NRCD: An Open Database of Collegiate Running with Unified Performance Standardization

Abstract:Collegiate running in the United States generates thousands of race results annually in cross country and track and field, yet no large-scale dataset has been publicly available for research. Existing websites such as this http URL, MileSplit, and TFRRS host results but do not support bulk download, restricting prior analyses to ~500 performances, often skewing studies toward male athletes. We introduce the National Running Club Database (NRCD), the first openly available collegiate running dataset at scale: 128,963 approved performances from 28,913 athletes across 1,336 meets in four sports (cross country (XC), indoor and outdoor track, and road races), 36.3% women, spanning 2004 through 2026. Within that single export, meets from August 2023 onward carry comprehensive course distance, elevation gain and loss, weather at race time, and track venue metadata (97.7% of XC rows with weather fields); earlier seasons back to 2004 are included with sparser metadata. NRCD is community-governed through open submission and expert approval and is maintained as a live database whose meet volume has grown yearly. We release a unified performance standardization framework that operationalizes established distance, elevation, and heat adjustments in one pipeline. Furthermore, we recommend gender-stratified modeling. On XC, full standardization lowers median within-athlete cross-meet variability by 51.0% (women) and 34.4% (men) versus raw times. We release the dataset and pipeline with a python package `nrcd' under FAIR principles, supporting longitudinal athlete modeling, environmental-confounder studies, and gender-equity research in collegiate sport.

Machine Learning (cs.LG); Computers and Society (cs.CY); Information Retrieval (cs.IR)

arXiv:2608.14776 [cs.LG]

(or arXiv:2608.14776v1 [cs.LG] for this version)

https://doi.org/10.48550/arXiv.2608.14776 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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