Sure. But that requires a lot of futzing with the system. And how many outdoor rides fit into that kind of approach with TR?
Let’s take a very simple ride example. Say that I do a 4 hour ride with 3 hours of zone 2 and 1 hour of threshold/SS. This is the type of workout that a coach might recommend (Kolie has on his podcast) and JOIN gives.
Do I have to manually create/select two workouts, a 3 hour Z2 and a 1 hour SS? Which do I associate to the actual ride data? Then what do I do with the other workout, which will make my TSS artificially high? Or should I comb through all 4522 and growing workouts to find a close match?
What do I do if I’m racing every week? Good luck finding a decent match for that, even manually.
For many complex/variable outdoor rides, the best you can manually hack together is a set of workouts recreating a time in zone chart. But apparently PLs don’t work that way, TR must have some more complex logic looking at target vs achieved power, otherwise it wouldn’t be taking them more than two years to implement it.
And that’s where they went wrong IMO. However their way of assessing fitness through PL works, it should have been designed from the beginning with the right requirements, that being that it works fully on “unstructured” rides/workouts (i.e, TR had no data for what your power target was) just as well as it does on TR workouts. Then they wouldn’t have to manually finesse the PLs for each workout or take forever to make WLV2.
I think it was a mistake to try to assign separate scores for 7 zones. Fitness isn’t THAT fine grained. 4 or 5 would have worked better in my estimation. Endurance/Tempo, Threshold/SS, VO2Max, Anaerobic and Sprint. In the real world nobody is great at Endurance but not Tempo. Threshold overlaps Sweet Spot. Your fitness is a spectrum and there are no hard borders.
Given that this has taken so long, I’m hoping they did redo the whole PL algorithm, even for TR workouts. Otherwise they likely don’t have a robust solution that will be worth the wait.
Otherwise I think their competitors are going to start really eating their lunch by allowing people to ride outside as much as they want and actually interpreting that data well.