KoopCast
Coach Jason Koop covers training, nutrition and recent happenings in the ultramarathon world.
KoopCast
Polarized or Pyramidal Training for Ultrarunning with Michael Rosenblat, PhD #238
Michael Rosenblat comes back on the podcast to discuss his new paper exploring what types of interval workouts are most effective for Ultrarunners.
Which Training Intensity Distribution Intervention will Produce the Greatest Improvements in Maximal Oxygen Update and Time-Trial Performance in Endurance Athletes? A Systematic Review and Network Meta-analysis of Individual Participant Data.
Michael’s website-https://www.evidencebasedcoaching.ca/
Koop’s article on interval training-https://trainright.com/decoding-ultramarathon-interval-workouts/
Sign up for CTS Coaching-https://trainright.com/coaching/ultrarunning/
Subscribe to Research Essentials for Ultrarunning-https://www.jasonkoop.com/research-essentials-for-ultrarunning
Information on coaching-
https://www.trainright.com
Koop’s Social Media
Twitter/Instagram- @jasonkoop
Buy Training Essentials for Ultrarunning:
Amazon-https://www.amazon.com/dp/B09MYVR8P6
Audible-https://www.amazon.com/dp/B09MYVR8P6
#ultrarunning #trailrunning #running #sports #sportsperformance
Trail and ultra runners. What is going on? Welcome to finally. Welcome to another episode of the coop cast. As always, I am your host, coach jason coop, and it has been a while for new episodes of this podcast, but we are back in action and I am happy to announce in a slightly new format More on that later, because today's guest is making his second appearance on the podcast.
Speaker 1:Welcome back, michael Rosenblatt, who recently was the lead author on a new paper on training intensity distribution, which gets to the age old question of what types of interval workouts over long periods of time are the most effective. Michael comes back on the podcast to discuss his work, some of the painstaking steps he had to take to collect the data, as well as what all this means for the upcoming workouts that you have in your calendars over the course of the next weeks or months. And finally, as a new wrinkle in this podcast, we'll be hearing from our CTS coaches at various points during the discussion to bring a practical element to the research and how we use it with our athletes. So today on the podcast, you will also be hearing takes from CTS coaches Ryan Anderson and Adam Ferdinandson as we discuss how we use these findings in practice with our real athletes. All right, we're back in the saddle and, as always, I'm going to get right out of the way.
Speaker 1:Here is my second conversation with Michael Rosenblatt, all about intensity distribution and program design. Hey, how you doing? You're doing pretty well.
Speaker 2:I'm glad we could finally get this going yeah, there's a few little hiccups along the way I can see like I'm just in a random airbnb now.
Speaker 1:So anyway, what was me anyway? Thanks for putting up on my schedule.
Speaker 2:Yeah, no, it's great that we're able to to meet up and discuss the new research. It's kind of exciting stuff.
Speaker 1:So yeah, yeah, I'm stoked about it too, anytime we can talk about training, intensity distribution and things that coaches will actually take away and apply right, because that's fundamentally what we do is prescribed training, those.
Speaker 2:That's usually the research that we're kind of the most keenly interested in yeah, and I don't remember if I actually explained that to you last time that we spoke, but that was actually why I got into research, because I was originally a coach, yeah, right, so I coached triathlon and so it was to find better ways to tell my athletes and I felt this was the best way to go. So, yeah, that was really to find, you know, do good work and more applied work. So there's a lot of theoretical exercise science stuff out there, but it's good to be able to or hopefully it's good to be able to find some good work and create some new knowledge that'll be directly applied to the field.
Speaker 1:Yeah, that's good. I mean, we might as well get into it, we don't? We can skip, skip right to it. Well, welcome back to the podcast. First off, I had to go and look back.
Speaker 1:The last time you were on the podcast I released that episode and let's see, when was this? I believe it was December of 2013. So a little over a year ago, or sorry, 2023. I'm even going back even further than that, Number 198.
Speaker 1:So it was a while ago, and how time flies and I'll leave a link in the show notes to that particular podcast, but it is actually a pretty decent primer for this one, because we're talking about some of the practical elements that we're going to get into here, which is just how should we design intervals right, like, from a fundamental standpoint.
Speaker 1:You want to do something with an athlete, you want to improve their VO2 max or improve their 40K time trial or whatever it is? How do you design the individual training sessions to accentuate either a particular part of their performance or a particular part of their physiology, or some Venn diagram overlap between those two? As we were just discussing, those types of conversations end up being some of my favorite and also some of the listeners' favorites as well, because they end up going and doing the things that they just heard about sometimes the same day, sometimes the next day, sometimes the next week, and so I'm always really, really thankful of that. So you kind of already gave a little bit of a background on like how you started to answer these questions, but if you want to elaborate on that a little bit more, just in terms of like who you are, your coaching and your research and things like that, go ahead and take the floor for a little bit so the listeners can get to know you a little bit better again.
Speaker 2:Sure. So originally I was actually a triathlon coach. I think I started coaching in my early 20s and I'm from Toronto, ontario, in Canada, and I think there's maybe four or five other provincial coaches around and I started working with them and learning along the way, and I was asking a lot of questions about you know best ways to program exercise, be it interval training or even going up to the full program and I feel the answers I used to get was well, this is what's been done in the past and so this is why we do it this way, or this is what someone else has showed me, which I mean. Of course, clinical or practical experience is certainly valuable, but I kind of needed something a little bit deeper than that, and so that's why I continued my education, and even actually before I continued my education, I started reading the literature. When I say continued my education, I mean formally, but I'm actually a physiotherapist by trade.
Speaker 2:So after coaching triathlon, I got into physiotherapy and after practicing for a little while, I decided to go back to do a PhD in exercise science at the University of Toronto, and my research was primarily in programming interval training. And, of course, covid happened, and that shifted my research focus from laboratory work to more knowledge, evidence synthesis and knowledge translation. So I got to start synthesizing the evidence and I think I became somewhat of a methodologist and biostatistic along the way, and that's kind of what the majority of my work has been, or the area of my work has been. I'm currently practicing full-time as a physiotherapist, but I'm also a research affiliate at the Sylvan Adams Sport Institute and kind of guiding, hoping to help further their research program as well, and yeah, and so that's kind of where we are today and just to have this new research that's coming out. It's quite an interesting project because of the collaborative nature of the work. Yeah.
Speaker 1:So that's what we're going to talk about today. It's a synthesis of the information, as you put it. I like that terminology and you're absolutely right. It is a kind of a hit list of who's who in physiology. A lot of these people have been on this podcast, including yourself. I've got to get Jim Arnold on because I just really respect his content that he puts out in the space, but I think five of the authors in this list have been on this podcast either one or multiple times, and what I'm going to do in the show notes, since a lot of these themes are redundant, is link up those podcasts as well.
Speaker 1:So if somebody wants to do a really deep dive into all this stuff, which has a lot of overlapping topics with them, I would encourage you guys to just list in sequence but the specific piece of research that we're going to talk about now, the title of which is and if you have changed the title since the manuscript that you sent over to me, please correct me, but it's a mouthful the link will be in the show notes. But the title is which training intensity, distribution, intervention will produce the greatest improvements in maximal oxygen uptake and time trial performance and endurance athletes? And to say it's a synthesis of the information I think kind of like under undersells the effort that you and your colleagues undertook and we're going to kind of get into that effort just to paint the picture. The title kind of says it all but a little bit. Elaborate a little bit on like the questions that you're specifically trying to answer here.
Speaker 2:Yeah. So it's actually funny because, even just to discuss the title, that was certainly a discussion amongst my colleagues, especially because it's quite a long title and we tend not to like to have those types of titles but, based on the type of work it is, there's certain criteria that we need to follow in the title. So it's kind of as much as it's long, it's also somewhat necessary, unfortunately. But yeah, in terms of the question that we wanted to address was looking out, you know, I'd say well, which training intensity distribution would be the best for an athlete to use to maximize their performance. And interestingly, you know, we added the term intervention after the training intensity distribution, because when you really think about research and sports science, we're really just looking at an intervention in a set given amount of time, whereas in the real world we're really looking at not just, you know, a single session or a week, or we're looking at a full program to find a way to get some an athlete to peak or to be able to peak multiple times throughout a season. And so, yeah, and so I thought we kind of realized it was probably the best way to describe what the work is that we're doing. It's really just looking at an intervention period and the questions that we wanted to look at. You know we use those two variables or outcomes maximal oxygen consumption and time trial.
Speaker 2:Maximal oxygen consumption is certainly probably the most common physiological variable or internal measure that we use to measure performance, and then time trial, I'd argue, might be the best. It's hard to say, I mean I might say it's the best measurement of performance in terms of specificity. It's as close as we can get to what an athlete might actually be doing. But of course both have their strengths and both have their limitations, and there's so much to this that we're trying to address. But I think there's a few really unique things about that, and one, unlike previous literature that's been done, including my own work and I think it was some of the foundation of what we were discussing in our first time in our first podcast was it wasn't just a pairwise analysis, meaning it wasn't just comparing one intervention to another, it's a network meta-analysis. So we were able to compare all the different types of training intensity distributions to each other, and so that's something that's unique about the work that we were doing no-transcript.
Speaker 1:a coach, I mean and you know, you know this from your own coaching practice one of the things that is the biggest time cost when you're working with any athlete, and in particular any new athlete, is digesting their previous training, because it's everywhere it's in Strava and in training peaks and on the back of napkins and in three ring binders and you know old Excel sheets, and sometimes all of the above with just one athlete and being able to come through that for any significant period of time is always a pretty it's always a pretty big time cost. So when you and I were offline kind of discussing how we're going to crack this conversation, it kind of like to for you to peel the curtain back a little bit because I think it just it's kind of speaks to the efforts you have to go to to like figure this stuff out.
Speaker 2:Yeah, and not only that, but to find a consistent variable in terms of their training data that goes across all of the studies. Of course you can use different variables and try to mesh that all together, but you'd want to find something that's a similar measurement, to be able to accurately and I guess I can say reliably combine the data.
Speaker 1:So you're looking at all these different studies, right? Can you kind of give a little bit of the range of the studies that you were looking at in terms of how long the interventions were, what the typical interventions look like, who the participants were and things like that? Just so, when you're digesting all of these different studies, what I'm trying to communicate to the listening audience is is what's kind of the size and scope and what do those studies actually look like that you're looking at in terms of how relevant it might actually be to them?
Speaker 2:Sure. So first of all, we only included experimental studies or quasi-experimental studies, meaning like they're randomized into different groups or at least somehow put into two separate groups, and that's how we compare those different groups or interventions. The studies, the durations of the studies were quite different, so some were as short as three weeks, others were as long as 23 weeks or a couple of months, almost like six months worth of training. Sample sizes, you know, anywhere from maybe 10 people in a study, depending on if it's a crossover design up to about 30 or 40 participants. So sample size is not that large, and I'd say that really makes things interesting when you're looking at combining the data.
Speaker 2:Look at all sorts of sports. I think the majority of sports was running. I think most studies included runners. There was some with cycling, triathlon, cross-country skiing, and in terms of performance level, they were all endurance trained athletes. But there was a kind of a dichotomy here of athletes that were either considered recreational or competitive, and so we were able to do several analysis based on the different characteristics of the participants included in our studies.
Speaker 1:Yeah, and how would you more colloquially define that dichotomy of a recreational athlete versus a competitive athlete? Like, like, make it real to the person listening and who's going to be in one category versus who's going to be in the other category? Sure.
Speaker 2:So it's interesting because what we originally did was we used the subjective description that each of the respective authors used, but we found something that was consistent across those studies. So recreational athlete we've called somebody who is just doing a sport, specifically, so runners who are running consistently for a certain period of time. You know, we can say, let's say, two months, three months, six months, and they're training two, three days a week, but they're not necessarily competing, whereas we're looking at competitive athletes. We say somebody who might be a tier one athlete, a national or provincial state level athlete, olympic level athlete. So while there's certainly a range of competitiveness across even that group of individuals, we found just those who are technically competing at some degree level that's been classified previously versus those that haven't been. And that's how we originally separated the groups.
Speaker 2:It's very common to separate individuals by their VO2 max and say, okay, well, we have these people that are in a certain VO2 max and others that don't, and we're going to slip them right down the middle or come up with some sort of arbitrary value. And there's certainly an issue with that, because when it's a continuous outcome measure, how do you know where the right number would be? And then the other issue with something like that would be well, and I'm sure most of your listeners know that VO2max isn't really the be-all, end-all right. Submaximal performance is really something that can influence performance. So, yeah, we use basically those subjective ways to differentiate.
Speaker 2:However, what was interesting was we did a post hoc analysis. Basically after we did all the analyses, I looked at the VO2 max for those different groups and they were statistically different, which is quite interesting. So it actually says, hey, maybe there's something to the way in which we categorize these individuals. So the recreational athletes they had a VO2 max of roughly 55 mils, I think, plus or minus five mils. And the competitive athletes they were around 65 mils, plus or minus five mils, and included both males and females in those categories. So there's why we might have an even larger standard deviation.
Speaker 1:So you ended up categorizing the recreational versus the competitive athletes, kind of along their VO2 max versus the whatever they were categorized previously. Am I understanding that correctly?
Speaker 2:Well, no, actually what it is.
Speaker 2:We didn't necessarily categorize them by their vo2 max, they just so happened to just backed it up essentially yeah, we looked it up retrospectively we said, hey, it's interesting that this subjective way in which we decided to to separate these athletes also showed some characteristics that were very different and their vo2 maxes were very different. So it was kind of an interesting finding which sounds somewhat intuitive. But it's nice when you do it backwards and you see, oh, it just so happens that it's more of a real differentiation rather than some arbitrary reason to separate their VO2 maxes.
Speaker 1:I'm going to pick up on that backwards theme a little bit because I was just thinking about this. So we've already described the outcomes that you were looking at time trial, performance and VO2 max. Then we've looked at the subjects. They're either recreational or competitive. The interventions is kind of the first piece of it right. So polarized versus and we'll get into a coaching discussion. I'm sure that it's really not a versus thing once you get into actually coaching athletes, especially when you look at it over long periods of time. But polarized versus pyramidal training and we've discussed this across a few different guests on this podcast. But for the people that are new, let's just describe that really quick, just so they know what types of intervals and what types of work kind of goes in each one of those categories.
Speaker 2:Sure. So first I think it's important to describe that there's these different zones of training and of course there's different models that people could use. In physiology we typically use a four or domain model In the training intensity distribution research we typically divide to three zones below your first lactic or ventilatory threshold. So basically very easy work before you start really to see some sort of accumulation of lactate in your blood or before your ventilation really starts increasing. And then you have your zone two, which is I guess we'd say is really your threshold zone, and so maybe your race pace or racing should be somewhere in that zone two, depending on the distance of course, but that's where you'll start to see an increase in lactate and oxygen consumption, but you'll still reach a steady state. And then zone three that's where you're above your maximal metabolic steady state. So now you can't reach a steady state, you can only stay there for a certain given amount of time, of course, theoretically, and at some point in that zone or domain you will reach your VO2 max if you stay there long enough. And so if you think about it, that first domain, that's your easy effort kind of training. The middle zone is your threshold somewhere. Racing sometimes typically is there. And then above that's where interval training would be, anywhere from long duration intervals all the way up to sprint intervals.
Speaker 2:And so when we look at the different training intensity distributions, I think the big one that we talk about a lot is polarized training, and that's where majority of the time you'd say maybe roughly 80% of the time would be in that first zone or domain and then 15, 20% of that time would be in the third zone there, and then maybe a little bit of time in that middle zone.
Speaker 2:And then we have our threshold intensity distribution which is I think that's the next, that's really where the two biggest comparisons have been historically where majority of the training is in that kind of that middle zone there, with the next next amount either in the zone one or zone two sorry, zone one or zone three. And then there's a third training intensity distribution called a pure middle model, which is actually a very common model. I think it's something that's been done quite a bit in the past, but we only kind of more say more recently, described it as a pure middle model where the majority of training would be in zone one, then the next would be in zone two and then subsequently zone three. And so the reason why I say kind of we've only recently started discussing it or calling it pure middles because a lot of times we used to call threshold training Right yeah, we used to call it a threshold model, when it actually really maybe would come up with more of a pure middle distribution.
Speaker 1:Yeah, and I've been.
Speaker 1:It's funny that you mentioned the threshold model. So I've been coaching long enough to kind of remember some of the original premise behind that type of training, which kind of alluded to the fact that we would call that the most trainable aspect of an athlete's physiology. We used to say the most trainable system, but we've kind of moved away from that vocabulary as well. And because it was the most trainable part of an athlete's physiology, well, naturally you would have to train at that intensity in order to facilitate all the adaptations and that all the adaptations that are fundamental to performing at that, at that intensity, in order to facilitate all the adaptations and that all the adaptations that are fundamental to performing at that, at that intensity. Now, that's a, that's a history lesson, not what we're actually going to, not what we're actually going to go to. But I do the newer vocabulary because I think it starts to move. It starts to move away from that legacy and this like pigeonhole ideology that you have to train at these certain intensities to elicit the adaptations of those intensities.
Speaker 2:Yeah, it's interesting because we start to think about what's the physiological response that you're trying to achieve versus what's the performance outcome that you're also trying to achieve, and they're very different in terms of how you're trying to train.
Speaker 1:Yeah, Okay, so we've got these. We've got these different training intensity distribution models. How did you figure that out across all of the studies? Because there's a number of different ways that you can do it. If it's a cyclist, you can use power meter. If it's a runner, you can use pace. All endurance athletes can use heart rate. What were you fundamentally like boiling down? How were you fundamentally boiling down the intensity that the athletes were doing during these training interventions?
Speaker 2:So that's a very good question, and we actually we did this in two ways. And so there's and we've discussed this previously as well, or you and I have spoken about this a little bit in terms of something called an intention to treat analysis versus a per protocol analysis, and so the first way that we analyzed how they did their training was we kept the athletes in their original groups. So we said, hey well, the way that the study was designed was, they said, this group is doing a polarized intervention, this group is doing a threshold intervention. Let's just say this is what it is and this is what their intended distribution was supposed to be. So, based on what the original researcher for those respective studies had stated, that was the first analysis. And the second analysis, what we did was we were able to collect all of the heart rate data. For when I say we, all of the collaborators on the study were able to look at all of the heart rate data that was collected through their entire intervention. And what they did was they looked at the time in zone, based on heart rate. So there's several ways that you can. Of course, you can measure workload, as you mentioned some of them. You can look at power on a bike, you can look at speed with running, and then there's different ways in which you can calculate that doing, you know, looking at both internal and external measures.
Speaker 2:In this study specifically, heart rate was the only consistent measure that we had, and not just that we had, that would be consistent across studies, but just that was consistently, I guess, collected. Because some of the studies were a little bit older as well. I think we have one study from 07. And while that doesn't sound that old way, the way to conduct research at the time maybe we were just using heart rate monitors. Of course it was in runners as well, and it was just at the time, the best way to collect the data. I mean not necessarily for that study, but I'm just saying overall, heart rate was just very commonly used, and so that was what was consistent across studies. So we look at time and zone using at a given heart rate and then, given that time and zone, we're able to determine how much time each individual athlete spent overall throughout the intervention. And in several studies we're actually able to look week by week as well.
Speaker 1:So here's my bonus question with that If you're looking at each individual study and trying to and using heart rate for all of them to create a standardized intensity approach, you also have to have a way to determine what each individual participants ranges were based off of heart rate. And, as you and I both know, establishing that on the front end with any one individual study can go several different ways. Sometimes they do, you know a ramp protocol, vo2 max test. Sometimes they're taking training data. Sometimes they're doing you know this, that and the other. How did you stand? How did you not standardize? But how did you figure out that component? Because you have all of these individual. You have all of these individual athletes that are doing different interventions. You have heart rate data on all of them, but in order to categorize the intensity, you have to first calibrate what heart rate means what zone for each athlete. So how did you go about doing that?
Speaker 2:Yeah, and actually it gets even messier than that.
Speaker 2:To make this more interesting. The way in which the individual authors determined the different zones was also different. And I don't just mean did one group use lactate, did one group use ventilatory thresholds? But some groups wouldn't use inflection points. They would say, well, we're going to look at this. You know, two millimoles of lactate would be their first and four would be their second, or two plus one millimole would be consumed, and so they were very different across the studies.
Speaker 2:And what you do, if you're able to synthesize the data properly and you're looking at, you're running a true meta-analysis here you do something called the Oxford approach, which is where you combine all the studies first, regardless of the fact that, hey, we know there's these differences, maybe in the participant characteristics, and in this case we're talking about how we would determine those different thresholds and then determine, after we've pooled that data, did that actually influence the results? And so it sounds like, well, of course it's going to influence the results, right, and so it sounds like, well, of course it's going to influence the results, right. I mean, these are all these different measurements that are different methods to determine the same thresholds in terms of, you know, are we using gas, are we using blood measurements. Where are we taking that blood measurement? Is it from the ear, is it from the finger, is it arterial, is it venous, those types of things. And so you know there's all these different ways to do that. And so you'd say, well, theoretically that sounds like for sure, this is just a big mess. How can we pool all this data together and actually get something that's consistent across all studies to be able to pull the data?
Speaker 2:Now you know, if you're looking at an individual participant and you're going to say, well, I want to know, am I seeing a change over time? Then you're going to say, well, I want to know, am I seeing a change over time? Then you would need to say, yes, I need to be very consistent with how I'm measuring this data. And the reason why I'm saying that is because I don't want this to be misinterpreted as saying, oh well, it doesn't really matter which way we do this. A hundred percent it does. But when we actually pooled all the data together, there was no heterogeneity or what we'll say a statistical heterogeneity across all the studies when we look at the results, meaning that the variability was so minimal that it actually didn't matter when we pooled the data.
Speaker 2:Okay. So it's very important to say, though, while it may not have mattered when we're looking at a little bit of difference, when you're training, it can be maybe a little bit below, a little bit above it's not going to influence you that much Maybe your training it can be maybe a little bit below, a little bit above, it's not going to influence you that much maybe. But when you're looking for change over time in an individual athlete, then of course it definitely matters. Right, if you're going to assess it from the beginning of an intervention to the end of an intervention, then yes, you need to be very consistent with those measurements. But overall, a little bit of variability here or there actually didn't influence the outcomes.
Speaker 1:You know, what's interesting is like the inverse of that is normally what I have to deal with as a coach, when I have an athlete that does some sort of graded exercise test in one lab and then, for whatever reason, wants to do it in another lab with another protocol, marrying those two up in terms of were they better, worse or the same during those, both those points when the protocol is different, when the equipment was different, there are a whole number.
Speaker 1:Even the technicians doing the, doing the tests are different. In many cases I won't say all cases, but in many cases it's hard to reconcile because you don't know if this, if a test that uses three minute stages versus a test that uses four minute stages and you see the inflection point at, you know X minutes per mile or kilometers per hour or whatever, you don't know if that's, if that has the same meaning when the, when the protocols are fundamentally different. But what you're saying is that when you pool all of that, it kind of doesn't matter, like those differences, kind of like they're not as I don't know what the right word I'm searching for, but they tend to. It just tends to not matter, I guess.
Speaker 2:Yeah, but you're still onto something important here, though, right, like if you're going to be training and let's say you're training, you know five Watts below or five Watts above your threshold, well, I mean, physiology is kind of continuous. Everything's kind of always happening at once, and to what degree, and if you go a little bit less or a little bit more, well it's not at least the results of this study suggest maybe it's not going to have that big of an influence. But what you were saying, though, is if you're going to send an athlete to one lab to do a test, even if it's the same test but it's a different person interpreting yeah, that definitely would be a problem, because now you can't tell if someone's improving, and that's where there's a problem for sure. So you're correct to say that, yeah.
Speaker 1:My colleague, Lindsay Golich, over at the training center, who I've known for years, is really famous for saying and I don't know if she's the, if she can claim origin over this quote, but I'm going to give her origin over it that we will always take a consistent test over the perfect test Meaning we get. Sometimes we get caught up in okay, we, in order to do this threshold test, we want exactly these stages and exactly these speed ramps and on, and then 10 years later we come up with some other version of that because of some nuance that somebody thinks is important. And what we'll always come back to is the test might not be perfect, but if you do it consistently, you're going to be able to extract more information out of what the change over time is, because you're not having to also interpret what the change in the protocol is and how that's affecting the athlete and the protocol is and how that's affecting the athlete.
Speaker 2:Yeah, I like to think of it as if you're getting on a scale and it's five pounds off right and you want to see if your weight is changing. Well, it's always going to be the same five pounds off right and so you'll know are you going up or you're going down, but it's always going to be consistent there.
Speaker 1:Yeah, perfect, okay. So let's get down to the nitty gritty here. So we've got these two types of training right Threshold training and VO2 max training, or polarized training. And sorry, pyramidal training and polarized training.
Speaker 1:I want to make sure I've got parallel structure there, sure, two categories of athletes the recreational and the competitive athletes and then the pool set of all of them and then two different outcomes time trial performance and improvements in VO2 max. It's two by two. If you want to think about it like that, let's use the broadest lens possible, right, sure? Did any of the intervention, either of the intervention categories, affect either end performance and time trial performance or VO2 max?
Speaker 2:when we're looking at the groups as a whole, so we're looking at it as a whole and this also includes other groups as well. We look at different distributions that just so happen to be included. So I think there's a total of five different types of interventions. One of, the one of the groups showed no, there was no difference at all. And the other one showed no statistically significant difference. And I'm very particular about how I say that. Okay, that's very important to say it that way. And so when we look at polarized versus pyramidal, there was no difference between the groups.
Speaker 2:When we again we're just looking at everything as a whole right, I said I'd use this idea or this concept of I can't at the moment it's eluding me. I've already said it the Oxford model, basically how a look at the results and then kind of figure out everything after that. So there's no difference between polarized and pure middle. We look at everything together, but there's no statistically significant difference across any of the other comparisons. And what I'm saying here is well, maybe the magnitude of the effect for the other groups was large.
Speaker 2:So for polarized versus pure middle, maybe there was zero was the magnitude, whereas the other ones, you could say maybe the VO2 max increased by five mils, but there is such a large degree of error, of statistical error, there that it just didn't reach a statistical significance. And I can actually speak to that likely because the sample sizes were too large for that. So you'd see very large standard deviations and you're just not going to be able to determine one if it's actually a true result. And then also the direction and the magnitude of those results. Right, because the smaller the sample size when you look at a study, then more room for error.
Speaker 1:Do you think that this is purely an artifact, though, of the sample size, or do you think that there are other things kind of going on as to as why you are not seeing anything? At the end of the day, for the other groups.
Speaker 2:Definitely, I think it's sample size there's very small, there's very few participants. I think we had some that was only like 20 or 30 total participants in the comparisons and interestingly, when I compared between the protocol and the intention to treat for one of the groups, the comparison went from one side all the way to the other. So it went from favoring one intervention all the way to the other and that really suggests a sampling error, meaning the sample size is so small that maybe there's three participants all the way to one side of the distribution. Basically, I'm just saying it's just too small to really tell what's going on there so is the take-home message here I'm trying to bait you into answering some questions.
Speaker 1:Here is the take-home message. It doesn't matter for any athlete. Meaning if you do any sort of willy-nilly, you know type of training structure, high intensity, threshold intensity or whatever the end result when we're looking at time trial, performance and rvo2, irrespective of the athlete's experience level or how good they are Like, is there any difference at all between these and if there is, how can we start to distill through that?
Speaker 2:So that brings me to, kind of that, my secondary analysis that I looked at. So when you see that there's no difference, you say, okay, well, am I sure that I combined all these studies properly? And so we're looking at something called the statistical heterogeneity. And so if there is this degree of variability, you say, well, what confounding variables can influence the results? Did age influence it? Did certain participant characteristics or training characteristics? And so we looked at all of these different variables and specifically with polarized versus pyramidal, because one, there was no difference, not that there was no statistically significant difference, and the sample size was large enough. And so this was the only comparison where there was enough participants to look further into the analysis. And when we looked further into the analysis, we found that actually performance level matter, which was quite interesting. So there was a difference between which type of intensity distribution polarized versus pure middle benefited one type of athlete versus another.
Speaker 1:And so what was that specifically then?
Speaker 2:Yeah. So with respect to polarized, we found that competitive athletes tended to benefit more from a polarized distribution, whereas recreational athletes tended to benefit more from a pure middle model. Now, when I say tended to benefit, the reason why I'll be very particular about my terms is because there wasn't a statistically significant difference between those groups. So it was actually 0.6 standard deviations. Basically, it's for that type of population that's quite large. So they really were different. Not only that, they went in completely opposite directions. The only thing was is when I then went into looking at these subgroups, specifically the recreational versus competitive athletes, the sample sizes start to get smaller, right. So now we're taking these interventions, we're cutting it in half and now it's even smaller, and so just the magnitude of the effect. So basically, it was about just under a half the standard deviation for both groups, but all the way to the other direction. So recreational athletes tended to benefit from polarized and again I started from pure middle and competitive tended to benefit from polarized.
Speaker 1:It just didn't quite meet statistical significance when we're looking at that exact magnitude there okay, let's take a quick break in the conversation with michael to bring in cts coaches ryan anderson and adam ferdinandson to expand on this aspect of how elite athletes might actually adapt differently to different types of workouts as compared to their non-elite counterparts. Okay, ryan, so we have this like concept from this paper that elite athletes generally do better underneath a polarized structure. We'll just say better athletes generally do better underneath the polarized structure and athletes who are not as good do better underneath a pyramidal structure. Let's try to like like break this down for what this means for, like your group of athletes, because you coach athletes that are both at the elite level and at the non elite level. How do you put this piece of literature and what Michael and I have been talking about kind of into context just in in the day-to-day, from a day-to-day coaching and training perspective?
Speaker 4:So one takeaway I have is defining like better athletes are likely to have more overall training history. It can be kind of a self-selection and that they've become a better athlete from all that training history or they are an athlete who can put in consistent training to become a better athlete. So this was my first thought in these two different ways to label a better or experienced athlete or a less experienced athlete. More training history typically leads to a better athlete. More training history means you can reach a plateau with your growth. More training history means you can reach a plateau with your growth. So a phrase I like to use with my athletes is like okay, what lever are we going to crank on in training? And the more training history you have, the more experienced.
Speaker 4:You kind of have to go to the more extreme end of the spectrum or the zones or on that polarized end of really hard intensity. If an athlete is self-coached, I typically find they are less likely to have hit these intensities before, maybe out of fear, or especially ultra runners like what's the point of hitting these intensities? So it is less likely to be an intensity they have trained at and therefore it's an intensity they're going to respond better to. So that's kind of my thoughts, with better athletes needing more intense work to respond, and then with the less experienced athletes, you can just go with the simple principle of like, hey, don't screw it up, they don't have a lot of training history yet. Whatever you give them, they're going to keep improving. They don't have a lot of training history, which means they may not be as durable and able to withstand really hard workouts. So don't screw it up. Give them a little bit of everything and they're going to keep responding and growing.
Speaker 1:I didn't even think about this when I was interviewing Michael, but the fact that a good athlete with a lot of training history, that might be an elite athlete, it's a little bit of a self-fulfilling prophecy that they have done workouts at a variety of intensities because you don't get to that level, you don't get to that experience without having that big variety of intensities.
Speaker 1:Similarly, on the other end of the spectrum, most newer athletes who are inexperienced, don't have that variety of intensities for whatever reason. There might be a fear factor, they might not just know how to do it, they might be running recreationally, they want to run predominantly at a less intense level and so in many ways, when you think about it, like the kind of the results of this shouldn't be all that surprising just because of that self-fulfilling prophecy, you kind of like get, you kind of get to this area, or you get to this level simply as a byproduct of all the training that you're doing, adam, I kind of want to like throw it over to you as well. So we've talked about like polarized and pyramidal training, kind of in this, with, with this like overall architecture, but I was wondering if you could actually bring that to reality for the listeners in terms of what does that actually look like at the workout level? What sort of workouts would fit into this construction that we've been talking about for the last several minutes?
Speaker 3:Yeah. So this honestly isn't something that on a day-to-day basis. I look at one of my athletes' training plans and say, okay, we're going to make it more pyramidal this year or more polarized this year. It does happen somewhat naturally from the level of the athlete, kind of like you were describing Coop. But a more polarized plan would probably include more of the very high intensity workouts, so what we might call VO2 max workouts or running intervals kind of colloquially here and then pure middle might include a greater percentage of that middle range, the tempos and the steady states, and that's a really big, big picture, broad brush way to describe it.
Speaker 3:So someone that's more elite, you might spend more time hitting those workouts, more volume within those workouts. So maybe you're talking about a four by four minute workout, something pretty chunky, even up to like a five by five for the really really intense workouts, whereas if I have a newer athlete and we're trying to do something that same intensity range, I might do six by two or by three, you know some sort of more bite-sized variety like that. And it kind of reminds me of the principle of don't go there until you need to go there, and so many of our newer athletes don't need to go there. There's a practical and psychological element as well of whether or not they can actually execute those workouts if we gave them bigger ones, whether or not they're mentally ready to handle that and are used to pushing at those higher levels of exertion, and I think that takes quite a few years to get really good at.
Speaker 1:So I'm going to boil it down to like really simple. So a quote, unquote polarized workout in our vocabulary would be a running interval workout and that's something like five by three minutes hard, three minutes easy. Seven by three minutes hard, three minutes easy. For a really good athlete it might be four by five minutes hard, two and a half minutes easy, something of that construction, where the total amount of time at intensity is anywhere between 12 and maybe 20 minutes at the very maximum. A pyramidal structure will also include those workouts, but then we'll also include what we call threshold workouts or maybe even steady state workouts. So threshold workouts or tempo runs, which would be our vocabulary, would be something like four by 10 minutes hard, five minutes easy. And rather than go through all the different like permutations of that, I'm going to drop a link in the show notes to an interval workout article that I wrote for the Train Right website.
Speaker 1:The train right Website that you can look at and you can.
Speaker 1:It gives you a menu of any of these workouts that we have kind of like ever prescribed in like a small, medium, large format based on your actual experience level.
Speaker 1:And, interestingly enough, just to give a little bit of a plug to this, ryan's working on an AI project with me where we've had to take the this kind of construction of workouts and bring it to life to people who are like applying to this ai project and make sure that we get them in the right beginner, intermediate, advanced classification to make sure that they have the right volume of intensity at each one of these types of each one of these types of workouts.
Speaker 1:We're going to spare that discussion for later as a little bit of a tease for a podcast that will probably come out six weeks from now with the person who's designing that. But it's something that very much we have to bring to light day to day from a coaching perspective is not just to look at this research but also look at how are we actually going to program workouts based off of this. So I'm going to like colloquialize this. If people are getting lost in the polarizers pyramidal, the better athletes benefited more from higher intensity interventions, and the athletes who weren't as good benefited more from the what I'll call more medium intensity or threshold intensity types of interventions.
Speaker 2:Fair categorization there oh, definitely, that's actually kind of one of the things that we were considering is probably why is this happening? Like, is it just it had to do with that intensity? Yeah.
Speaker 1:Yeah, so. So that was leads me to my next question why so, if this is a like a real finding right, why? Why would this happen in your mind If you kind of look at this through your practitioner's lens? Why would we see different athletes improve differently or benefit more I'm going to use that term benefit more from a different intervention?
Speaker 2:So, in terms of the analyses that we ran, there was no difference in terms of the total training volume, the number of weeks, et cetera for any of the studies. When you know, did that influence those results? Weeks, et cetera, for any of the studies when we're you know, did that influence those results? And so the reason why I bring that up is because a lot of people would say, well, if you're going to do a polarized training distribution, you're going to have to do way more training volume for that to be beneficial. And so what we found was, well, that didn't really matter in this case, it didn't really influence the results. So we, you know, in terms of our analysis, there wasn't anything that very specific that we could point out other than, like I said, the performance level. So you say, well, why would performance level influence this?
Speaker 2:And you might think, well, the higher trained you are, the more volume of intensity you can handle, Whereas the less fit you are, maybe you can't handle as much training in zone three. Either you physically burn out while you're trying to do it, or maybe you're just not recovering well enough. It could be any number of factors that we can discuss, but probably it's that well these higher trained athletes handle more intensity, they recover better and they can generate a stimulus for change from that, whereas the recreational athletes can't. The other way of looking at it could be well, where is your relative threshold? So one way of looking at it is well, here's your intensities. And then the other thing is there's a lot of literature that shows that recreational athletes well, maybe their second threshold is around, let's say, 80%, and maybe- 80% of their VO2 max.
Speaker 2:Sorry, yes, 80% of their VO2 max. And that maybe competitive athletes, typically around 90% on average. Well, so then where would you say the weak point is for the competitive athletes? Well, it would be pushing their VO2 max. And then, so maybe you need to do more higher intensity training to push your VO2 max. And then, when you look at the recreational athletes, if they're doing a little bit more threshold work, is it? I mean, this is we're just kind of discussing here. I can't say this based on my work, but we could say, well, is it possible that maybe they'll benefit from doing more threshold work to maybe push that second threshold a little bit more, or just not as much high intensity effort, and so maybe that's where there are limitations. We want, maybe we want to shift the threshold a little bit and so that could be another way of looking at this.
Speaker 1:Well, certainly, because once again I mean having work, you know, having had a physiology lab and access to lots and lots of results, and you kind of recognize the same thing. One of the key differences that normally shows up when you see a whole lot of athletes is the better athletes have their threshold. However, you want to define threshold at a higher percent of their VO2 max, sometimes almost to a fault, to where you've got to go through different course corrections. Where an athlete's threshold is relative to their max is actually one of the bigger key pieces of data that we can extract from a graded exercise test, because it tells you and this is part of this research right here it tells you what lever you can push on, what button you can push, and so if your threshold is really close to your max, doing maximal, improving that max is going to have a bigger benefit. If your threshold is way, far away from your max, it's probably both, and maybe you could make an argument that the improving your threshold should be more of the, should be a bigger part of the emphasis. You can kind of boil it a lot of ltv02 tests down to just that when you have a new athlete and if you're trying to extract information related to what you want their training program to actually look like, what you want their periodized approach look like is just look at their percentage of VO2 max or their percentage of threshold as compared to VO2 max and take cues from there.
Speaker 1:Now I'll back up a little bit before somebody accuses me of being myopic or something like that. That doesn't mean that all of the training goes into that bucket. It just means how. It just means that you take a little bit of a different approach and shade more of the training to the things that matter more and shade the training away from the things that matter the least. When you look at it over a longer period of time so nine months, 12 months, 24 months and things like that If you know an athlete is quote unquote weak in one area, you just design everything so you have a. You have more of the training to accentuate that.
Speaker 2:No, exactly, and that you know, it's exactly the way that I think it should be done as well, and it's I like how you kind of said well, it's just kind of shifting a little bit of a focus more into where their limitations or where their weakness is, and I think that's very important.
Speaker 2:In fact, you know, hopefully we're going to be analyzing some data to look at. There's a study that came out, a 2022 study. It's actually one of the studies that we included in our analysis that actually periodized, pyramidal and polarized training, and so what we're going to do is actually look at responders versus non-responders and look at their relative thresholds and see, well, maybe there are some responders that benefited more based on where their threshold was. So, for instance, if they had very high second thresholds, maybe they benefited more from a polarized model to push the ceiling or push the roof, whereas maybe those who tended to have lower threshold benefited more from a pure metal model. And then, when they in terms of the periodized approach, and so we're going to, we're going to kind of reanalyze our data to see if if that may actually show something there.
Speaker 1:Yeah, yeah, and I mean I think this is a good pause point to kind of move outside of the research and into some of the more practical elements that you just mentioned. It would be very rare and I'm speculating a little bit on this, but I don't think that that's too far of a speculation it would be very rare that you had an endurance athlete with any sort of reasonable history two, three, four or five years of training or something like that was only using one intensity domain for their intensity when you looked at it over long periods of time. Most of the time they're doing zone three and zone two and zone one and zone back to zone two and zone three when you look at it, sometimes within a week, sometimes with even with even a session like. So that's the way some, you know, interval sessions would kind of be designed, and so I think that when we start talking about this, we have to realize that it's not a going back to my kind of my first point.
Speaker 1:It's not a versus proposition, it's when you roll it into the, into the practical elements.
Speaker 1:It's it's how much proportion are you spending at these intensities versus these intensities? Is it 50-50?, is it 70-30? And I definitely think that you can take some shades from that. You can take some shades of that with this particular research and we have history to kind of like back this up as well as well that generally speaking, athletes with a longer training history and that are quote unquote better are going to benefit more from higher intensity work and less from threshold work. And then the opposite might also be true with athletes that are a little bit earlier in their whole endurance journey, like if you want to take the biggest, broadest brushstroke from a coaching standpoint for this type of research. That's what I come away with. It's just like what intensity distribution would I use over a 12-month period with any type of athlete? And if they're more experienced, I'm going to shade that intensity distribution towards more higher intensity stuff, and if it's more of an entry-level athlete, we're going to spread it out a little bit more.
Speaker 2:Yeah, because I mean, if you're a highly trained athlete, you may respond much quicker, so you may be able to put more time into something else, you may recover quicker and it changes right. It's like you know, like we said earlier, how we're comparing training intensity, distribution, interventions, and so it's not just which intervention is better, but when you go down into the characteristics of the individual, why might one individual benefit from one distribution over another? And then you say, well, now that they've adapted, are they now a different individual and do they now subsequently need?
Speaker 2:a different model, and so it's just what do you need right now? And then, as you adapt, where's your limitation? And then let's address that limitation.
Speaker 1:Yeah, and that's actually where testing can really come into benefit, because you see the effects of the training, but then you also see if the limiter that you previously thought was there has changed and if there is a different limiter that you now need to address. So, like wonderful wrap up there. Okay, let's take another quick break in the conversation to bring back CTS coaches Ryan Anderson and Adam Ferdinandson to specifically discuss how we use physiological testing to further individualize the training that we are giving to our athletes. Individualize the training that we are giving to our athletes. So, ryan, you've actually had athletes come into our physiology lab, do physiological testing and then, based off of the results of that physiological testing, had to decide what to do with their training that might be different from what you originally planned. Why don't you describe that process?
Speaker 4:Okay. So this athlete had a robust training history, which was also in training peaks, which is always so nice when we can look at their data in training peaks and use our ways of finding specific intensities, workouts at those intensities, et cetera. So this athlete's training history is robust. They put in a lot of volume and naturally, from onboarding this athlete and talking with them, it was like, yeah, they did a lot of volume, not super high intensity. I'm not seeing a lot of true like VO2 max running interval workouts. I am predicting that is not going to be their strength.
Speaker 4:That wasn't that hard to conclude. They go in the lab, sure enough. Their VO2 max is a relatively low percentage of their threshold, but the magnitude that I saw that at was like, oh crap, this is an even bigger thing that we need to leverage. This athlete's goal events are 100K, 100 mile, so we want to be specific to those work endurance, bigger volume that they can handle. But seeing that data reemphasized, to me it is well worth this athlete's development and getting most prepared for these events by doing an additional running interval block that I would have originally planned. So in this case the testing showed what was easy to hypothesize and be correct, but the magnitude and just seeing the data was a reminder that, while this intensity is not most specific to these athletes goal events over the next six to eight months it is going to greatly benefit them and help their development so you're just to like encapsulate that a little bit.
Speaker 1:Their threshold compared to their max was, let's just say, 70 or something like that. We would consider that far below their max. And then what you did as a consequence of that is you shaded a little bit more of the training towards that specific intensity in order to push it a little bit closer to the max exactly and we.
Speaker 1:So this is where testing testing can become actually a better tool than actually looking at the training history, or it is something that makes you double down on what you were going to do earlier based off of the training history.
Speaker 1:Most of the time it's the latter, because most of the time what we see in the physiology lab is a reflection of what the athlete has actually done.
Speaker 1:Lab is a reflection of what the athlete has actually done, and if you have very good training, if it's all logged in training peaks and they've got good notes and it's three or four years worth of data sometimes, there's most of the time there's not any sort of like big surprises right, you got what you got, it's been revealed through the training process and you're just getting a little bit of a more precise lens on it through through through actual physiological testing.
Speaker 1:But having the data as opposed to your opinion of the training process, it becomes one of those things that kind of engenders some further confidence, especially for a new athlete, because now you have two directional arrows that are pointing the same way. One is an analysis of the training, the other one is an analysis of the athlete's current physiology, a snapshot of their physiology, and when you have both of those kind of pointing in the same direction, it gives you and the athlete a lot of confidence for what you're actually doing. I'm going to try to put some numbers onto this at the very end of this quick conversation, just so athletes who have physiological testing can kind of bring it to light or turn it into reality. But, adam, I'm wondering, from your perspective, what do you have to say to this concept of using physiological testing to start to shade the training, either based off of Ryan's example or of any anything that you've kind of encountered?
Speaker 3:Yeah, well, in general, it would be very nice to have physiological testing for all of my athletes. I have physiological testing for two and one of them was, I don't think, done very well, went over that with someone that works here internally. And then the other one it was lactate only. It just it kind of checks out. It looked good. We're going to continue our training.
Speaker 3:So these examples where we see a really clear directional arrow are really nice. But in lieu of that, and even I'm sure if we did more testing, the magnitude of that directional arrow probably doesn't outweigh a lot of the other factors that we're balancing Whether the athlete needs to go work on technical terrain, more fueling or anything like that. I think the situations where it leads to a clear decision on training are kind of few and far between, at least for me personally and the athletes that I work with. So I make a lot more decisions based off those kind of former things. I mentioned the more practical parts and you know, occasionally without testing, you can see something pretty clearly in training peaks and in their data, but not as often as I guess as I would like.
Speaker 1:Okay, so really good point here. So a big piece of Michael's study. It was digesting training data and that was that's what he spent an inordinate amount of time actually doing with the subject pool. And one of the reasons that's so important as a coach trying to get a handle on a new athlete or actually what is going on with one of your existing athletes is that you have many data points to pull from. Not all those data points are going to agree with each other, but you have a lot of them.
Speaker 1:One of the disadvantages to physiological testing it's a data point from a singular moment in time. It's a reflection of that athlete's physiology, their capacity at that one moment, which can change. And most of the time when we're working as coaches with athletes and we have testing data and training data, the training data is the bigger directional arrow. So if we have these two things that are both pointing in the same direction, it's great. But if you have these two things that are maybe, you know, 10 degrees off or something like that, more often than not we're looking at the training data to try to come to some sort of confluence as what to do, as opposed to the testing data, which a lot of people actually see is a little bit backwards, right, because the test is supposed to be accurate and you're measuring all these things. You're measuring oxygen consumption, you have lactate draws and there's a lot of people involved in it. It's usually a big effort to go out to a lab and things like that, but I think what a lot of people have to realize is that the scope of that actually is relatively limited, both in terms of what you actually do with it and then and then and also how much you actually, how much you actually rely on it. So, to your point of getting the right testing data, we could adjudicate that for another whole podcast and go through what labs to look through what labs to look at how to kind of discern if you're going to get good lab data or bad lab data. I'm not going to go through that right now, but if you do have, if you do have good lab data, I think one of the first things to look at that's relevant to this conversation is what is your lactate threshold compared to your VO2 max?
Speaker 1:This is kind of one of the key numbers to determine training architecture and we've said that if it's quote unquote low, that you can take this type of approach. And if it's quote unquote high, then you can take this type of approach. And if it's quote unquote high, then you can take that type of approach. I almost like to use like an exclusionary rule set when I'm looking at this. So if it's not high, it's kind of medium.
Speaker 1:So if you get somebody who's lactate threshold is within 95 or maybe even 99% of their VO2 max, they don't have a lot of room to run by doing a lot of threshold intervals because they're so close to their max already. So therefore you would take on a more of a polarized shade to their training and improve their VO2 max first. I think everybody else fits into the other category, meaning they can benefit from a wide variety of training and you can kind of take the training architecture wherever you want to. There are certain cases where that threshold is so low lower than 75% of their VO2 max where you would do a disproportionate amount of low intensity work, steady state work, tempo work and things like that, in order to bring that up before you even touch VO2 max work. But those are, I would say, kind of more rare. So for those of you that are trying to use lab testing to determine any of this, I would first encourage you to look at your training history, because that's going to be a better directional error. And just what types of training have you done? Have you done a disproportionate amount of low intensity or threshold work? Well, if you've done a disproportionate amount of that, you should change it up a little bit in order to get kind of a further, kind of further adaptation.
Speaker 1:I've had even elite athletes go to labs and I've been kind of ridiculously underwhelmed with what they have come back with. It's not, it's not. It's kind of not an easy proposition, but go find a high quality lab and see if those two sets of information actually come together in the same and are telling you the same thing. I need to do this type of work based off of the history and I need to do this type of work based off of the, based off of the physiology, and I need you to do this type of work based off of the physiology. And if those two things don't come together, go get an expert opinion on it. That's usually not the people in the lab, that's usually a coach or a practitioner who's actually had to synthesize all this information in order to know what to do. The labs are really great at telling you what your numbers are and telling you where, what your ranges are, what they, what many of them they're. The failure point of many of them is then being able to take that and put it into the kind of the real world, because they don't have your training history in a lot of cases and it's a big lift to look at all that training history. So don't think that you're getting like Baghdad or a bad deal or anything like that. It's just a big lift to do those things. But marry those two things up. Marry the training piece of it up with the testing piece. Don't overly rely on one or the other, and I think that is more of a surefire way to get a good direction on what type of training you want to deploy for the next three, six, nine months, however long you're like laying it out for.
Speaker 1:Okay, let's get to audience specific now. So this is an ultra marathon audience and pretty much only an ultra marathon audience. I mean, maybe less than 5% of my audience is going to come from Ultraman and Ironman and cycling and things like that. This is really specific. And cycling and things like that this is really specific. And whenever we talk about training studies that either are discussing high intensity, polarized training via two max types of intervals and things like that, and or research outcomes that are based on a time trial, some people will just roll their eyes in their back of the, in the back of their head, saying okay, what? Why is this relevant to me when my event is six hours, 16 hours, 24 hours, 30 hours? Why should I be looking at these? Why should I be taking cues from this research that that, on appearance, is in a different domain with a different time specificity? I'm wondering what you have to say to that just specific to the audience, and how we can make it relevant for them.
Speaker 2:I think that's a very important question and, interestingly, I don't think it's just an ultra endurance sport problem now you know, and I say to them I mean cyclists would say, well, we can't train the way runners do, or runners will say, we can't train the way cyclists do, and regardless of the distance. So what I've kind of learned over the last however many years is that, okay, well, we, you have a certain goal and you need to think of, well, what's the goal that you have? And in this case, if it's ultra endurance, and you say, well, what are the physiological adaptations that I need to occur to then be able to achieve that goal? Now there's a whole other component to add on to this with ultra endurance athletes and I've coached several Ironman athletes, and so that's about as close as I can get to thinking about ultra endurance and that's where nutrition really starts coming in. And then there's these other factors that I certainly am nowhere close to being a specialist, both on the science side as well as on the coach side, to get into. But what I would say is, if you need to increase your VO2 max, then you need to do a training program specific to increase your VO2 max. If you need to increase your sub-maximal thresholds be it your LT1 or your LT2, then you need to do an intervention that's specific to doing that, and it doesn't matter who you are. You could be a 40K runner or you can be a 10K runner or an ultra Pushing. That first threshold is the same type of training regardless.
Speaker 2:The interesting thing with something like ultra endurance is well, what's the need in the sport? So 10k runner would need to have need to be able to push at much higher intensities during their race, whereas somebody who's an ultra endurance at ultra endurance athlete is going to be spending a lot more time at a lower zone. So it's not necessarily the method to achieve that specific physiological adaptation. It's going to be the same, no matter who you are. It's just where. Where should you focus? And that's what I think is what it comes down to. Somebody was saying to me oh, should I do one-minute intervals, or should I do four-minute intervals, or should I do six-minute intervals? And now I'm generalizing big time, and I said this in our last discussion. Well, maybe six-minute intervals are the optimal way to achieve that physiological adaptation, assuming you're all the same level of training and the same experience.
Speaker 1:So then, why would you do four minute intervals if six minutes is the best Right? Always optimize, always optimize.
Speaker 2:Right. So you do the thing that's going to lead to the best. I was saying, if you've never done an interval session before, one minute's going to kick your butt just enough. You don't need to do six minute intervals, Right? But the point is, is what's the best way to achieve that physiological adaptation? And then that's the program to do. But the question is again going back to ultra endurance. Well, what's the need? What ultra endurance athletes need, and they need to be able to really push that first threshold as far as they can, which involves a huge amount of fat oxidation. And then there's a lot of dietary components to that too. So I'm not getting. The thing is, I guess I'm not giving the best answer to it, but what I'm doing is changing how we think about training. It's not that training is specific for an athlete. It's well, what should I in terms of the physiological approach? It's well, what's your goal? And then hit that.
Speaker 1:That that method to get to that goal, right? I mean, simply put, you can improve the physiology that's still relevant to the event, without with using intensity domains that are seemingly unrelated. That's the way I think about it is okay, yeah, you're doing a 24 hour event, right? You're well below your first lactate threshold, your first threshold, ventilatory threshold, however you want to define it for the entirety of that event. That doesn't mean that the only relative, the only way to improve is work below the first threshold.
Speaker 1:Sure, that's a big component of it, because that might be the most important thing, but that becomes really limiting at the end of the day. And if you're only focusing on one thing, because we talk about this concept of having a string of an athlete that can operate across a lot of different intensities, and if you push or pull on one, one part of the string, that whole string moves, so, so, so anyway, I mean that when I kind of come back to, when I try to answer the question of why are these intensities, they're seemingly so irrelevant to the event that I'm doing. Why am I doing these? I just I come back to that as is. You'll still improve and you'll probably improve more at the intensity that you have to actually operate at, because there are physiological adaptations that you are going to accentuate only at those intensities, or maybe predominantly those intensities that you can't at other, intensities that make the entirety of the athlete better.
Speaker 2:Yeah, we think about if you train your VO2 max. You're raising the roof. You're raising the roof, but you're raising the roof, You're also going to pull the second and first, or a long Yep, a hundred percent, a hundred percent.
Speaker 1:So what else I mean? What else can athletes and coaches kind of like take away from this from a programming standpoint? So this podcast is going to come out If I, if I get my stuff together. I've had a little bit of a podcast lull for the people that are in the know, and this is going to be one of the first few that I release after that lull. It'll be released in February.
Speaker 1:People are hopefully just starting to execute their plans right. They have their seasons kind of mapped out in front of them. I know what my apex race is. I know what the training races that I need to do in advance of that are. I've got my next six to nine months mapped out in terms of a racing perspective. So studies like this and thinking about what they mean are incredibly important during this time of year because you're trying to plan out the architecture for the entire of the season. What from the study can we kind of like use in that process to like really drill it home for either the coaches that are listening or the athletes that are kind of programming their own training when they're thinking about the season, when they're thinking about the season as a whole. So I think using.
Speaker 2:It's interesting. It brings us back to the idea or concept of reverse periodization we're starting with. Yeah, I know you're talking about types of periodization I love the vocabulary.
Speaker 1:Right like periodization is this and the opposite is reverse periodization yeah, I know, but, uh, I know.
Speaker 2:But so really what it comes down to is the results show okay, lower intensity is better for recreational athletes. So maybe if you're starting off your season, it might be better to start with a little bit less intensity, more low intensity and threshold work, and then maybe possibly shift into increasing the intensity as the program, as an athlete's program, goes on. Sounds like something we all already know and have discussed so many times, but we are seeing a very big difference between recreational, competitive athletes, and it does have a lot to do with their training status and so and their fitness in terms of their VO2. So certainly that would be important to consider.
Speaker 2:One thing that we didn't discuss that I will say that the results of the study showed indirectly was there was an improvement in VO2 maxes, which is what we're talking about. There was no difference across interventions and time trial performance, and so the reason why I'm bringing that up now is because the point is that it's not just going to be one method that's going to improve. You have to look at an athlete's whole program and make sure that you're modifying that program along the way as appropriate for that individual athlete, by constantly reassessing as appropriate and then shifting to address their weaknesses assuming it's likely their weaknesses to then to see those changes. If we stay consistent and just say, well, we're just going to do a pure polarized model and just keep it exactly the same, then we may not necessarily see the adaptations we're hoping for in overall racing performance, and so it was kind of an indirect result of the study that we saw. So it's again we're all science, just kind of looks at an intervention.
Speaker 1:It's hard to look at the whole program as a whole, and that's where the coach really needs to come in yeah, I like that takeaway though, because a lot of times you know you're going to combine I mean, you're combining a lot of different studies. But a lot of times we're combining a lot of different studies as well as what we've seen in the field to determine what to do with athletes and in in my mind not to use too much like confirmation bias or anything like that that this kind of validates the architecture that we use a lot of the time with athletes when we're looking at how to plan an entire season out. We want to do a variety of different intensities for some athletes. The better athletes we're going to how to plan an entire season out, we want to do a variety of different intensities for some athletes. The better athletes we're going to use, you know, a bigger distribution of the VO two max work for the more for athletes that are a little bit earlier in their journey or who are not as competitive.
Speaker 1:We're going to use more of a kind of more of a mixed model. I think that all of those things, we, many coaches, including myself I won't say all coaches, but many coaches, including myself we're already kind of like taking that underneath our wings to to put into practice. And this just makes us look at that and go yeah, okay. And if you're not doing that, I do think you should like take a step back and go okay, if I'm only using this type of model, or only using that type of model, or using a disproportionate amount of, of of polarized training for an entry-level athlete, take a little bit of a step back and like think if that's like the best thing, based on what everything is, what everything, what all the research results are actually telling you.
Speaker 2:Yeah, and then the thing to know when to change is is to test your athletes.
Speaker 4:We all like to say here do four weeks of this, and now do four weeks of that.
Speaker 2:If you don't test your athlete, maybe they needed to change sooner, maybe they needed to change what they're doing later they're able to keep benefiting.
Speaker 1:So testing is it's actually more important than we think it is testing and look, I'll actually like expand upon that a little bit, testing and actually really scrutinizing the workouts, because you can get a lot of value, just you can get a lot of value, just. You can get a lot of value that you are also looking to get out of with a test. If you scrutinize and you have to do this with a fairly fine tooth comb if you scrutinize the workouts, you can pick up on some of those little subtle changes in where they're performing at certain parts of certain parts of the intensity. Cycling, that's not all that hard to do. Running, it's a little bit harder, trail running it's. I would say it's kind of obnoxiously hard to do, but still you can. But still you can do it. And I think when you combine that with some type of testing, whether it's laboratory, field testing or a combination of both of them, you can really get a good picture with what's moving the needle and what's not.
Speaker 1:Yeah, and when it's time to change, exactly when it's time to change, that's the when it's time to change, that's the best thing, right? Because then you know that you're not. You're not kind of like beating a dead horse, so to speak. We're going to let you go, man. This is great, as always. Like I said, things will be in the show notes to this piece of research, as well as the previous podcast that we did, as well as all fascinating stuff. I appreciate you coming on the podcast again. Where can people get to know a little bit more about you, the work you do and the coaching that you do?
Speaker 2:So you can find me, my research and my website is evidencebasedcoachingca, and I'm also affiliated with the Sylvan Adams Sport Institute, and so I'm doing some research with them and hopefully you can be putting out some cool, some cool work in the next little while as well awesome and is the research going to be open access, or is this something where they're going to have to reach out to you to go and get?
Speaker 2:so this just I actually that's funny that you say that I tried to get this to be open access, because that's what I really go for. But I wasn't able to I know I wasn't able to make this open access, while I actually the delayed in the in the publication itself was that was part of the reason why I was pushing for open access.
Speaker 1:Okay, all right. No, fair, fair enough. I know this is a constant source of consternation amongst the field and we won't belabor that point here. News to say there's, there are ways you can get it yes okay, perfect. Thanks for coming on the podcast.
Speaker 2:I really appreciate it again yeah, no, thanks for having me again.
Speaker 1:I always appreciate his research because it tends to blend what we see in the scientific community with what he actually does with athletes on the ground, and I do think there are things that come about from his research that you can apply directly into your training. We are now getting into the racing season. We should be thinking about what types of workouts we are doing to help tune our bodies the best for the races that are in front of us. Also, thanks to CTS coaches Ryan Anderson and Adam Ferdinandson for offering their particular perspective, as well as CTS coaches Fred Sabatore-Pastor and Adam for their production assistance with this podcast and doing some of the background research. All right, folks, that is it for today. As always, this podcast is brought to you advertisement and sponsorship free. Once again, no ads, no sponsors on this podcast, and that is so we can deliver the most up-to-date, unadulterated, unfiltered information to you, and we do have a heap of that upcoming.
Speaker 1:Since we have had a break on this podcast for a while, I can kind of preview some of the podcasts that I have in the can that are going to be coming out over the next few weeks. We're going to be talking about carbohydrate consumption some of the dietary manipulations that you can make in order to potentially improve your race day nutrition performance. We're also going to have many conversations with our coaches about how to implement things like strength training and other points of training design practical elements that you can actually take into your training tomorrow. All of these are queued up over the course of the next few weeks and we're back. We're back on a regular schedule. Expect this podcast to be released weekly from here on out.
Speaker 1:Like I said, I'm really excited about the content that we have banked and that is coming up, and as well as the format where we get to hear from our own CTS coaches to bring to light some of the things that we talk about during our main guest conversation. As always, appreciate the heck out of all you listeners. This podcast is nothing without you. Appreciate those who have reached out to me during the course of this break of the podcast encouraging me to get it back online. It has been a long time coming, but those words of encouragement have meant a lot to me and getting this thing booted back up. But here we are, we're back live and we are not going to stop. So, like I said, we will see you guys next week, appreciate the heck out of each and every one of you and, as always, we'll see you all out on the trails.
