Chronic Training Load
Chronic Training Load (CTL) is the exponentially weighted 42-day average of the Training Stress Score and is often labelled "fitness" in training software.
Definition
“Chronic Training Load” (CTL) is the exponentially weighted moving average of daily TSS values over a longer period, 42 days by default. Like TSS, ATL and TSB, the metric was developed by Andrew Coggan and TrainingPeaks and is displayed as “fitness” in the Performance Management Chart. It describes the load the body has adapted to over the past six weeks.
Why it matters
As a trend line, the CTL curve shows whether regular load is rising, stagnating or falling. Combined with the acute load ATL it yields the Training Stress Balance, the form curve.
The label “fitness” is misleading, though, because it is quickly read as readiness to perform. A rising curve only says that training load is increasing, a falling one that it is decreasing. A planned recovery week, for instance during a taper, lowers CTL purely mathematically, even though that is exactly when the best performance is due.
Sharp jumps in CTL are an indicator of overload. TrainingPeaks therefore recommends aligning planned sessions with the current CTL; the example assumes a CTL of 50.
| Session | TSS per session | Relation to CTL 50 |
|---|---|---|
| Hard workout | 75–100 | 50–100 % above the baseline |
| Moderate workout | 60–70 | roughly 25 % above the baseline |
| Easy workout | 35–40 | 10–25 % below the baseline |
Another problem lies in the purely mathematical nature of the calculation. Because we like to see the form curve rise, easy sessions, technique work, stretching and mobility get skipped in favour of those that push TSS and thus the supposed “fitness” upwards.
How obseed measures it
obseed calculates CTL from the TSS values of all recorded sessions, whether imported from a wearable or logged manually. The basis is the standard formula with a 42-day time constant:
CTL_today = CTL_yesterday + (TSS_today − CTL_yesterday) / 42Since TSS depends on your stored performance values, CTL is only as reliable as those values. obseed therefore recommends taking threshold values from metabolic diagnostics rather than an FTP test. An overestimated threshold pushes the TSS of every session down and makes CTL look systematically too low.
Example
An athlete starts a build block with a CTL of 50 and completes a hard session of 90 TSS on one day.
CTL_new = 50 + (90 − 50) / 42
= 50 + 0.95
= 50.95A single hard day raises CTL by just under one point. If he instead averages 90 TSS per day for two weeks, CTL climbs to around 61. Only at that scale does the change become visible as a trend, which underlines the character of CTL as a long-term measure.
References
- Allen, H. & Coggan, A.: “Training and Racing with a Power Meter”.
Categories
- Trainingssteuerung
- Datenanalyse