sksports.metrics.training_load_score

sksports.metrics.training_load_score(activity_power, mpa)

Training load score.

Grappe et al. proposes to compute the load of an activity by a weighted sum of the time spend in the different ESIE zones.

Read more in the User Guide.

Parameters:

activity_power : Series

A Series containing the power data from an activity.

mpa : float

Maximum power aerobic. Use metrics.ftp2mpa if you use the functional threshold power metric.

Returns:

tls_score: float

Training load score.

References

[1]	Grappe, F. “Cyclisme et optimisation de la performance: science et méthodologie de l’entraînement.” De Boeck Supérieur, 2009.

Examples

>>> from sksports.datasets import load_fit
>>> from sksports.io import bikeread
>>> from sksports.metrics import training_load_score
>>> ride = bikeread(load_fit()[0])
>>> mpa = 400
>>> tl_score = training_load_score(ride['power'], mpa)
>>> print('Training load score {:.2f}'.format(tl_score))
Training load score 74.90

Examples using sksports.metrics.training_load_score

Quantify Effort in Activity using Power