Abstract
A probabilistic model of maximal mean performance in endurance sports is presented. The joint distribution of three variables namely interval length, average power, and average heart rate is modeled using Gaussian processes. The model allows for prediction of maximal average performances even based on data from sub-maximal efforts.
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Notes
- 1.
In case of cycling power is available for measurement by means of power meters; in case of, e.g., running, power can be estimated by running speed.
- 2.
E.g. assuming a simple hyperbolic relation \( HR \)-\( T \).
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Asteroth, A., Ludwig, M., Bach, K. (2020). Probabilistic Performance Profiling. In: Lames, M., Danilov, A., Timme, E., Vassilevski, Y. (eds) Proceedings of the 12th International Symposium on Computer Science in Sport (IACSS 2019). IACSS 2019. Advances in Intelligent Systems and Computing, vol 1028. Springer, Cham. https://doi.org/10.1007/978-3-030-35048-2_15
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