Retrospective Analysis of Training and Its Response in Marathon Finishers Based on Fitness App Data

Zrenner M, Heyde C, Duemler B, Dykman S, Roecker K, Eskofier B (2021)

Publication Type: Journal article

Publication year: 2021

Journal

Frontiers in Physiology Frontiers Media

Book Volume: 12

Article Number: 669884

DOI: 10.3389/fphys.2021.669884

Abstract

Objective: Finishing a marathon requires to prepare for a 42.2 km run. Current literature describes which training characteristics are related to marathon performance. However, which training is most effective in terms of a performance improvement remains unclear. Methods: We conducted a retrospective analysis of training responses during a 16 weeks training period prior to an absolved marathon. The analysis was performed on unsupervised fitness app data (Runtastic) from 6,771 marathon finishers. Differences in training volume and intensity between three response and three marathon performance groups were analyzed. Training response was quantified by the improvement of the velocity of 10 km runs Δv10 between the first and last 4 weeks of the training period. Response and marathon performance groups were classified by the 33.3rd and 66.6th percentile of Δv10 and the marathon performance time, respectively. Results: Subjects allocated in the faster marathon performance group showed systematically higher training volume and higher shares of training at low intensities. Only subjects in the moderate and high response group increased their training velocity continuously along the 16 weeks of training. Conclusion: We demonstrate that a combination of maximized training volumes at low intensities, a continuous increase in average running speed up to the aimed marathon velocity and high intensity runs ≤ 5 % of the overall training volume was accompanied by an improved 10 km performance which likely benefited the marathon performance as well. The study at hand proves that unsupervised workouts recorded with fitness apps can be a valuable data source for future studies in sport science.

Authors with CRIS profile

Markus Zrenner Machine Learning and Data Analytics Lab Björn Eskofier Machine Learning and Data Analytics Lab

Involved external institutions

Adidas AG DE Germany (DE) Runtastic GmbH AT Austria (AT) Hochschule Furtwangen DE Germany (DE)

How to cite

APA:

Zrenner, M., Heyde, C., Duemler, B., Dykman, S., Roecker, K., & Eskofier, B. (2021). Retrospective Analysis of Training and Its Response in Marathon Finishers Based on Fitness App Data. Frontiers in Physiology, 12. https://dx.doi.org/10.3389/fphys.2021.669884

MLA:

Zrenner, Markus, et al. "Retrospective Analysis of Training and Its Response in Marathon Finishers Based on Fitness App Data." Frontiers in Physiology 12 (2021).

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