Which FIT files should I include for calibration?

More files are not automatically better.

The best calibration dataset is the one that best represents how you move on the trips you want to plan.

Include files that are:

• representative of hiking or backpacking you actually do
• spread across meaningful terrain variation
• typical of your real pacing and effort
• complete enough that you would trust them as examples of your normal movement

Exclude files that are:

• from unrelated sports
• obviously corrupted or incomplete
• dominated by stop time or strange recording behavior
• extreme one-offs that do not represent how you travel most of the time

Decision rule

Ask:

If TRIPS learned from this activity, would it improve or weaken future backpacking plans?

If the answer is “weaken,” leave it out.

Start smaller if you are unsure

If you are torn between a smaller clean set and a larger messy set, start with the smaller clean set.

You can always expand later.

Why this matters

Calibration is about improving relevance, not maximizing file count.

A moderate representative dataset is better than a large mixed dataset.

If you want deeper guidance on different kinds of FIT collections, tradeoffs, and limits of various kinds of “cleanliness,” read Build a calibration workset.