Polarized Training Deep Dive and TrainerRoad’s Training Plans – Ask a Cycling Coach 299

I see what you are saying about hypothesis generation by gauging the contribution of a variable to model fit. I think it’s just really hard to tease out which variables matter more.

In stepwise regression variable selection, the order of entry of variables matters. If you call for forward or backward selection, the end model can differ. Imagine you added in HRV, then a variable which previously seemed insignificant becomes significant as if HRV was a negative confounder.

It’s better to have a priori hypotheses with a conceptual framework and then focus on one single variable of interest to put the hypothesis to the test.

To date, the form of big data hypothesis generation I’ve seen is something like screening drugs. You hit cell cultures, benign or malignant, with hundreds of different drugs to see if RNA expression changes in interesting ways. You might find something like a statin or an antihistamine affecting a expression of an oncogene (a gene that drives cancer), then you are left with wondering if that drug would really work to prevent or treat cancer. First of all, is that real or a chance finding. All tests have a rate of false positives. What dose matters? Over what time frame? When? There are big biomarker studies where you take blood or tissue from patients with X disease but at the end of the day you scratch your head if your findings are meaningful. In imaging, there are worries that AI overdiagnoses cancers.

AI, ML, big data - this type of stuff seems more helpful when the platform can create data rather than just look back on existing data. There’s a fascinating documentary on how the AlphaGo creators built an AI to play Starcraft 2. The computer plays so many games that it spends virtual time far greater than the total time of human existence. It then does some crazy things while pummeling professional players, like use an excessive number of mining probes that humans would think inefficient.

AI/ML is a very hot topic, but I’m waiting for concrete examples of it doing something to advance medicine before getting excited about it.

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Ah, I see. I didn’t realise you were using two decimal places in the percentage; hence the number of variations you get for each PI value.

BTW, if zone 3 > zone 1 then PI is not valid based on info here:

The innateness of this thread has made me realise I like to simply go ride my bike sometimes(!) :smiley:

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Yeah, that would make it HIIT, or whatever you want to call it.

Considering this is based on time in zone, its only a handful of ratios on the left hand side that are truelly polarized.

I’ll take that as a compliment. Around these parts calling someone a spanner is less than complimentary. Perhaps I should reconsider my handle…

Mike

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@ambermalika Nate’s menstrual cycles at sea level and at elevation had me on the floor! You’re absolute right!!

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Thank you @ambermalika and @Nate_Pearson. I have learnt more in the first 35 mins of this podcast than I have in the last 3 years of cycling combined. That was amazing!

I wish I had Amber as a teacher/lecturer at university when I was younger. I would of understood a whole lot more!

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Isn’t one of TrainerRoad’s basic training goals to train ALL the energy systems? I’ve always understood this to mean that some workouts will focus on your aerobic endurance and some will focus on your ability to achieve and repeat VO2 Max and higher intensities. Sweet Spot trains both your aerobic and anaerobic capacity. I’ve always thought I need to do at last one or two intervals workouts/week above my FTP. If I try to do more than two HIITs per week I run the risk of overreaching and eventually overtraining. Only two of the five TIDs Amber identified include Zone 3, over FTP intervals.

@_Matthew

Agreed.

I also have to confess to being bemused by the big data hype: it seems to go against everything I was trained in – you have to have a good idea before you go looking for / at data. But then, that was more than half a century ago.

But I do like the idea of adaptive training, which seems to offer the prospects of setting more personalised progressions than are possible in generic training plans. That is: “here is a rate of progress that it seems you can handle and when you get to this performance level, it will be time to move on to the next phase” rather than “do this for 6 weeks”.

Nice talking to you!

Thanks TR for coming up with reply to the whole Pol discussion. I am a big fan of TR and have been using it for the past 2 years and love the podcast to bits.

I love that TR is taking the necessary/proactive steps in advancing cycle training with Adaptive Training and now a Polarized plan.

BUT, as a former academia, and the small dabble i had in research, i was expecting a different approach from TR about this matter. Starting the podcast by dissecting the very few decent research on this matter wasnt one of it. What about all the studies that have been quoted in the podcasts in the past? Are we going to dissect each and every one of them back and re-look at recommendations made in the past podcasts?

A simple, TR plans are NOT threshold because of etc etc. would have been sufficient.

I respect TR more now because they are brave enough to venture into research of the matter. Looking forward see what the results of the huge randomised control trials on this matter shows.

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All of TR’s other plans have been developed and tweaked over the years, and have been proven to yield improvements.

A polarized training plan, which is structured, initially would be aimed at presumably would only target one type of event/riding style. So I reckon TR won’t release e. g. a polarized crit plan alongside a polarized rolling road race plan and a polarized century plan. That means it makes a lot of sense to initially funnel only people to it who know what polarized is and want to try it.

I am not sure whether there exist long-term studies that for polarized that are not observational. With this I mean not studies across one or a few training blocks, but studies that investigate the efficacy of polarized structured training plans. I think the studies on the tri plans lasted 13 weeks if memory serves, so that’s about half a block and for a very specific application where in competition you spend most of the time at 70-85 % of FTP.

I think choosing a plan with too high a volume, lack of prep, sleep and inadequate nutrition are likely quite high on the list. That’s quite independent of training methodology. At equal time a polarized plan would be easier, because it packs less TSS.

I love that you live extreme ownership, @Nate_Pearson. Thank you for this.

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Does this help?

I think it is better to think in terms of 80:20 (low stress: high stress session ratio) than polarized. but that term lives its own life now out in the digital landscape. I will continue to talk about this and acknowledge that “pyramidal versus polarized” often comes down to race duration that the athlete is preparing for and other details".
Dr Stephen Seiler - March 15th 2021

It’s SESSIONS not TIZ.

So if it’s not sessions, I could do all my V02 Max training in a single mega workout once a year. Then ignore it every other day. (I’d also be dead, from 50hrs of continuous V02 Max work). That would be okay because my yearly TIZ would be perfect. My big P little p would be on point?

Of course not. Because it’s SESSIONS. The whole point of polarized training as it’s being used by actual coaches in the real world, is to better manage fatigue in athletes. A majority of easy sessions with a small amount of focused hard sessions.

This is what Dylan was harping on about, this is what many of the forum discusions were about. Breaking down a study, then showing the TIZ of a bunch of training programs does not address the FUNDAMENTAL issue.

Fatigue management of athletes on training programs. Essentially, how many hard sessions vs easy sessions.

Now, somebody with the required ability could easily breakdown the TR training programs into hard vs easy. I’m willing to bet that few, if any, are polarized by session.

Particularly, if you include sweetspot in the hard bucket, which I personally absolutely include that way. How many plans have more than two days of intensity? How many have more than three?

This I believe is the relevant question.

Go ahead, break down the TR plans into sessions

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I don’t think I have a dog in this fight (well - based on my flip - flopping between pyramidal and polarized over the years maybe I have both dogs in the fight…) but I think by defining the metric this way, you’re already declaring the outcome. If it’s just a binary “hard vs easy” then yeah, TR’s ratio of hard is too high. But that’s just a function of how you decide to measure. Another way is to draw the line at FTP (as opposed to under sweet spot as you did ) then the infamous Sweet Spot Base High Volume is now too easy - as it has zero hard days.

I do think it’s important to view the human body / training interaction as a gradient - the binary hard / easy is just too simplistic in my view for such a complex process. That’s one reason I’m really excited about the TR “levels” for the workouts as it will add more granularity to the broad buckets - not less. For many people maybe they can do 5 days in a row of “4.0 level” sweet spot, but that same schedule of 6.0s will break them? Or a single 9.0 puts them on the couch for a week?

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First: Yes to all what you said.
Second: However if you look at the potential available time at 7 days, the equation is different.

Example:
You could ride 5 days easy (but for 2-4h each ride), 1 day hard (1-1,5h), 1 day off. Let’ assume this would be OK with your fatigue levels (5 2-4h days are no joke)

You could also do 2 hard days (1h each), 2 Tempo/SS days (but just 1,5h each), 3 off days. The overall stress should be about the same. Also taking into account that SS creates way more fatigue then LIT.

Sidenote: I personally would do the long rides for best aerobic adaptations, but this is not a question of what works better, but a question of induced fatigue.

And this is the problem which Nate is trying to explain: MidVolume plans are no joke. You might have the time to follow a MidVolume plan, but maybe not the fitness and would be better off with a LV plan. This was 100% the case with me when I first started.

And here is the point that TR plans are lacking for me:
I have the time for a mid volume plan, but want more low intensity and less overall stress. → Btw: LV + adding LIT sessions doesn’t work quite well, as I find the sessions in the LowVolume plans BRUTAL.

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I don’t know if we should argue if long-ish jobbers at 90% FTP are hard.

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I’m not saying they aren’t hard - but that its unnecessarily simplistic to just call them hard or easy. They are “differently hard” then a Vo2 or Seiler 4x8 session (at least for me) and I think that granularity is constructive.

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I love how engaged the TR team are and it is this that sets it apart from other training platforms. Half way through this pod. Its great listening. Thank you all.

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I think the “hard” or “easy” characterisation should be more related to the impact the session has on the endocrine system. I need to document myself, and here I am basing the next hypothesis on my feelings,so I might be completely wrong: but the SS sessions, although feeling much easier than a 4x8mn by Seiler, might have some similar impact on the endocrine system. I feel that the cumulative 1 hour SS workouts 3x a week before the real “difficult WO” are having a real toll and when I come to the real challenging workout (threshold; OU; VO2max), I am mentally drained and bail out quickly in the 3rd or 4th week of the plan in those WO. Maybe swapping one or 2 SS WO by z2 rides would help to recover better, at least mentally, before tackling the breakthrough WO

A bit OT: I also wanted to thank the TR team to let everybody discuss the topic openly. I am following the different threads, without participating because things are sometimes hot enough. Also, being opened to implement the polarized plans even if the team believes their approach is better is something everybody should applause. So thank you.

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I was struck by the small sample size of most of these studies, n<20 in most cases. Not sure any of them have p<.05 statistical significance.

And then thinking about the mountain of real world data TrainerRoad is sitting on and the studies that could be generated from that…it would amazing to see a collaboration between TR and academic exercise physiologists/data scientists.

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