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ARAşTıRMA · MAKINE ÖğRENMESI arXiv:2509.10600 12 Eyl 2025 · v6

Faster Results from a Smarter Schedule: Reframing Collegiate Cross Country through Analysis of the National Running Club Database

Jonathan A. Karr, Ryan M. Fryer, Nitesh V. Chawla

YAYIN:12 Eyl 2025 ALAN:cs.CY OKUMA:2

Özet

Collegiate cross country teams often build their season schedules on intuition rather than evidence, partly because large-scale performance datasets were not publicly accessible prior to the National Running Club Database (NRCD). We analyze the comprehensive-era Cross Country subset of NRCD, 23,360 results from 7,056 athletes (2023-2025; >99% course/weather coverage). Under leakage control and temporal validation, race-result features do not support out-of-year forecasting of individual improvement (best men's R^2 = 0.044; women's -0.018), capturing only a small fraction of the outcome's reliability ceiling (approximately 0.23-0.28). Against this null, team race frequency associates with nationals placement (pooled RR = 2.09; GEE OR = 2.56/SD). Program-wide opportunity (roster depth; Effective Racing Opportunity) outranks a single workhorse's max race count cross-sectionally, but overall team depth for race count is controlled. Converted Only times (not adjusted for weather and elevation) overstate mean first-to-last gains by 15-21 s relative to Standardized. These results challenge coaching practices that treat schedule design as purely anecdotal and show how NRCD enables evidence-based decision-making in collegiate cross country.

Özetle: Collegiate cross country teams often build their season schedules on intuition rather than evidence, partly because large-scale performance datasets were not publicly accessible prior to the National Running Club Databa…

Özet

Collegiate cross country teams often build their season schedules on intuition rather than evidence, partly because large-scale performance datasets were not publicly accessible prior to the National Running Club Database (NRCD). We analyze the comprehensive-era Cross Country subset of NRCD, 23,360 results from 7,056 athletes (2023-2025; >99% course/weather coverage). Under leakage control and temporal validation, race-result features do not support out-of-year forecasting of individual improvement (best men's R^2 = 0.044; women's -0.018), capturing only a small fraction of the outcome's reliability ceiling (approximately 0.23-0.28). Against this null, team race frequency associates with nationals placement (pooled RR = 2.09; GEE OR = 2.56/SD). Program-wide opportunity (roster depth; Effective Racing Opportunity) outranks a single workhorse's max race count cross-sectionally, but overall team depth for race count is controlled. Converted Only times (not adjusted for weather and elevation) overstate mean first-to-last gains by 15-21 s relative to Standardized. These results challenge coaching practices that treat schedule design as purely anecdotal and show how NRCD enables evidence-based decision-making in collegiate cross country.

Orijinal Özet (İngilizce)

Collegiate cross country teams often build their season schedules on intuition rather than evidence, partly because large-scale performance datasets were not publicly accessible prior to the National Running Club Database (NRCD). We analyze the comprehensive-era Cross Country subset of NRCD, 23,360 results from 7,056 athletes (2023-2025; >99% course/weather coverage). Under leakage control and temporal validation, race-result features do not support out-of-year forecasting of individual improvement (best men's R^2 = 0.044; women's -0.018), capturing only a small fraction of the outcome's reliability ceiling (approximately 0.23-0.28). Against this null, team race frequency associates with nationals placement (pooled RR = 2.09; GEE OR = 2.56/SD). Program-wide opportunity (roster depth; Effective Racing Opportunity) outranks a single workhorse's max race count cross-sectionally, but overall team depth for race count is controlled. Converted Only times (not adjusted for weather and elevation) overstate mean first-to-last gains by 15-21 s relative to Standardized. These results challenge coaching practices that treat schedule design as purely anecdotal and show how NRCD enables evidence-based decision-making in collegiate cross country.

Kaynak: arXiv:2509.10600 · PDF

BibTeX

@article{karr2025faster,
  title   = {Faster Results from a Smarter Schedule: Reframing Collegiate Cross Country through Analysis of the National Running Club Database},
  author  = {Jonathan A. Karr and Ryan M. Fryer and Nitesh V. Chawla},
  journal = {arXiv preprint arXiv:2509.10600},
  year    = {2025},
  url     = {https://arxiv.org/abs/2509.10600}
}

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