailed analysis of the teaching resource construction platform, the improved algorithm is applied to the teaching resource recommendation platform, and the algorithm effect is verified based on the collected data. The experimental data shows that the error of this method is significantly better than ID3 algorithm, the error is reduced by 26.55%, and the recall rate is 95.72%, which is 12.76% higher than ID3 algorithm. The introduction of personalized recommendation technology into the utilization of sports information resources can improve the efficiency and accuracy of users' access to resources and strengthen the adaptability to the continuous deconstruction and new integration of the higher education system.