Another variation on the ongoing questions of how to manage cases where power/FTP differences are not trivial…
Just got the Assioma DUO upgrade on sale - primary interest was to improve data precision for CdA field testing on my TT bike.
However, I was surprised to see a 54/46 offset very steady over my first ride with it yesterday. Was expecting more like 52/48 based on the one time I rode with a dual meter on a rental bike a couple years ago.
As a result, the target for threshold felt super easy and I ended up hitting way higher than normal reported power outputs. To complicate this further, my road bike for the foreseeable future will remain L-only, and I have years of good perfectly matched data between the road and TT bike using L-only, and a long history of training where I am very well in tune with my power data enough to know when someting is “off.” Previous testing I did showed the stages/assioma matched within 1W from endurance to sprints - my point is that this is not a case of “oh, nothing can be trusted to more than 5%”- that is a common online cop-out answer when following best practices with good modern power meters
So - assuming this offset persists, which I will need more riding to see, I can’t just dump all my TT bike data into the same database with an 8% difference when I’m riding both bikes regularly. A difference that large is not something you can just handwave away, but it seems like right now, that is the official solution from TR - “it’ll all just average out”- and basically every road bike workout is too hard, TT workout is too easy, AT will chase its tail based on my feedback and performance against these targets, and it’s completely unnecessary noise.
Other options I could see would be -
Use the Assioma app to scale my dual side power data down by 8% - bad for vanity, but good for data consistency
I’m not aware of a way to scale a Stages L-side meter up by 8% - but if there is, I’d consider that… this would at least let me not confound what feeds into AT going forward, and have data that is closer to an absolute correct value
Do math in my head so all my outdoor TT workouts aim for 8% over target - but once outdoor workouts are analyzed, that will skew things…
Are there any other 3rd party solutions out there that may conveniently allow some scaling offset to help manage this - esp. if can be done prior to Strava so that everything that syncs from there is then consistent?
Overall, I would be a lot happier if TR would take seriously the need to segregate and offset data sources / positions / indoor/outdoor even if we had to manually assign them into buckets once defined. Without this, for some of us, there will continue to be a lot of unnecessary noise injected into AT that is impossible to accurately compensate. In fact, this could be a very nice differentiating feature if TR was able to provide such organization for things like PRs, etc. I’m not aware of any app that does it today, and at the moment, I’m going to start generating a lot of BS PRs on my TT bike unless I artificially scale down the data.