Used of Cho in post ride report

[Mika22]

Hi,

I noticed something on my Z1 recovery ride this morning (~32 min, 160 kcal total). The device reports 47 g of CHO used, which seems quite high for this intensity.

Physiologically, for a Z1 ride of this duration, I’d expect roughly 75–80% fat oxidation, so actual CHO usage should be closer to ~10 g.

I just wanted to check if this is a known behavior of the algorithm, or if there’s something I might be overlooking in the interpretation.

Thanks for your insight!

Best, Mika

[R2Tom]

Yeah unfortunally it takes variability and your estimated VO2max into account. I’ve run in this problem with EVERY commute. High VI calculates high carb utilisation. Even if I do only 40%FTP average, but maybe 50% of FTP as NP - because there are some hills around me… then it calculates 100g carbs within 15minutes commute or so.

I’ve raised this problem somewhere in this thread, but don’t know if the original data modeller / paper author is still reading it on the forum, so I doubt it ever get “fixed”:

Carb utilisation and ingestion on activities

Activities now show carbohydrate utilisation in grams and you can capture how much you ingested: [Screenshot 2024-11-04 at 08.39.11] Columns are available on the activity list view: [Screenshot 2024-11-04 at 08.44.04] Carbohydrate utilisation is calculated using the TSS model from this paper by Rothschild et al.: Notes: VO2 at VT2 is estimated from FTP Activities with a variability index (normalised power / average power) of less than 1.10 are considered “continuous” Prior day S-RPE i…

So I can’t use this metric if I still track my commutes …

[Mika22]

Dear Team,

As mentionned in my previous post I am concerned regarding the current carbohydrate utilisation model, particularly as it applies to short, low-intensity but slightly variable activities such as commutes or recovery rides.

From what I understand, carbohydrate utilisation is calculated using the TSS-based model derived from Rothschild et al., with VO₂ at VT2 estimated from FTP. While this framework is coherent for structured and sustained efforts, it appears to overestimate carbohydrate oxidation in short-duration activities that include minor variability (e.g., small hills or stop-and-go patterns).

In these cases, even when average intensity remains low (e.g., ~40% FTP), a modestly higher Normalized Power and Variability Index can substantially inflate estimated carbohydrate utilisation (sometimes to physiologically unlikely levels for 15–30 minutes of predominantly aerobic work).

Physiologically, short Z1–Z2 efforts with brief surges do not typically allow sufficient time for metabolic steady state to be reached, nor do they meaningfully impact muscle glycogen stores to the extent suggested by the current calculations. The model’s reliance on NP and VI may therefore overrepresent glycolytic contribution in such scenarios.

May I suggest considering one or more of the following adjustments:

• Introducing a minimum duration threshold for carbohydrate modelling (e.g., 30–40 minutes).
• Reducing the weighting of VI for activities with low overall intensity (low IF).
• Allowing exclusion of activities tagged as “commute” or “recovery” from carbohydrate utilisation calculations.
• Using average power instead of normalized power below a certain intensity threshold.

I believe refining this aspect would improve physiological accuracy and enhance the practical value of the metric for users who track recovery rides and daily commutes.

Thank you for your continued work on the platform.

Best regards,
Mika