Base training / zone 2 datasets

In all seriousness:

Or, as someone else said, take an exercise physiology class, especially one focusing on clinical populations.

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With all due respect…

Would you say the same to Attia ?

I haven’t found a single paper with the parameters I want

  • sub lt1 training
  • multiple sessions a week
  • less than 10h total
  • before and after lactate curves.
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I would.

As for what you’re seeking, it might be out there, but again, most studies will have had participants training at a higher intensity, for fear of not causing any improvements.

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Exactly my point.

And sadly yourself and your peers are the closest to the truth. And if the data isn’t out there, how can you really know

Why can’t we have you and Attia or ISM debate ? I would pay good money for that.

Because people have measured other outcomes (mostly VO2max) as a function of training intensity, and we know that there is minimum required to elicit physiological improvements.

Why would I want to debate an influencer or a coach? Or are you somehow under the mistaken impression that they are the experts that they claim to be?

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There’s a non sequitur there in my (untrained) eyes.

True for vo2 max improvements but that doesn’t rule out lt1 increases? Aren’t you even remotely afraid there may be something there to z2, despite all the noise ?

In all seriousness are you better off answering individuals like us instead of taking your experience out there on the big stage ? Why let these influencers do damage, if they indeed are doing it ?

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Just train however you want then…

The All Roads Lead to Rome (or Tokyo) recently comes from Mike Joyner’s interview:

Norpoth who got the silver medal ran a very high volume of lower intensity.

So what is stopping you from polarized training - lot of easy and 1-2 sessions per week of VO2?

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my proxy for LT1 (never measured lactate) is EF (power/HR) on endurance rides. That has mostly scaled lockstep with FTP.

Even on “almost averaged 8 hours/week in 2022” best level of “volume” commitment, my ftp has scaled mostly with volume and not so much on intensity:

That dataset starts at age fifty two. 2014 and 2015 were spin classes, mostly on Stages SC3 bikes in the gym (they have power meters). Bought a road bike Dec 2015, better data starting 2016 onwards. Bought a power meter October 2016. I’ve got some “my proxy for LT1” data kicking around but its not lactate and like I said, it mostly parallels the rise and fall of my FTP.

Again not what you are asking for, its n=1, but you should be able to see my peak in high-intensity training was 2017 and estimated FTP of 275. Then I dropped volume and FTP dropped. Then I increased volume and did more “easy” rides, and sprinkled intensity throughout the year, and my FTP kept rising.

This year I hit some all-time power PRs:

the all-time power PRs are in purple. The green are within 5% of all-time power PRs. Nearly all my power PRs are from 2017, except for a few short durations from a little bridge sprint from December 2016.

YMMV. Don’t try this at home. It depends. You are the experiment.

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oh, and I forgot to mention that in late 2021 my RHR started dropping. Then my HRV started increasing. This year my RHR is down about 14bpm versus 2020 and earlier. HRV keeps rising, from well below normal in 2020 to slightly above normal. Was it cumulative endurance training taking a long-time to take effect? Or did my STRESSFUL job and high-intensity work conspire to keep me in a constant state of fight-or-flight? Or something else? I have absolutely no idea, all I can say is those metrics have improved substantially. And that everything is better by doing my endurance training by feel, with some bordering right around what I believe would be LT1 if I went into a lab. Regarding LT1, it is pancake flat here, I have zero distractions while riding rural roads, and I listen to my body and its pretty easy to detect the increase in breathing somewhere around 65-75% estimated ftp / 136-139bpm. I have intensity control and large portion of my rides often look like erg power, which means I play around with ‘letting the power come to me’ and slowly increasing power and feeling the impact on breathing and heart rate. Without looking at bike computer I can often tell you my HR within 1bpm. Heck I’ve done so many steady endurance rides I can usually tell you my TSS within 0.5.

FWIW.

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Just reporting back after a number of hours skimming the literature, some as far back as the 1970’s.

  • In cycling, moderately trained athletes reach their FATMAX around 64% of Vo2Max. You can probably use the Karvonnen formula to estimate that to heart rate.
  • There is absolutely something magical happening below that intensity, which is more or less Zone2. I’m not sure what to make of “you don’t need to train fatox to be good at fatox”, when clear studies have shown no improvements to fatox when during only SIT.
  • There are clear benefits to long-interval, high-volume (zone 3 in a 3-zone heart-rate system) vo2 max sessions. Probably this is why pros do polarized / pyramidal.
  • There is no evidence to support the benefit of mid-intensity exercise at the expense of low-intensity or high-intensity volume.
  • Gene expression changes when training ‘light’.
  • Sweet-spot / Threshold workouts do have some fat ox, and probably do have some effect on vo2 max. So for newbies, it really doesn’t matter how you train. Not sure how long improvements can be pushed by training lots of it long term though. What I know, is ‘z2’ low intensity + 1-2 sessions of vo2 max a week is more enjoyable that a shitload of middle-intensity day in and day out.

Some sources:

  • Optimizing Fat Oxidation Through Exercise and Diet by Juul Achten, PhD, and Asker E. Jeukendrup, PhD
  • The Effect of a 3-Month Low-Intensity Endurance Training Program on Fat Oxidation and Acetyl-CoA Carboxylase-2 Expression Patrick Schrauwen,1 Dorien P.C. van Aggel-Leijssen,1 Gabby Hul,1 Anton J.M. Wagenmakers,1 Hubert Vidal,2 Wim H.M. Saris,1 and Marleen A. van Baak

No I can’t get the data, but I was asking for data in case these researchers were kind enough ‘by default’, but it seems I’m naive with respect to this.

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Just as an aside, the most successful long distance tester I know trains pretty much exactly that way: lots of easy miles and one or 2 VO2 sessions per week.

Having said that, he’s been at it a very long time, and didn’t always train that way. Much as he now says ‘long intervals just burn you out’ there may be a possibility that he has inadvertently discovered he can maintain what he has through less onerous methods than he used to build it.

I don’t know, honestly.

I do know, though, that when the majority of successful practitioners of anything adopt broadly similar methods, there’s likely something to be gleaned from copying them, regardless of what the research says. Remember, there were many years where the science as it stood suggested bees should not be able to fly…

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Part of the issue with training is that the science is very sparse and what does exist is typically what would be considered low-quality by biomedical research standards.

Heck, our understanding of human physiology in general is already so poor (even for topics like cancer where billions of dollars are spent each year), that we still don’t understand why many basic things happen, and drugs we develop don’t work the way we think they should like >90% of the time. Let alone a more niche area like exercise physiology…

In medicine, this is dealt with at least partially by practitioners making decisions based on volume of quasi-empiric data that they personally witness (things they notice from treating their own patients). This low-quality empiric data is then shared amongst practitioners and forms its own quasi-scientific knowledge base - it’s one of the “pillars” of evidence-based medical practice. It’s a major reason why medical training is so long - you need to develop your own set of personal observations. Knowledge like prior probabilities of disease for a given symptom, the diagnostic accuracy of various pieces of information, etc. is all largely based off of this quasi-scientific knowledge base rather than proper scientific study (and would likely be impossible to formally study scientifically in a useful way for reasons which are outside the scope of this comment).

Medical practice is then shaped by weighing all of this data together in a Bayesian manner - scientific studies provide answers to relatively narrow questions. Clinical experience provides further real-world data. This is all thrown together in a pot and as long as you use the right ratios you get a reasonable tasting soup that’s probably nourishing and likely won’t kill you.

As a non-expert in this specific area, looking in, it looks the exact same to me. You have a very limited science base that can answer narrow questions. Then a wealth of low-quality but very broad observations from people like coaches and cyclists themselves.

To make the best training decisions you need to find the right ratio of how to weigh this all together to make a soup that tastes reasonable.

The lack of certainty about what the right ratios are then allows ample room for variations in practice and excessive argument.

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The most successful guy you know probably has the best endurance genetics of anyone you know.

I knew a former Olympian who got a top 10 in the Olympic road race. After his pro cycling career, he sat on his butt at a desk job and got fat. He didn’t ride or maintain fitness. Then after 10 years of doing that he decides to ride again and race masters. Within a few months of training, he was literally going off the front of strong master’s fields and lapping them. And this was still with an extra 20 pounds around the middle he needed to lose.

He didn’t have super secret training methods handed down to him by previous pro coaches. It was old school, ride a lot and race into shape.

To me it just shows that the superior genetics and VO2max to respond to training.

All roads lead to Rome - polarized high volume, pyramidal, whatever. Get your training load up however you like it and you’ll land where you were mostly destined to land.

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