Abstract
The growing demand for scientifically grounded and highly personalized fitness plans reveals the huge shortcomings of traditional recommender systems, which cannot overcome template-oriented methods and effectively cope with complex, dynamic user data. As a remedy for this shortcoming, this work utilizes a Large Language Model (LLM) augmented with a domain-specific knowledge graph to develop LLM-SPTRec, a novel framework for intelligent sports training plan generation. This model successfully integrates multi-source heterogeneous user data and enhances the personalization and scientific validity of recommendations by grounding the LLM’s generative process in an expert-elicited Sports Science Knowledge Graph (SSKG). Empirical results on a real-world dataset demonstrate that LLM-SPTRec surpasses traditional baselines—including collaborative filtering, sequential models, and general-purpose LLMs—on fundamental measures of plan coherence, goal relevance, and predicted user satisfaction. The findings of this research provide a new paradigm for the discipline of intelligent health by bridging the gap between big data analysis and expert knowledge in addition to providing a new direction for the overall field of applied AI by demonstrating that knowledge-based LLMs are capable of generating safe, effective, and scientific personal health recommendations.
Data availability
The datasets generated and/or analysed during the current study are not publicly available due data privacy but are available from the corresponding author on reasonable request.
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Disclaimer
LLM-SPTRec is a decision-support framework intended for educational and fitness enhancement purposes. It is not a replacement for clinical diagnosis or individualized medical advice from qualified healthcare professionals.
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Zhongliang He: Writing, Methodology, Formal analysis, Supervision, ValidationJiacheng Wang: Formal analysis, Supervision, ValidationBinggang Zhang: Supervision, ValidationYang Li: Supervision, Validation.
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He, Z., Wang, J., Zhang, B. et al. Knowledge-grounded large language model for personalized sports training plan generation. Sci Rep (2026). https://doi.org/10.1038/s41598-026-37075-z
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DOI: https://doi.org/10.1038/s41598-026-37075-z
