Training Plans

When I run to pace, my heart rate is outside the range specified by TrainAsONE. What should I do?

By Dr. Sean Radford • 21st February 2022 (Updated 22nd January 2026)

It is very common for pace and heart rate to diverge, with many runners noticing an actual heart rate that is higher or lower than the range specified. If you feel normal and aren't experiencing unusual fatigue, there is generally no cause for concern.

1. Prioritise the "Intent" of the Workout

The relationship between pace and heart rate isn’t a fixed line; it is a moving target influenced by sleep, stress, temperature, and terrain.

For Easy/Recovery Runs: If staying within the specified heart rate range means running slower than the target pace, stay in the HR range. By doing so, you are following the true "intent" of the workout—ensuring a genuine aerobic effort and proper recovery.
For Fast/Interval Runs: Prioritize the Pace. Heart rate is a "lagging" indicator; during short, intense bursts, your interval might be finished before your heart has had time to rise into the specified range.

2. How Artemis 2 Handles Discrepancies

Our next-generation AI engine, Artemis 2, is designed to be "sensor-agnostic." Whether you choose to follow the pace target or the heart rate target, the AI performs a second-by-second analysis of all your data. It recognises when you’ve adjusted your pace to manage your effort and uses that information to refine your "physiological fingerprint."

Note: TrainAsONE's Artemis v2 algorithm is now in **[Open Beta](https://trainasone.com/training/forget-generic-heart-rate-zones-the-artemis-2-beta-results/)**. It removes generic, age-based formulas in favor of machine learning based on your actual data. You can enable it in your **Training Settings** under the **Training Algorithm** field.

3. Why is there a mismatch?

Physiological Modeling: In the Artemis 2 model, the heart rate ranges you see are a consequence of the AI’s understanding of your unique physiology. If they don't match your pace yet, the model is likely still refining its map of your cardiovascular response.
Narrow Heart Rate Ranges: Some individuals naturally have a very small heart rate "window" even across a wide range of paces. This makes specification extremely difficult for models. Artemis 2 is designed to learn such narrow physiological profiles, but it requires consistent data to pinpoint exactly where thresholds lie.
The "Noise" Factor: Recording devices are not perfect. Factors like "cadence lock" or poor sensor contact can create "noise." If your heart rate range is naturally narrow, even a small amount of data noise can make the specified target feel "off."
Natural Variability: On some days, your body simply has to work harder (due to heat, caffeine, or lack of sleep). This doesn't mean the system is "off"; it is reflecting your real-time state.

4. The Choice is Yours: Use the Metric You Prefer

Ultimately, TrainAsONE is designed to support your training preference. All said and done, you should use the metric — be it pace, heart rate, or simply perceived effort — that you feel most comfortable with and that works best for your running environment.

Whether you are a data-driven runner who loves following a specific HR zone or someone who prefers the consistency of a target pace, the system will adapt. Many successful users find a "hybrid" approach works best:

Set Fast/Interval runs to guide by Pace (to ensure the correct intensity).

Set Slow/Easy runs to guide by Heart Rate (to ensure true recovery).

5. Accelerating the Learning Process

You can help the AI align these metrics faster by using the Run Confirmation widget. If you ran to pace and felt great, but your HR was outside the predicted range, confirming the run effort as "Easy" or "Normal" provides the high-quality feedback the AI needs to tune its physiological model to your reality.

References and Further Reading

Artemis 2.
Cooper, C.B. and Storer, T (2001) Exercise Testing and Interpretation, A Practical Approach. Cambridge: Cambridge University Press.
Bouchard, C. (1982). Exercise and Sport Science Review. New York: Franklin Institute Press. p. 49-83.
Atwal S, Porter J, MacDonald P. Cardiovascular effects of strenuous exercise in adult recreational hockey: the Hockey Heart Study. CMAJ. 2002 Feb 5;166(3):303-7.