Foster Monotony & Strain Index Calculator
DeclaredFostermonotonymean/POPULATIONSDandstrainΣload×monotony,nophysiologicalovertrainingdiagnosis. Actual matched calibration,units,edition,geometry/measurement and model applicability independently established;not hearing/structural safety,compliance or universal perceptual prediction.
Description
Training monotony compares mean daily load with its variation; strain combines monotony with total load.
Training monotony compares mean daily load with its variation; strain combines monotony with total load.1
Include rest-day zeros and keep the load definition consistent across the recorded period.
When to use Foster Monotony & Strain Index Calculator
Use this tool to apply the stated foster monotony & strain index calculator operation with an explicit input and unit basis.
How to use Foster Monotony & Strain Index Calculator and how it works
- Establish the measurement basis and units described above.
- Enter actualDailyTrainingLoad and run the tool.
- Read result.meanDailyLoad, result.populationDailyLoadSd, result.monotony, result.strain using the output meanings below.
- If input is rejected, correct the stated type, range, ordering or alignment issue and rerun; review successful results under the declared convention.
| Input field | Meaning | Value type | Requirement |
|---|---|---|---|
| actualDailyTrainingLoad | Daily training load, on the basis specified in the algorithm. | array of number | required; dense; align related rows as specified; further conditions in the algorithm |
Require at least two nonnegative daily loads and positive population standard deviation. Return mean, population SD, mean/SD monotony, and total load times monotony.
SD = √mean((load−mean)²); monotony = mean/SD; strain = Σload × monotony Apply the declared units, ordering and branch conditions.
| Output field | Meaning | Value type |
|---|---|---|
| result | Object containing the declared output fields. | object |
| result.meanDailyLoad | Arithmetic mean in the daily load unit. | number |
| result.populationDailyLoadSd | Population SD in the same load unit; division uses the full number of days. | number |
| result.monotony | Dimensionless mean/SD ratio. | number |
| result.strain | Total period load times monotony, in the declared load unit. | number |
{
"input": {
"actualDailyTrainingLoad": [
1,
2,
3
]
},
"output": {
"result": {
"meanDailyLoad": 2,
"populationDailyLoadSd": 0.816496580927726,
"monotony": 2.449489742783178,
"strain": 14.696938456699069
}
}
}Limitations and assumptions
The output applies the declared operation to the values you supply. Establish the measurement basis, units, coefficients and any caller-selected rules before interpreting it. The tool does not independently collect or verify observations or decide whether a model or reference applies.
Supply explicit required fields with the documented types and dense aligned arrays. Unknown fields, wrong types and nonfinite numbers are rejected. Branch-specific constraints are explained above. A successful false boolean, negative signed difference, empty slice or unresolved tie is distinct from an input error. Very large inputs or outputs may be rejected by shared resource limits.
Alternative or Complementary methods
For a related operation, use SWOLF Swim Efficiency Score. SWOLF combines one swim length's elapsed seconds and counted strokes into a session metric.
For a related operation, use Triathlon Brick Leg Pace Blend. A mixed-sport brick session may combine unequal leg distances and transition time.
References
Similar or alternative tools
- SWOLF Swim Efficiency Score
SWOLF combines one swim length's elapsed seconds and counted strokes into a session metric.
- Triathlon Brick Leg Pace Blend
A mixed-sport brick session may combine unequal leg distances and transition time.