The Holy Trinity: How to Monitor Training

Dr. Seiler shares his method for monitoring an athlete's training volume and intensity.

Dr. Stephen Seiler presented at the ITU World Triathlon Edmonton 2020 Science and Triathlon Virtual Conference: Planning for 2021 and Beyond.

In this video, Dr. Seiler shares his method for monitoring an athlete’s training volume and intensity.

Video Transcript

Intro  00:00

Dr. Seiler, welcome, and thank you so much for being here and talking to us today.

Dr. Stephen Seiler  00:06

Well, thank you, Joe. That was completely embarrassing. I have to say, I did not ask him to say all that stuff.

Dr. Stephen Seiler  00:15

So just scratch it out of your head, and let’s get to work here. I will say this, yeah, I’m from Texas, you can hear the accent, it’s not very Norwegian, but I’ve lived in Norway so long, and I’ve been working with Norwegian Sport quite a bit, so I’ve kind of become Norwegian patriotic. So, here’s what I’m going to do to show that, I’m going to just put a couple of people, whoops, what happened here. I’m going to do that, and then I’m going to take them back away, just to show that I actually that Norway has actually become a bit of a triathlon nation, 10 years ago, triathlon almost didn’t exist here. We skied, rode, ran, and cycled, but we didn’t do triathlon, but things have changed. And so that’s been exciting to see. I’m excited also, because I get to speak together with John, John’s a guy that I have followed a bit myself, and I think you’re gonna find that our two talks are complimentary, because we go at it, I think we’re interested in some of the same issues, but we pursue them from a little bit different places, and I think that’s a good way to go. So, let’s start here, if you’re a journalist, you do a lot of you talk about, you know, we need to know the why, and the what and the where, and the how, and so forth.

Why Do We Monitor Our Training Process?

Dr. Stephen Seiler  01:36

So why do we monitor? Why do we need to, you know, try to talk about and decide on some methodologies for monitoring the training process? Well, one is, for me, it’s about execution, do the athletes actually execute what we prescribe? And the answer often is the prescription and execution are not aligned, if we can solve that problem, then already, we are making headway, because if as a coach, if I’m prescribing something, and I’m assuming that it’s being executed as prescribed, but it’s not, then that is an immediate cause for concern, and it will almost certainly lead to some problems down the road. Number two, we wanted to take deviation in it, and you might say deterioration, we want to hopefully detect it early. Now, in my head, after a lot of years, I kind of think of the fatigue process in the deterioration process at three levels, there’s muscular fatigue, but the muscle is the working muscle, if it’s well trained is remarkably adaptive, and it recovers quite quickly. Then you have the autonomic nervous system, which is not going to experience the same ebb and flow of fatigue, but if it first becomes fatigued, then you definitely will, that will have an impact on training and performance. Way down the road, if you really push an athlete too far, we can actually see what we might call an endocrine exhaustion, which is more related to some very big problems of non-functional overreaching, or even overtraining. But these, particularly muscular fatigue, and autonomic nervous system fatigue, these are things we deal with from day-to-day, week-to-week, and we need to kind of have a feeling for how they’re how they’re working in our athletes. Now, with knowing these things and knowing prescription execution, then we can individualize and revise training prescription, and this is where John I think is gonna really come in and talk about you know, how far in advance can we plan the periodisation process, and the importance of being flexible in in adaptive in the planning and periodisation process? And then I want to know, I want to quantify development, I want to I want to develop best practice, knowledge in my organization, which whether it’s me and one athlete or the Norwegian Olympic Federation, we need to have institutional knowledge and documentation of our training process that helps us to reduce errors over time and improve success. So those are the reasons that I think this whole monitoring discussion is very important.

Marit Bjørgen: Comeback Story and Why Monitoring Training Is Important

Dr. Stephen Seiler  04:25

Now, this is a cautionary tale. I think this is one of the best-case studies ever, ever published. I’m not involved in it, so that’s just my objective opinion, but it is from Norway. The woman involved is a named Marit Bjørgen, she’s the all-time winter Olympian, male or female with eight Olympic golds, 18 World Championship Gold, and 114 World Cup winning. She has a tremendous legacy in cross country skiing, and what’s Important is, is that that legacy was very close to never happening, and ending very prematurely, this paper is primarily about her five most successful seasons, and you see those from 2010 to 2014-2015, she then had a child and then had come back for one more season. What’s interesting, and I think, particularly here, besides the remarkable success, and kind of a blueprint for how it was achieved, is that she almost quit the sport before that best five-year period ever happened, and this was a picture of her during this period of, you know, this desperation where she was trying to understand what is happening?  She became world champion in 2005, at a very young age, and then the successive three years after that, she basically did the same thing, the same training that made her a world champion, but she deteriorated, her performances went steadily down, and what you’re seeing here is the number of podium medals, World Cup or World Championship, and basically, by the time she hit here, she didn’t win anything, and she was ready to just say, “well, maybe I retire.” No, we think there’s some issues with your training with some, you know, other issues that we need to go back to basics and resolve, but your talent is still is still there. What you should see is with the helicopter view, there’s not a huge difference between what ultimately here was an athlete in total decline, and here an athlete that was absolutely dominant. But there were some subtle differences in the loads that she was putting upon herself, particularly the high intensity loads that when they were adjusted, she came into a kind of a balanced state, and then won and won and won and won. So, this is a cautionary tale that we need to have good data to detect these nuances, because it’s not it’s not like the athlete goes from black to white or, you know, it’s always just so clear what is wrong in a training process, what is leading to an imbalance. So, we need good information to make these observations and help the athlete when it does go wrong. Fortunately, here this athlete was helped by her support people and ultimately had a tremendous or you might say, Renaissance or recovery.

What and When Are We Measuring?

Dr. Stephen Seiler  07:48

Now, so what are we going to what do we measure? Well, what I want to measure are I want to measure loads applied, and we get a bore, there’s a lot of discussion, what’s load? What stress? You know, you get all these terms training stress, training load, what’s the difference? And so I’m going to kind of give you my definitions, but I want to measure loads applied, and then I want to measure the resulting stress responses and the adaptations, because those are two sides of the sword here, the stress and the adaptations we have to live with that they’re both happening, and we’re trying to balance them as best as possible. Now, when do we need to measure? When do we need to test? You know? Well, I would say often enough, that the process kind of merges into a process or the measurements merge into a process or a kind of a video we, if you don’t measure often enough, you don’t really see the continuity, what is the connection? If you may have your too often, then you start to irritate the athlete and disturb their training process. So, we have to, you know, some things we’re doing daily, some things we may be doing weekly, and other things we don’t need to do very often in terms of testing. And then the how, here’s this is a huge area of discussion, obviously, are the tools that are available to us with technology and so forth, what do we measure? How do we measure it? I guess I’m old school, but I still believe I look at technologies all the time, but I still believe that we use the simplest tools available that consistently inform the process and don’t confuse us. So that’s my you know, keep it as simple as possible while maximizing what you might call the information versus confusion ratio, because if you measure enough stuff, you can measure hundreds of variables and just confuse the heck out of yourself and your athlete, and that doesn’t help anybody. So simple measurements done well, I think are always superior over the long-term, then measuring lots of different things with uncertain reliability and repeatability.

Training load

Dr. Stephen Seiler  10:01

Now, training loads, that’s what we control. We prescribe as coaches, we execute as athletes, these loads, you know, and it’s in terms of intensity, duration, modality, this is what we do.


Dr. Stephen Seiler  10:18

It’s our action, but then the adaptations that occur, those are the results that we achieve, and we have to maintain them and integrate them into our performance into our execution.

Stress Responses

Dr. Stephen Seiler  10:31

And, and then along for the ride, we have stress responses, these are reactions that we have to manage and mitigate, we use this word mitigate a lot these days because of COVID-19, but it’s relevant here too, because the stress responses are going to happen. Our goal is not to eliminate stress, because without the stress, we don’t get the adaptation, but we have to manage it. So that the the ratio or the relationship between the adaptive responses and the fatigue and stress that we’re imposing on our athlete or on ourselves as an athlete, are tolerable and sustainable over time. So that’s, that’s what I’m always trying to achieve in my head is how do we do a better job of that?

Three Aerobic Training Zones

Dr. Stephen Seiler  11:19

Now, obviously, if we’re going to measure training, we need to have some kind of a framework and intensity zones we talk a lot about, again, simple is better than complicated. For me as a physiologist, as many of you, if you’ve seen any of the stuff I’ve done, you’ll know that I tend to use three zones, and that’s because in our physiological testing framework, this is what we’re able to define, we’re able to identify reasonably well, a couple of so called turn points or thresholds, often called the first and second lactate turn points, they can also be measured with ventilatory responses, we’re able to define a maximum aerobic capacity, in the form of VO2 Max and maximum heart rate. So those give us an anchor points for a three aerobic training zone model. And then obviously, sometimes we may do some intensity that’s higher than 100% of VO2 max, but for the triathlete, it’s not going to be too often that we’re doing that. Now, this three-zone model is a reasonable starting point, I think, for a lot of athletes, it’s still that’s all you really need is three zones, to be perfectly honest. But, you know, we’ll talk about how we can get more detail. Now, we achieve these three zones with different in the lab, we do lactate profiles, and then we, you know, we’ll take them up to max after a bit of a rest, and this is a female athlete, happens to be my daughter from probably almost a year ago, because we haven’t been able to do much testing in the lab recently. But we’re able to identify breakpoints, that help us to distinguish these clearly below the lactate threshold, in that lactate threshold region, and then clearly above the lactate threshold where it is a quite, you know, you’re counting minutes until exhaustion. Now, this is what it looks like in the lab, you can do all your physiology and find these break points. But most of us don’t have access to all of this, so we’re often thinking about how can I give my athlete reasonable information if they don’t have lab access? One thing I want to remind you about is that heart rate, obviously is one of hour max, one of our calibration tools, particularly the maximum heart rate. The data you’re looking at is just to show that this is data, we’ve from about 157 cyclists we’ve tested with the same lab, same protocol, and what you’re seeing is on the y-axis is the actual measured maximum heart rate that they achieved during the cycling test to exhaustion, and on the x-axis is their age. Now if you 220 minus age as this line of identity, this is what it looks like. Well, that’s what you know, if you were just going to estimate their heart rate based on their age, here’s reality, and this is just a reminder that the reality is there’s a lot of variation, maximum heart rate in any group of athletes that you work with. So, if we’re going to use heart rate, then you need to have a reasonable estimation a true actual measurement of maximum heart rate, because if you use these estimation equations, it’ll work for a fair amount of people reasonably well, but for a big number of your athletes, it can be so wrong, that it just completely confuses the process. And to add a bit of complexity in the triathlon, you’re basically talking about three different maximum heart rates, this is old data, it’s 30 years old now, but it’s still about, you know, what we would say is that you can see a 20-beat spread in maximum or peak heart rates that are modality specific. So, if you’re going to use heart rate, then clearly, you’re not going to use this heart rate when you’re trying to manage and monitor the swimming part, or even the cycling part, so if you’re gonna use heart rate, then try to be specific in terms of the peak values that you’re using as your, your calibration points for your different modalities.

Dr. Stephen Seiler  15:43

Now, this is data that we published on well-trained runners, orienteers, some of them world class, they were asked to do four different workouts, it gives you just a good framework for what are the physiological responses and the perceptual responses to these different intensity areas, and in well trained athletes, there’s very, you see a great deal of stability, if they do a 60-minute run, or 120-minute run, which is what these were, they are, there’s not a lot of drift upward, there’s no, you know, they, they told me, I can remember from the study, they said, “Look, after two hour run, I feel better than when I started.” So, when they’re in low intensity mode, when they’re doing zone one, there is zone one, and it is clearly a very manageable intensity for them, it is talking pace, it is relaxed, but they’re doing the work. Threshold is a clear difference, and then of course, the high intensity, but the difference between threshold in high intensity is not very big compared to the difference between threshold and the low intensity longer duration work. This is this is typical values for RPE, and then the so-called session RPE, on the 10-point scale, you can see, in aid on that scale, you’ve worked very hard, and you really feel it 30 minutes after the session is over. Now, you can have more than three zones and why would you? Well, if it improves your communication with your athlete, and I think in many cases that it can, and it does if used correctly. So, for example, even in Norway, we have a five-zone system that is used kind of, it’s imposed or integrated at a national level, and it’s across the different sports disciplines. So, it gives us a common language when describing, you know, if we say zone two and row in zone two in cycling, zone two in swimming, then in theory, we’re all talking about the same intensity level, relatively speaking. So that can be useful, but it’s just worth noting that, again, it’s based on the same anchor points physiologically, and then what we’re doing is essentially just making some fuzzy lines drawing some lines in the sand, that give us these additional zones. So that green zone gets kind of shaded light and dark green, and that red zone becomes orange and darker red, and that can have some utility, at the individual level in particular, because of the way athletes tolerate these, this spectrum of intensity over time. So, there’s nothing wrong with that, but don’t make it more complicated than it needs to be. Again, always seek the maximum degree of simplicity, I guess you could say, to help communication.

What if You Don’t Have Access to a Lab?

Dr. Stephen Seiler  18:49

Now, if you don’t have access to a lab, there’s questions about well, what do I do then? And there have been studies have shown that, for example, the Talk Test works, particularly in distinguishing I would say here, these two and I think that’s really important that if I’m prescribing low intensity training for my daughter, and I wanted to stay below her first lactate turn point due to 90-minutes, then it’s really important to me as the coach that she is executing that as intended. One way as I look at heart rate stability, I should not see a situation where the athlete is not dehydrated, not dealing with a big heat stress, they should stabilize in heart rate after about 15 minutes and from 15 to say, an hour or 80 minutes or whatever in a run, or from 15 minutes to two hours, three hours in a ride. That heart rate should not just keep drifting up, it should stay pretty darn flat across that duration, if they’re doing their maintenance in terms of hydration, and so forth, and they’re well ventilated. Same way with lactate, lactate, you know, we, if they pass the Talk Test, and they’re hydrating, then lactate is quite stable, versus if you’re seeing this drift, and if you’re seeing lactate climb up, this, you know, this is what this is lactate threshold, and if they’re starting to struggle to do the Talk Test, it’s a good indicator that they’re, they’re creeping into a threshold intensity. This is a typical, a typical training error, this prescription is green, the execution is yellow, and if you do that enough, as an athlete, then you are going to have problems because pretty soon the red prescription is also going to be executed as yellow, and we get this kind of regression towards the mean, and that is a wonderful prescription for overreaching and stagnation. Now this, I put this picture here, there’s some of argue that if you’re really in the green zone, you should be able to run with your mouth closed and just use nasal breathing. It looks like that may be true, but I definitely want to have a really clear sinuses if I’m going to do that, I have done it, it does work, but only if my sinuses are very clear.

How To Quantify a Training Session

Dr. Stephen Seiler  21:18

Now, here’s this is a training intensity distribution of a World Champion, or an Ironman, you know, 12 times Ironman Champion, and when you use time in zone, then you at this level, you’re seeing very small contributions in terms of percent of total volume in these higher zones. Now, why do I say that? Well, I think the point here for me is that because these are small, then I want to be really good at making sure I am consistent in how we measure it, because it doesn’t take very much difference in the way you measure it to actually double that number, and then we’re not sure what we’re comparing. So, I want to talk about that a little bit. Now, if let’s take this workout example, this is 5X8 minutes with two- minute recoveries, this is an elite level cross country skier. Meaning they often have a very high slow twitch competition, not a very high peak lactate, so when their blood lactates are four millimolar, they’ll say, “my legs are on fire.” So, you have to remember the calibration, but these are this, this athletes working hard, but then the question is, how do I quantify this session? Because there’s different ways to think about doing it, we’ve published some work on this, and we said basically, you’ve got three choices. You can go time and zone based on your heart rate monitor, where you just plug in your cut off points and Garmin or polar flow or whatever calculates time in zone, now this is going to underreport your true high intensity time, because of lag times per heart rate, that’s an issue, we can fix that, or we can at least correct for it using so called modified time, so where we basically square the curves and say, “well, it was five times eight minutes, that’s the prescription, we know they’re working, so it’s 40 minutes of high intensity work finished.” That’s pretty simple, but some would argue that doesn’t tell the whole story either. The third way that I have promoted or used in a lot of research now for 20 years, is this session goal where we basically say, well, look, the body’s not counting minutes in terms of measuring stress and all this stuff, the body is this responding to an overall stimuli. We’re either activating a big stress response, sympathetic load, you know, a lot of high blood lactate or so forth, or we’re not. So, we can basically put the different training sessions in the boxes, was this training session a high intensity session? Was it a threshold session? Was it a low intensity session in its entirety? And then we’re using the highest load or the highest intensity part of that session, as long as it’s a certain number of minutes to say that’s what is defining that session, so that’s a categorical approach. In the 80/20 distribution, that I have published, and we’ve talked about for quite a few years now is is based on session goal,  just so that’s clear, it’s based on saying look about eight out of every ten sessions will tend to be below the first lactate turning point, two out of ten will be above, and then of course how that two out of 10 is distributed can vary depending on competition, distance, and so forth, that’s been what we’ve used as the measurement stick is session goal categorical. if you use time in zone with elite performers and measure the time, they spend in these three zones that I’ve described, then were talking, it often be more like 90% in that low intensity zone, or even higher than that, as you saw with the 12-time Ironman champion. So just to keep us clear on how we’re measuring these issues.

Dr. Stephen Seiler  25:35

Now, here’s another example. You know, this is a six times four minutes, two-minute recovery, this is a typical situation in that interval session. It’s not their heart rate is coming up to the same value each interval, there’s a heart rate drift during the interval session, particularly if they’re running to pace. So if you’re saying, I want you to add this wattage, or this pace, six times four minutes, then the first bout will obviously be, it’ll be the same external load, but it’ll be a very different internal load as the as the session progresses. So, this creates some issues that you need to be consistent about in terms of, okay, how am I going to quantify this? And how am I looking at this in terms of the overall response, and it may be that during certain parts of the year you’re going on feel when you prescribe this session, and then on other parts of the year, you’re very rigid on pace, and then you’re letting heart rate in the in the internal load drift upward. So, there’s different ways of prescribing and you just need to be clear with your athlete on what you’re expecting, is this a feel based or a pace-based prescription, and you’ll get somewhat different responses.

Training Monitoring Trinity

Dr. Stephen Seiler  27:00

Now, here’s the title of this talk was this idea of an endurance training monitoring Trinity. I grew up in the South of the United States, you know, number one, the United States is supposed to be based on a government of checks and balances with the three different branches of government, but also that there was this Trinity, you know, we learned in the church from the, from the preacher, so I guess that carried over here. But there’s also a Trinity and training monitoring, and the Trinity is that we look, we can measure external load, we’ve never been able to do it better than we can now with our good GPS systems, our power monitors, and so forth, so we can accurately measure power, pace is a little bit more problematic when running because of undulations in terrain, and so forth, but even that, you know, we’re getting pretty good at that, and then we can use key sessions under various controlled conditions and get a very good idea of what that external load is. And then we can measure physiology, the tools that are most readily available to us are heart rate, and, to a lesser degree, blood lactate, we can measure other stuff at nowadays, and still, you know, I don’t know how much yet those other measurements are informing the process, but it can be heart rate variability can be muscle oxygenation, it can be VO2, and so forth. So, we have some tools that are more and more moving out of the laboratory into the field. But we just have to be very clear on what we use, which of those tools we use, how we use them, so that we don’t confuse when we want to improve. And then finally, and, and very importantly, we’ve got brains, and those brains of ours are amazing integrators of a lot of information, a lot of feedback coming from the word of the body, that gives us the ability to perceive effort and exertion, to perceive fatigue, perceive how much longer we can hold this intensity, and so forth. So, we need to use that we need to use perception, either using metrics like Borg scale, or is nothing wrong with just qualitative, how do you feel? How did this feel? Those are important questions. And that data is important in the monitoring process. So, when you put those three together, you’ve got this Trinity, and you have this checks and balances system, because each of these has weaknesses. There are situations where they will tend to under or overestimate what you’re looking for, so when you put them together, they correct each other, and that’s why I see them as a really important Trinity. And you put them together and it helps us to get at this, how is this relationship changing from during the workout but also from day-to- day, week-to-week? Are we seeing a shift that tells us that this body is failing to adapt to respond appropriately to the loads that we’re imposing?

Dr. Stephen Seiler  30:05

Now, here’s where things get interesting, because we have to distinguish between some short-term stress responses, and long-term adaptation with these checks and balances. This is where our skills, our subtleties, as coaches and scientist comes into play, we got this training load, it’s going to induce adaptation, it’s going to induce stress responses, sometimes those look different, they look the same, but they’re going in different directions. We know that muscular fatigue is an issue, we know that the autonomic nervous system is, is responsive to the loads, and we know that ultimately, we can also start to see endocrine imbalances, meaning the hormone responses to the training can become first higher, but then blunted. So, here’s an example. Take the typical right shift in blood lactate that we expect and heart rate, we typically will say, look, if you’re in better form better shape, you will have lower lactate and lower heart rate at the same external load, power, or pace, and that’s positive over time, year on year, that’s what we want to see in a young athlete that’s developing is their threshold power is getting higher, at the same heart rate, at the same level of exertion, at the same blood lactate. Everybody knows this right shift, but if we look at the short-term, for example, where we do, as in this case, a three week loading period, where we’re acutely increasing the training load, we might call this a super compensation period where we’re trying, we’re going to push the athlete hard in then hopefully, when we ease up on the throttle, we’ll get a rebound, and in this kind of supercompensation response, this would be an example of what we would call functional overreaching. Well, here, what do you see? You see that at low intensity, at lactate threshold, and high intensity, even in exhaustion, we see the same basic pattern, this athlete has lower heart rate into an extent and lower blood lactate at the same intensity. So it looks like a training adaptation, but actually, what we’re seeing is here’s an athlete that’s fatigued, and their sympathetic nervous system is not responding, they are, you might say parasympathetically, hyperactive, and that sympathetic system that really drives heart rate up, drives glycolysis, drives lactate production at very high intensity, it is, it is you might say the brakes are on, and that athlete is fatigued, and they are not going to be able to perform at high intensity, they are compromised. But if you only look at heart rate and isolation relative to load, it looks like this is positive, and they may be pretty good at low intensity, but they don’t have they don’t have that fifth gear, this so this is the kind of subtlety that we have to be able to be sensitive to otherwise, we will miss interpret the information that we’re getting from the monitoring process, and we may drive the athlete farther down the wrong road by prescribing more heavy loading.

Dr. Stephen Seiler  33:39

Here’s an example, this is me actually, just recently I did this I developed some software with a with a colleague from the from Great Britain, and I calibrate my heart or the athlete’s cardiac response by using heart rate reserve, percent of heart rate reserve, and I’ll show you that in a minute. And then I calibrate the power output as a percentage of six-minute power, and the reason is that seems to work pretty well as a surrogate for 100% of maximum aerobic power, it’s kind of a power equilibration with the VO2 max. So, I look at this relationship and it typically in athletes, these will be pretty much a one to one relationship over a fairly large continuum of the intensity scale, but what we’re seeing here is, this is a Ramp Test, where I just slowly stood I sat on the bike, doing nothing to get my bike resting heart rate and then started pedaling at 60 watts, and then 80, and then 100, 120, 140, 160, 180, and then eased up to 10 watts per minute increases, and then I’m looking, I’m interested in saying is my house my heart rate keeping up? Okay, so this is heart rate in the colored values, and this line is power. Initially heart rate is higher, but then heart rate it flattens out, this is probably due to some stroke volume increases, and now I’ve got this very nice one-to-one relationship in this fresh state before a race. Now, I race a hard race, two hours, a lot of you know, for me, it was very exhausting, I’m 55 years old, and this is 32 hours post-race. So, this is an acute, now I do the same basic ramp protocol, I’m kind of experimented with this. But now what we see is that, again, this is power, and this is heart rate. Heart rate is now not keeping up, in other words, the parasympathetic is okay, but when now when my body needs to start turning up, and keeping up with the demand, it’s as if there’s a transient or an acute sympathetic depression or the brakes being on, and so I’m not going to be able to perform well at high intensities one day after this race. But at low intensities, I feel I feel pretty good, if that makes sense to you. And so we’re, I were experimenting with this, I don’t know that this is the best way to do things, but it does show that transiently, we can see these changes in the heart rate to pace or power relationship that initially look like a positive, but that’s actually a negative, it’s an indication of fatigue. Now, here’s one day later. Now I’ve gone basically two days after that race, and now you see that it’s back to normal, that relationship or that response is back to normal. So then, so it looks like I can detect that acute fatigue, in the sympathetic parasympathetic response, just an example of if we can, you know, with a little bit of nuance, we can distinguish an acute fatigue from a long-term adaptation.

Basic Model for Endurance Adaptation

Dr. Stephen Seiler  37:22

Now, here is the basic model for endurance adaptation, the things we measure in the laboratory, we look for an increase in VO2 Max, we look for an increase in so called fractional utilization, that’s that threshold, but there’s, you know, a dear child has many names, and it can be confusing. We have lactate threshold, ventilatory threshold, maximum lactate steady state, functional threshold power, but all of them are different ways of trying to get at what we call fractional utilization. What percentage of that VO2 max can we maintain over many, many minutes? Let’s just put it that way. And then we have efficiency, which connects the cost, the oxygen cost to the actual output, the external production. Then we throw in a little bit of anaerobic capacity, and that’s the basic model for endurance performance that comes out of the laboratory out of 50-60-70 years of measuring highly trained people, it’s has served us well, but it doesn’t capture all of the changes that we would like it to end, it doesn’t capture a lot of things that happen as the athlete matures.

Problems with the Monitoring Process

Dr. Stephen Seiler  38:43

So here are two big problems with that standard model as I see it. So, you have to accept that this is my perspective. One is that this model fails to capture important adaptations that occur over time, meaning that what we see with elite performers is they, if they’ve been in the game very long, their VO2 max stabilizes, it peaks at a fairly young age, and their threshold powers, their FTP, 20 minute FTP, whatever you might be you’re measuring, those stabilize pretty early in the career of your triathlete or your cyclist, or your runner, but they keep getting better their times get better in these longer events. So what are we missing in that testing? The other is that we tend to when we bring people in the lab, we warm them up for 15 minutes, we do the Step Test, or we test the max, and we find power and pace at these different thresholds, and we kind of assume that those represent static, unchanging resources. But that’s not true, you are not the same athlete, you do not have the same threshold power four hours into a cycling race or to, you know, six hours into the triathlon, that you had it 30 minutes in, then you are fatiguing, you are deteriorating, hopefully less than the other athletes that you’re racing against, but that is part of the war you’re in, is that there, you’re losing you’re fatiguing underway. We’re not capturing that and the changes in the rate of decline, the improvements in the athlete’s ability to sustain over longer durations, we’re not capturing that with the typical lab tests that we do, because those are always fresh, you know, we’re fresh rested, and we get these values. So, these are issues that I think are important when we think about our monitoring process.

Dr. Stephen Seiler  40:53

So what I tend to I recently have called this as low intensity durability is something we’re trying to improve, we want our athlete to be able to maintain sub-threshold pace or power longer, without seeing this decoupling, this shift where the internal workload is starting to increase relative to the external workload, because obviously, that is a that is a situation that won’t be sustainable. And then, in a lot of race situation, in situations in endurance sports, it’s about high intensity repeatability, that there will be repeated bounce climbs in a loop course, where every time the athlete hits that climb, they’ve got to produce big power outputs, and eventually the, you know, it’s a war of attrition, and those who cannot continue to repeat, those high intensity bouts will get dropped. So, this ability to do repeated high intensity bounce is important. It’s an adaptation, that happens, that’s not necessarily captured with a one-off testing of fresh athletes. So, these are things that I’m trying to, you know, get a handle on, and how do we improve at that, this started for me when I got back into cycling, and I noticed that my ability to do these long green zone rides was improving. So, this is an example of, you know, here’s December 18, here’s heart rate response at 205 watts, I’m going pretty good for 90- minutes nice and flat, and then just kind of all of a sudden heart rate just starts drifting up. Drinking well, ventilated with, you know, big fans, but my body is now deteriorating, and then six months later, same exact situation, but now there’s less drift. So, this is a typical example, that’s not going to be captured in a typical lab test, but obviously, my durability was improving in these long, low intensity training sessions.

Dr. Stephen Seiler  42:56

So this, I’ve tried to say, well, how do I calibrate and measure that better? And this brings us back to that heart rate reserve, you need to know your heart rate Max, you need to know your resting heart rate, and then you get the actual, what’s to say, the number of beats that you have available, that is your range, because you don’t go below your resting heart rate, you don’t go above max, so this is what I have to work with, and that’s a good calibration that I can use.

High Intensity Repeatability

Dr. Stephen Seiler  43:24

Now, here’s some data. This is from a group of people that I asked if I could get flat marathon performances. So, if they did, Rotterdam, Berlin, London, Chicago, I believe, they submitted their race files with the GPS data and the heart rate data. So, what you’re seeing here is their percentage of max heart rate, they also told me, they’re resting in their maximum heart rates. So, I’ve calibrated this as a percentage of max heart rate for all of these athletes, and what you see here is that there is a period where they’re very stable, on average, and then about on average, about 60% of the way into the marathon, you start to see the decoupling, you start to see a drift upward in heart rate relative to pace. Now, if we look at the percentage of the pace, I’ve calibrated it relative to their self-provided lactate threshold pace, and what you see there is they are very stable through most of the race, but on average, there tends to be a bit of a decline towards the end. Well, when you put these together, you end up with a kind of a three-phase situation, and two of those phases almost always happen, and the third happens with a lot of athletes or a lot of runners. One is this phase where everything’s in line, we’re feeling good, we’re you know, the pace and the internal workload are matching, it’s usually just below lactate threshold, the first turning point, then you hit this phase where you’re starting to get decoupling, but the athlete is able to maintain pace, but it’s costing more, it’s feeling more strenuous. And then for a lot of runners, they hit this wall where the internal workload is still climbing, but they’re, they’re no longer able to maintain the desired or planned pace. So that that kind of by definition, would be that idea of hitting the wall in the marathon, this is a classic situation of the coupling.

Dr. Stephen Seiler  45:37

Now, here’s a situation, this is me two hours, 200 watts on a bike indoors, very good control, well ventilated, drinking, and, again, I am measuring the relationship between percentage of heart rate reserve, and percentage of six-minute power as two calibrations for external workload and internal workload, and it is just about spot on one to one, and it’s stable. So, there’s some fluctuations here a little bit, but on average, these are the power outputs every 15 minutes, this is about 50% of my six minute power, and you see that that ratio is very close to one, and it’s not changing. So that’s good, that’s what I want to see in that kind of a workout.

Internal External Stress

Dr. Stephen Seiler  46:27

Now, here’s a longer workout at a slightly higher power, four hours at 220 watts, begins the same way. Nice, one-to-one relationship between external and internal workload. But then things start to go sideways in the sense that now the external workload is increasing, the power is staying the same, but this is costing me more and more, and I can assure you that after four hours, I want off the bike. Even though this is not a very high percentage of my maximum heart rate, there is a big shift in that relative cost or relative workload, so I, I use the term IXS, or internal external stress, or an index of that, and you see that shift upward. This is probably not very many few, just a few watts under my first lactate turn point. So, you might say that starts out feeling green, but actually ends up feeling pretty darn thresholdish for me, and from a standpoint of fatigue, this is a high stress workout, it started, you know, if I’d only gone two hours, it wouldn’t have been but four hours, it was even though the the power output didn’t change. So, if you think about this, I tried to make this drawing actually drew this while flying across Canada about a year or so ago, if you think of this as the adaptive signal that results from a low intensity session, and this is the stress response. Let’s say that my typical long low intensity session over the past six weeks, it’s been two hours. So, this is very manageable, and as you saw, I don’t see any decoupling. So, you might say this is kind of a maintenance in terms of adaptive signal, a two-hour ride at this intensity will maintain my durability and my fitness, but it will improve it more. If I want to extend then I’m going to have to extend the duration, and I can do that, but there is going to be a cost, and for me, maybe a three-hour ride will give me a nice relationship between the positive effects, fairly low stress response. But if I go to four hours, then I’m turning that low intensity session into a very high stress workout. So, this is I’m kind of giving you a conceptualization of the fact that the duration, the first hour, the second hour, they’re not the same, the third hour, is not the same and some of the measurements of the metrics we use assume they are, and we need to really think about that in terms of how we interpret these different metrics. The fourth hour at that low intensity, for me is much tougher, much more stressful, and so forth compared to that second hour. But that’s not necessarily reflected in the metrics that we currently use. So, something to think about in your conceptualization of what you’re prescribing and how they’re responding.

Dr. Stephen Seiler  49:39

Now, here’s a this is a third last example, I’ll show you from my old body. This is a two-hour, kind of a war of attrition race where every lap there’s a little 200-meter hill, and you’re charging up the hill and pushing some these for me pretty big watts, you know, five 600 watts, and you do that enough times and it kind of wears you out. And so, there is a clear decoupling in the whole race, the whole race is performed at a state where the heart rate response or the internal workload is much higher than the average power that’s being produced, because of these fluctuations. So again, we have to really be careful about how we interpret the metrics, because at least in my case, this, the actual fatigue I feel here is not necessarily reflected by the metrics that are provided in typical training tools. So, I’m going to show you that and then now here’s what it looks like when somebody that’s really good races, in these very stochastic races, this is a top probably 50-60 level, international terrain mountain bike cyclists, this is a National Championship event from the Czech Republic. This is heart rate, as a percentage of max, it’s about 95% of max heart rate, on average, for the entire 98-minute race. This is power output, and it ranging from 1000 watts to zero, and just undulating back and forth throughout the course of this race. Each color represents a lap. And so, you see here, this athlete is averaging 95%, their average power is only 60% of six-minute maximum power, but when you do when you average it in this way with these undulations, there is a tremendous decoupling that is created.

Flexibility in Understanding Intensity Zones

Dr. Stephen Seiler  51:47

So once again, you know, for example, the how you use and interpret normalized power average power, and that is something you need to be consistent with. But this gives us some clue as to the actual stress that’s been imposed by this kind of about. So what I want you to kind of take home with you is this idea of intensity zones, we need to be a bit more flexible in our understanding of them in turn, because that line that we draw from the Fresh Lab Test is actually a movable line, it doesn’t necessarily move that way very often during the acute situation, but it definitely can move this way, in the sense that we deteriorate our athletes functional capacity is actually deteriorating due to glycogen depletion, due to damage in the muscle fibers, due to you know, many different factors, so you can almost say that there’s two intensity zones that are duration sensitive, you’ve got a low intensity zone where the stress responses are low, and you’ve got a kind of a moving target, where you’re inducing these big stress responses. This is something you have to manage and take into account when you prescribe even long, low intensity sessions, and there are implications if we understand is that there are implications for how we interpret some of the training metrics that are used, like trance, like session load from Paul Foster, like the training stress score, which it has an intensity factor, but it assumes the same linear relationship for duration on the score, which is clearly not true. So, there’s, you know, just so that we are careful if you use these metrics, don’t be a slave to them, because any of these kinds of indexes will be wrong, but it’s just an issue of when it’s wrong, how it’s wrong and how you interpret it. So, I’ll leave you there with that and we’ll take a break.