I disagree. Skills and tactics held equal, FTP is a large determinant in performance across a wide variety of different disciplines (excluding short duration track riding). Within a category, yes, there is variation and outliers, but on average, a Cat 1 rider will have a higher w/kg FTP than a Cat 3 rider and I think it would be pretty easy to pick out who would win a variety of different events if we had absolute and relative FTP. Hell ,you could build an ELO simulator and train it on this data to prove or disprove this point
The Critical Power/W’ model predicts anaerobic work capacity and critical power, which is different than FTP and has no corresponding physiological breakpoint [critical power] when you measure it in a lab.
I’m not aware of a Critical Power model that predicts LT1, especially since W’ is anaerobic work capacity and LT1 is an aerobic marker. Xert predicts LTP which is your threshold after you’ve depleted W’, which is fundamentally different than LT1. If there is a study around LT1/VT1 and CP, please link it so I can read it
(pause)
Okay, with that out of the way, in order to get a useful Critical Power plot, you need to have a short (5-45 second), medium (90s - 5min), and long (technically 12min, but its now recommended to be 20-30min) maximal effort that are far enough apart to be maximal, but close enough together to be within a reasonable amount of time. Let’s say just say 2 weeks.
If you’ve never gone out and done a 3MMP and 12MMP, they are soul destroying. And you won’t get training zones out of it. You’ll get W’ and critical power, which is useful if you are a rider focused on the anaerobic side of the equation, but that is only one side.
Cycling is a predominantly aerobic sport (even with a 1MMP effort, you are still working aerobically); by and large the reason why training plans look similar is that below threshold, most people function pretty similarly. When you get to the pointy ends of the histogram, there are people who respond somewhat differently, but for the most part, people respond to sub-threshold work pretty similarly.
The difficulty with almost all of the performance modeling that exists is that its very difficult to pull out the subjective factors that exist before fitting it to what might or might not be sub maximal or maximal data points. WKO4 is the only exception here and actually does a pretty good job, even though it may be the least user friendly product ever built. WKO4/Coggan iLevels/Optimized gets the closest to having high fidelity zones than any other product, but we are talking about a pretty small difference comparatively. And you have to feed WKO4 really good data for it to get close. Which usually involved regular testing