Article
Purpose. To identify patterns of age-related dynamics of training activity parameters – mean road gradient, total duration of work, and mean speed – in foreign road cyclists based on digital footprint data and to substantiate these parameters as components of a structural-functional model of long-term training.
Methods and organization of the research. The study was based on open-access Strava data reflecting the recorded portion of training activity of male and female athletes over a full season. The unit of observation was an annual dataset of an individual athlete’s training activity. The analysis was conducted using the GTV approach, including assessment of mean road gradient (G), total duration of training activity (T), mean speed (V), and the number of recorded training activities.
Research results and their discussion. The most pronounced age-related dynamics were associated with an increase in total training duration, the number of recorded training activities, and mean speed. The G parameter changed to a lesser extent compared with T and V; however, it reached relatively high values already in younger age groups and subsequently varied within a limited range. This indicates different age sensitivity of the GTV parameters: T and V reflect the main age-related changes in training activity, whereas G represents a stable characteristic of the training environment.
Conclusion. The digital footprint of training activity can be considered an empirical basis for analyzing long-term training in road cycling, while the GTV approach can serve as a tool for formalized assessment of age-related dynamics in training activity.
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