Running with power (Stryd)

I have been using a Stryd running power meter for the last 6 weeks. It messes up my Xert stats so I have to flag every running activity. Are there any plans to introduce running with power into Xert?

P.S. The beta iOS app is great :slight_smile:

Hi Adrian, we recommend not syncing runs and rides to the same account, since the power duration curves are very different. Xert offers a deal for premium yearly subscribers of Xert to set up a second account just for running data. Contact for more information.

Thanks Scott

Hi Scott,
reviving this, since I’m going thru the same process, and had same question from clients that I’m trying to get on Xert.
Separate account for running does’t make a ton of sense to me: running and cycling workouts are marked clearly, wouldn’t it be easier to select which data is used to generate two separate signatures for the same user?

My concern is that while fitness signatures ARE different, being different disciplines, the impact on stress/strain/workload is not, since it’s one human being, not two.

I requested the separate account, but I’m very skeptical of this approach.

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I’m very new to all this, but it strikes me as suboptimal too. Sure, power profiles might be different (and indeed I don’t have a power Stryd), but the aerobic training impact surely crosses over disciplines.

Seems like ignoring runs will under-estimate physiological improvements and fatigue estimations. I guess this is one of the reasons TrainingPeaks was recommended to me and Xert was pitched as “if you only do cycling”.

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I’m sure this will be addressed at some point, but indeed TP seem to be still a better option for Tri athletes

Simply adding your training loads together is just as suboptimal. Ideally, there would be a way to properly account for the crossover effect (it’s not 1:1). Without this, you don’t have a true representation and will rely on some form of guesswork in the end or external methodology. We have some athletes that export their XSS (L,H,P) data and aggregate them across disciplines using their own methods via a spreadsheet.

Note that CTL/ATL are often described as being too blunt to be predictive so simply adding all sources together isn’t going to do much harm since you’re relying on guesswork / personal history to make sense of the values. With Xert, this changes since your LTL, HTL and PTL are predictive. You can’t / shouldn’t contaminate their data and they should attempt to accurately quantify the amount of training and improvement you have made.