Your results
What do the confidence labels mean?
Every number shows how much to trust it, from Reliable to Good for trends to Rough. Estimate means a rougher method was used.
Motion sensors are good at some things and less good at others. So every finding carries a label that says how far you can trust it.
The labels
| Label | What it means | Example |
|---|---|---|
| Reliable | Measured with high agreement in studies. Trust the number. | Steps per minute |
| Good for trends | Close, but can be a few degrees or milliseconds off. Best for comparing your own runs. | Where your foot lands, knee bend, time on the ground |
| Rough | Only a rough guide. Use it for direction, not exact values. | Braking |
| Estimate | Worked out with a shortcut, for example from fewer pods. Counts half in the score. | Hip drop, heel lift from the shin pod only |
Next to the label you also see how many strides the number is based on.
What lowers confidence
Confidence starts at the level the method allows and drops when the data is weaker:
- you skipped the standing pose (angles are hidden),
- a pod lost data during a stride (signal quality),
- the pods' clocks didn't line up well,
- a pod sat at an unusual angle or slipped,
- the shin pod hit its maximum reading on hard landings.
How we use confidence
- Rough numbers never drive your focus. The app won't tell you to change something it can't measure well.
- The Running Form score gives less weight to lower-confidence findings.
- A finding with too little data says Needs more data instead of guessing.
How good are the numbers?
Step timing has been checked against force plates in a public lab dataset of about 9,400 strides. Angles have been tested on simulated runners but not yet against video or lab cameras with our own pods. We are running that check during the beta and will publish the results.
Updated 1 November 2026.
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ReadMyMove shows how you move. It does not assess injuries or health. If you have pain, see a health professional. If you're pain-free, there's no need to change something just because it differs from a typical range.