It is influenced by extensive curve updates among other things, as well as by vo2max values, currently 4 different parameters influence this value, it does not have to be in 30 days.
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The heart rate is a bit more complicated as I canāt access the parameters I want from the heart rate curve, so I had to design it in another way, even so in most of the cases it is estimating well, when I manage to adjust that parameter in intervals as I have it in wko5 it will estimate much better, although there wonāt be big differences.
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+1 for the adaption to running, this would be an amazing training tool to add to the arsenal, thanks a lot! 
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Just an update on something I noticed today. My estimated power at VO2 Max plummeted by 44w today. Old estimate was pretty much on the money Iād say. New estimate is way too low. Just did 3*10 on Thursday at higher watts than my new PVO2max estimate
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If you donāt have good data over time on values associated with vo2max, the estimate falls off like any data modelling.
Just thought Iād let you know because you were looking for feedback. Itās not a metric I pay particular attention to. I know what wattage I can do my VO2 intervals at and what I canāt do them at.
As regards the data I haveā¦ I got a power meter 4 years ago and have all 4 years of data uploaded to intervals. I have 1500 hours of cycling data where a power meter was used. Iāve also been doing VO2 intervals since July so all that recent data is there. There is plenty good data there.
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I understand what you are saying, the problem with something that is based on modelling is that in this case it takes values from the last x days at certain points, it will take the mmps, as there are no maximum efforts the value goes down. As soon as I have time I have to make some modifications.
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Hi Just found this thread but when I tried to add one of the fields all I got was this.
Could someone let me know what Iām doing wrong please?
Hi David, I added the AeT and AeTHR fields and re-analysed the files like you described. Fields wouldnāt show any data. Couldnāt figure out what I was doing wrong. Finally decided to ātry turning it off and on againā by logging out and logging back in. Suddenly the computed data appeared. Using Safari.
Edit: now also added MSS field and re-analysed. Didnāt experience the same problem.
Hi,
Hereās my first observations:
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Overall AeT is where I expect it to be, but AeT HR (141bpm) is higher than expected. I usually estimate it to be at around 136bpm, although indeed sometimes it seems to be as high as 144bpm.
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My AeT HR is calculated to be 141bpm for the entire history of rides I have uploaded (little over a year, or 264 activities). This is surprising to me because I have noticed that on the short term my heart rate vs power is quite chaotic and fluctuates very much from day to day and week to week, depending on factors such as sleep and freshness.
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On May 1 I had a bump in both AeT and MSS. AeT went from 177 to 180 and MSS went from 201 to 210. Because I was curious what ride would trigger such a change I looked it up and I noticed this is one of the few rides my power data was missingā¦ Did it maybe use cached power data from previous ride?
To however fixed it. Thank you
MSS looks a bit like the Lactate Balance Point that Steve Neal uses/used.
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Thatās right, Iāve changed a few things but thatās what I was looking for.
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On Aug 24th my MSS was 193W and on Sep 7th 165Wā¦ I donāt think MSS can vary that much on a short period like that.
This depends on the power curve at a certain time if your modelled eftp goes down, the model understands that all values go down. I think you should understand a little bit how a model works.
Iām on holiday at the moment so Iāve just looked at a few activities and the numbers look spot on. The algorithm seems to have picked slight reductions in numbers since I eased off towards the end of August which is what I would have expected. Off to do Mont Ventoux this morning if itās not too windy. I wonder how long I can hold my predicted MSS power up the hill.
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Well, youāve asked for feedback and havenāt specified that was only for experts.
Still for me, a non specialist, it sounds not rightā¦
Regards
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Letās try keep the emotion out of the responses, please. Perhaps due to the different languages among us, English is not the first language for a number of users, and the translation might come across as being rude/abrupt/harsh, when it is actually helpful. I have to remind myself often that English is my first language and cannot assume someone else is too.
Back to the topic:
@Gato_Felix to help understand a model, it can only look at the data that is present in your (recent) history, and not at what you might be capable of. The power duration curve is a model taking each personās best efforts and āfitting itā to a model of similar types of profiles.
For me, I havenāt done a lot of short duration efforts, as itās late base. So my model will be skewed by this, and show different metrics compared to when Iām in season. Garmin also shows as āunproductiveā, because Iām lacking āanaerobic intensityā, which will start closer to the race season.
So as @Inigo_Tolosa has said, the data in his metrics can only give you values based on your data that feeds to the model. Itās not perfect, and never will be, but for many that fit the bell curve it will be.
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I have simply explained the reason for these values, if you want to understand it as an offence to you. All this is an estimation and it will have its errors, to understand those errors you have to know how a data model works, which is what I have told you.
Maybe the best thing to do is to remove those fields and we will avoid problems.
Update after todayās session, if itās any help.
My power at VO2 max rebounded today and is back up the 43w it had suddenly fallen a few days ago.
However my AeT fell 47w this evening from where is was on Sunday. AeTHR remains constant at 146bpm.
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