National Running Club Database: Assessing Collegiate Club Athletes' Cross Country Race Results
It addresses a gap in sports science by providing a large-scale dataset for non-elite runners, though it is incremental as it focuses on data collection and basic analysis rather than novel methods.
The paper introduces the National Running Club Database (NRCD), a dataset of 15,397 race results from 5,585 collegiate club athletes, and analyzes it to show that runners' improvement per day is more pronounced for those with slower initial times and higher racing frequency, with factors like course conditions standardized.
The National Running Club Database (NRCD) aggregates 15,397 race results of 5,585 athletes from the 2023 and 2024 cross country seasons. This paper introduces the NRCD dataset, which provides insights into individual athlete progressions, enabling data-driven decision-making. Analysis reveals that runners' improvement per calendar day for women, racing 6,000m, and men, racing 8,000m, is more pronounced in athletes with slower initial race times and those who race more frequently. Additionally, we factor in course conditions, including weather and elevation gain, to standardize improvement. While the NRCD shows a gender imbalance, 3,484 men vs. 2,101 women, the racing frequency between genders is comparable. This publication makes the NRCD dataset accessible to the research community, addressing a previous challenge where smaller datasets, often limited to 500 entries, had to be manually scraped from the internet. Focusing on club athletes rather than elite professionals offers a unique lens into the performance of real-world runners who balance competition with academics and other commitments. These results serve as a valuable resource for runners, coaches, and teams, bridging the gap between raw data and applied sports science.