02/02/2026
WHAT A YEAR OF WEARABLE DATA TAUGHT ME - AND WHY INTERPRETATION MATTERS MORE THAN COLLECTION
January is as good a time as any to “audit” all aspects of our lives so I took some time to review data from my wearable. Here’s what I learned.
Wearables generate an enormous amount of physiological data. Beyond simple metrics like step count, making sense of it isn’t always straightforward.
Over the past year, my device tracked various metrics. Looked at in isolation, these numbers can be confusing — and sometimes misleading.
What changed things for me was using an AI-based analysis tool as a structured way to review patterns over time, rather than reacting to individual values.
By looking at multiple metrics together — and placing them in the context of age, training load, and recovery — the trends became clearer:
⬆️ rising heart rate
⬇️ falling HRV
⬆️ breathing rate
⬆️ temperature
↘️ sleep
Interpreted properly, this reflected accumulated training stress and recovery demand, not declining fitness or illness — particularly in the setting of HYROX training in my 50s.
The key lesson?
Wearables don’t provide diagnoses, and AI doesn’t replace clinical judgment.
But used thoughtfully, they can help organise complex data, highlight patterns, and support better decisions around training and recovery.
The value wasn’t in the technology itself — it was in understanding what the data was actually telling me.
Good data still needs good interpretation.
And for me, the key takeaway (which is surprisingly useful to help focus my training goals for this year) is to focus on recovery (especially sleep) as much as training.
Have you looked at your wearable data and if so what did it show you? Please share below 👇