No built in ability to send to erg mode, but they do have an option to sync to training peaks which you can send anywhere and use erg if that’s what you’re wanting. Frank is pretty big on being able to “freestyle” workouts, so while it may say 4x10 sweet spot, he encourages using judgement/terrain/etc. to work with that 4x10.
When I want to go brain dead and do an erg workout I just create a quick one in 20 seconds and do it.
Edit: yes, a training plan is laid out within the app.
I’d follow his page if you’re actually considering pulling the trigger. It’s worth full price, but he does have random discounts (I think I got 40% off just by luck of seeing it) so waiting if you can would be advisable.
Marketing or not, Frank seems to know that using the same name for a different metric was less than ideal (about 11:45 in the cast):
… so that’s how we derived, uh… the proprietary algorithm of xPower. It’s not Dr. Phil’s… uh… xPower, it’s, it’s our very, very own. Same name. Sorry for the miscommunication.
I think it’s great to have whatever they are doing in the space and I’m keen to learn more about it all. But this seems like a clear mistake and one Frank recognizes. Just odd to me.
yes, he apologized for the miscommunication, and I posted a shorter version of that above.
The longer version starts at 10:40 and is more interesting, I’m too busy to transcribe but the 3 minute discussion comes down to these key points:
Frank’s experience over 15 years is that normalized power can over-estimate steady state threshold power due to short punchy efforts
FasCat xPower corrects this issue with normalized power
tested out on 6 athletes, over 100 power files
FasCat xPower correlated very closely with those 6 athlete’s steady state threshold power
not Dr Phil’s xPower, same name, sorry for the miscommunication
really excited to build on xPower
can minimize some testing and give better FTP estimates than normalized of Skiba xPower
test twice, at beginning of off-season, then towards the end (when switching from base to race), and then FasCat xPower from hard group rides and race data. But if you do 20-minute time trial, or 30-min or 40-60-min, then use that
I’m not using the app, or Skiba’s xPower (I’ve modified Golden Cheetah charts to show normalized power). I’ve definitely seen normalized power from hard group rides over-estimating my FTP. So I liked what I heard on the podcast.
Is that correct? In the past, you had to have them send the plan to TrainingPeaks in order to see it. Have they updated it to where you can look at all the plans inside Optimize? That would be a nice improvement.
The value you calculate for CP depends upon the duration of the tests used to define it. It can therefore be greater than, equal to, or even less than FTP.
If you use the durations recommended by the person who came with CP (i.e., Monod), though, it is the same as FTP (on average).
FWIW doing a handful or two of spot checks, the “Extended CP” model in GoldenCheetah provides me with essentially the same estimates as WKO5’s FTP. Switching to the CP model in GoldenCheetah, will, as you say give me higher, lower, or the same as FTP in WKO5.
Again just a handful or two of spot checks, from times over 7 years when I had a well fed model.
It will be interesting to see if this receives the same blowback as Training Peaks’ attempts to protect the ideas I licensed to them. (I predict that it won’t.)
Interesting, you’re the first I seen to make that point and suggest FTP=CP is not reserved for the upper echelon. Granted I haven’t very dig deep into this and only follow wattage and cycling physiology on Google groups besides here. You got any source on it?
That CP is dependent upon the durations used to define it is a well-established fact in the scientific literature. Here is the classic reference (note the last author):
The dependency of CP on the test durations used to calculate it is the result of the fact that it is an imperfect model of reality. In particular, the relationship between work performed (distance covered) and duration isn’t truly linear. (Correspondingly, the relationship between intensity and duration isn’t exactly a right rectangular hyperbola.) Of course, proponents of the CP concept like to ignore this “dirty little secret”, because it undermines their narrative that CP is the “holy grail”, which makes them the keepers of the keys to truth.
ETA: I am not the only one who has realized that the emperor has no clothes.
Unfortunately, at the end of the day science is a human endeavor, with those wielding more political power - e.g., by serving as journal editors - having an undue influence on what people believe. Thus, as I constantly harp on my graduate students: learn to think for yourself.)
Gotcha. Yes, I always found the definition puzzling as it’s supposed to be the power you can sustained indefinitely but relies on the slope derived from very short MMP. And, I did read the second study on Google Groups but totally forgot about it. Testing-wise I seem to remember 20 minutes as the recommended upper bound and if you select the short duration as 5 minutes, that’s basically doing the Hunter Allen’s FTP test. Assuming one matches the 95%, that’s the 5%. I believe Hunter’s dataset has a plus minus of 2-3% which make it equal to FTP at the upper end.
That said, the CP that’s used when discrediting FTP is the slope derived from the short end of PDC and also the general usage (which I’m referring to).
Frank’s coaching company is a business, and it can be a problem if you can’t attract and keep enough to fund your new endeavors. Especially if these new features require data from a large number of customers. I’m saying this as someone who wants FasCat Coaching to succeed.
When I heard him say that on the podcast I immediately thought this is a red flag. I don’t think these numbers are sufficient to validate xPower as a concept.
… which, notably, is shorter than what Monod himself recommends.
More importantly, the use of such shorter tests to calculate CP is inconsistent with the proponents’ own position as to what it is supposed to represent. Specifically, in claiming it should be the new “gold standard”, Jones et al. have defined CP as the highest intensity at which all ATP is produced via oxidative phosphorylation. CP as calculated using shorter tests is claimed to fulfill this criteria because it results in a delayed steady state VO2 in many, but not all, individuals while cycling. However, this ignores the fact that at such an intensity lactate concentration increases progressively, meaning that there is ongoing non-aerobic ATP production, i.e., the intensity is greater than the definition that Jones et al. have embraced.
TL, DR: Conceptually, CP = MLSS and therefore = FTP. Operationally, this requires use of longer tests to calculate CP (as Monod himself recognized decades ago).
Little bit of a tangent here, and I’m very much not a scientist let alone a mathematician, but how reliable would you consider something like intervals.icu (or Xert, but I’m guessing this opens a different can of worms) where it grabs max efforts out of rides and uses that to calculate an estimated FTP?
This would be something like “From 14 minutes at X power, your estimated FTP is Y,” where the algorithm caught a 14 minute max effort out of a 4+ hour ride. I’m a little curious about the accuracy of something like this vs. more formal testing.
I would also say that developing and especially properly validating a mathematical model of the power-duration relationship just to estimate FTP isn’t worth the effort required, as there are numerous other ways to obtain an equally (im)precise estimate that are easier. That’s why I didn’t bother pursuing such an endeavor until I needed such a model to do other things (e.g., objective auto-phenotyping using discriminant function analysis).