What monotony and strain are
· Training Feel
Two weeks with the same total load can be completely different experiences depending on how it is distributed. Monotony and strain, associated with the work of Carl Foster, are the attempt to put a number on that difference.
Monotony: how alike the days are
Monotony is the mean daily load divided by its standard deviation. If every day is roughly the same, the deviation is small and the ratio rises. If there are hard days, easy days and days off, the deviation grows and monotony falls.
One detail changes the result entirely: days without training count as zero and belong in the calculation. Leaving them out artificially raises the mean and lowers the deviation, so a week with two days off looks far more monotonous than it was. For the same reason it is better computed over a calendar week than a rolling window.
Strain: load penalised by monotony
Strain is the weekly load multiplied by monotony. The idea is simple: the same amount of work weighs more if it was spread evenly than if it had peaks and troughs.
It is an individual measure, not a team one. Multiplying the squad total by its monotony produces a number that describes no player at all: it grows with the number of athletes, not with what happened to them.
What to do with it
The useful reading is comparative. Monotony rising week on week with the same total load says the planning is flattening out, even though volume has not changed — and that usually happens without anyone deciding it, through an accumulation of similar sessions.
These are not daily metrics. They are weekly by construction, and their value lies in the trend across a mesocycle, not in any single week’s figure.
Training Feel computes each week’s monotony and strain from the sessions athletes already logged, counting rest days the way they should be counted.
See how it works