Thanks for this link, @bbarrera.
For anyone who is interested, I extracted the rough power as % of FTP values from Figure 2 with different software that estimate numerical values in image-based charts.
Interestingly, power as % of FTP at LT ranged from ~70% to ~100% at 60 minutes and ~115% to ~180% at 3 minutes. The shortest duration at 100% of FTP appears near the 20 minute mark and the longest at the 80 minute mark.
It’s impossible to say what the range of FTP to MAP is in this data set since you can’t tease out the individual curves, but it is probably much wider than the often cited 0.72-0.77.
I’m a big fan of progression levels in TR, but am struggling to understand the focus on AI FTP detection (which is really just AI Ramp Test result prediction) given the limited utility of FTP in the first place.
Aren’t progression levels and adaptive training better-served with zone- or system-specific power targets?
As an “over-tester” with a stronger top end than endurance base, I have to reduce my AI-suggested FTP from 325 to 280-285 so that my HR and RPE are appropriate for sweet spot and threshold sessions. I could easily complete VO2 and anaerobic sessions at an FTP of 340-360.
There’s an opportunity to put these “your FTP is set too high/too low” discussions to bed.
Progression levels are terrific, but it seems like we really need zone- or system-specific power targets like iLevels to maximize their potential impact.
I would be happy to occasionally calibrate with something like the H.A. & A.C. Power Profile Test if it means getting better data to train with. I suspect many others would too.
Jonathan commented on a recent podcast that he was surprised by how many people don’t test and manually adjust their FTPs. For some of us, faith in and utility of the end result is a big reason why.