arXiv:2610.07035v1 Announce Type: new Abstract: The IO500 benchmark provides a common basis for evaluating high-performance computing (HPC) storage systems, while its growing submission repository also offers an opportunity to study performance behavior across systems and time. This work presents a repository-scale characterization of 294 post-reset IO500 submissions from 116 sites spanning 2019--2025. We combine descriptive and temporal analysis with phase-level correlation, scale-sensitivity analysis, and benchmark-log examination to investigate how performance characteristics represented by individual benchmark phases relate to composite rankings. The results show strong relationships among phases measuring similar I/O behavior, but weaker and scale-sensitive relationships between bandwidth and metadata performance. Temporal and log-level analyses further reveal information that is not apparent from aggregate scores alone. These findings demonstrate the value of analyzing IO500 results beyond leader-board rankings and identify important considerations concerning system scale, benchmark execution, and repository provenance when using community benchmark data for comparative and longitudinal HPC performance analysis.