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

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.

Longer Disciplined Tapers Improve Marathon Performance for Recreational Runners

“…Another consideration is the use of the fastest 10 km pace observed during training as a proxy for a runner's ability and its subsequent use in the estimation of finish-time benefits; a related approach was adopted by Zrenner et al ( 2021 ). It is not possible to verify whether an observed fastest 10 km pace is accurate for a given runner because it depends very much on the style of their training.…”

Racing Experiences of Recreational Distance Runners following Omnivorous, Vegetarian, and Vegan Diets (Part B)—Results from the NURMI Study (Step 2)

“…What remains unclear from the scientific evidence to date [ 18 , 27 , 32 , 33 , 34 , 35 , 36 , 37 , 38 ] is whether a running performance difference exists when including the vegan diet as an additional comparator group. Due to the vast influence of several different factors in running performance, such as genetics [ 39 ] or personal training behavior [ 40 , 41 ], observable diet type differences may be limited [ 36 , 37 ]. Previous population studies on long-distance recreational runners comparing omnivorous, vegetarian, and vegan diet types in performance have only examined a limited extent of training variables, such as weekly exercise frequency, running distance, durations, and/or professional support [ 32 , 33 , 35 ].…”