For decades, VO2max and time-to-exhaustion dominated endurance research. But world-leading experts now argue that durability and real-world performance tell a much more complete story.
Video Transcript
[00:09] Fast Talk Labs Intro
Welcome to Fast Talk Laboratories, your source for the science of endurance performance.
[00:18] Trevor Connor
Well, Chris, hard to believe we are at episode 400.
[00:23] Chris Case
That’s right. Amazing.
[00:25] Trevor Connor
Yeah, we made it. And kind of a unique episode because it’s almost midnight for us.
[00:31] Chris Case</strong>
You and I just ate very large pizza, so we’re being like college kids here.
start=”754″ data-end=”779″>[00:37] Trevor Connor
That’s right. But that is because we have some absolutely amazing names on this show, and they are located in Europe, Australia, and we’re here.
[00:48] Chris Case
Yes, yes. So, big thanks to all of you for joining us for the show. I think we’ve got just about every time of day covered.
[00:58] Trevor Connor
Thank you, guys. It’s a real honor to have you guys on the show.
[01:02] Guest
Good to be here. Four hundredth episode. That’s well done. Four hundred of anything is an accomplishment, I think.
[01:08] Trevor Connor
data-end=”1336″ />We appreciate that. So, the format here: we have some questions that we put together. We’re going to hit you with the questions, and then we’re really just going to let the three of you take the questions and run with it.
Dr. Mujika, I’m going to throw this one to you first. This is about the metrics that we use when we’re doing scientific research.
What motivated this: I know a lot of the older research really just kind of looked at, when it did any sort of intervention, do we see improvements in VO₂ max? And often, it would use time to exhaustion as the final metric.
We’ve seen cases where, because those were the two metrics being used, they said, “Well, X didn’t really help.” I think, for example, of weight training, where they said, “Well, we had athletes do weight training and we didn’t see their VO₂ max improve, so weight training doesn’t have a benefit.”
And you look at more recent research, particularly by, for example, Dr. Rønnestad, that showed, well, that’s not where you see the benefits, but there is actually a strong benefit to weight training.
So my question to you is: what do you feel are the best metrics we should be using when we’re doing research on endurance athletes?
[02:21] Dr. Iñigo Mujika
Well, that’s a great question.
I think we have to do some reverse engineering here, and first of all, we need to understand the demands of the competition itself.
One of the ways we’ve moved forward is by getting a better understanding of the requirements of competition and the requirements of performance.
Once you understand what is required from an athlete, you can go backwards and say, “Well, can we measure the physiological determinants, the biochemical determinants, the biomechanical determinants, the nutritional determinants of those qualities or those demands of competition?”
And if we can measure that, let’s measure it.
So if we know what the power requirements are of professional cycling, or more specifically, of climbing Mont Ventoux during the Tour de France, now we can go to the lab and try to measure whether or not an athlete can produce that kind of power for that particular duration.
A better understanding of the demands of competition is going to lead to more adequate measurements in the lab or out of the lab of what an athlete really needs in order to be able to perform.
A couple of days ago, I was at a conference in Sweden, and Andy Jones was speaking about what makes Eliud Kipchoge so good. There was a lot of discussion and talk about the new concept of durability.
Whether or not that’s new, that’s a different point. But until very recently, we thought endurance performance was based on the Joyner model: VO₂ max, your threshold, and your mechanical efficiency.
But you can have very good values of those for the first half hour of a marathon, and then toward the end of the marathon, you are completely destroyed and your efficiency goes down the drain.
So durability is a very important aspect to that model. Now you have to add that fourth component of endurance performance.
In the past few years, there have been quite a few papers looking at the durability of professional cycling, under-23 cycling, and even junior cyclists. I don’t think we have so much information about runners, for example, or about swimmers.
But we have started to understand better what determines and what drives durability: the capacity to produce the same type of powers and maintain your threshold and maintain your VO₂ once you have been working for a while.
Are you able to produce that peak power after four hours in a stage of the Tour as you were at the beginning of the stage, or not?
So understanding the demands of competition is going to drive the things that we can and should measure properly in the lab or in the field.
[05:58] Dr. Stephen Seiler
My grandfather told me he met my grandmother at a dance, and he bought a ticket to go to the dance, and they were in these dance halls.
Well, let me tell you, VO₂ max is a ticket into the dance.
You do need a high VO₂ max. The oxygen cascade is fundamental. The more you can get in, the better.
But I would argue it’s the easiest of those four domains that have been mentioned: VO₂ max, fractional utilization, efficiency, and now this construct of durability or fatigue resistance.
From a time component, what we see time and time again is that teenage athletes are hitting huge numbers for just VO₂ max, but they’re not at their best as performers at that age.
They continue to develop, not because their VO₂ max continues to climb, but because these other components get better. Fractional utilization gets a bit better, efficiency gets better, durability gets better.
So they’re able to use that oxygen more efficiently over time.
I do think that we’ve been lazy as sports scientists because VO₂ max is short and sweet. It’s easy to measure. So it ends up being the go-to measurement for how we evaluate athletes.
That’s part of it, but it’s unfortunate if it takes up too much oxygen — no pun intended.
[07:28] Dr. Iñigo Mujika
If I can add to that, with Peter Leo, we’ve seen that the main difference between professional cyclists and under-23 cyclists is not watts, it’s not peak power, it’s not maximum aerobic power.
It’s whether or not you are able to produce those values after three or four hours of cycling, when you have already produced 2,000 kilojoules of work.
Are you still able to do that?
That was the main difference between the pros and the under-23s. And that only comes with hours and hours and hours of training and years of experience in the field.
[08:09] Dr. Stephen Seiler
Dr. Burke represents an amazing part of this, which is that metabolic aspect of energy availability, carbohydrate and glycogen availability, and so forth.
That has fundamentally changed through training the gut and different things.
Then you have, I think, some issues around the neuromuscular component and how that may be a limiting factor — that the technical proficiency of the athlete deteriorates.
You can use accelerometry, IMUs, and different tools to get at the fact that athletes’ movement — the movement on the bike, the movement in running — gets, let’s say, less efficient and noisier with fatigue.
So we’re starting to unravel what is behind this durability construct. Maybe we’re going to get at how it is separate from the others, to the extent that it is, and then how to train it.
But I think durability is one of those holistic constructs. It will have nutritional elements. It will have mechanical and neuromuscular elements. It will almost undoubtedly have psychological elements.
So it’s kind of putting us right where we belong as sports scientists, and that is: we’ve all got to sit around the same table and work together to understand this correctly, just as we are right now.
[09:40] Trevor Connor
I’m glad you mentioned Dr. Burke. Dr. Burke, I’d love to throw this to you.
What would you like to be measuring in athletes, particularly to see the effectiveness of their nutrition plans?
[09:51] Dr. Louise Burke
Well, the hardest thing about being a dietitian is that you can’t measure what you’re most interested in, and that’s what people are eating.
When you ask someone to record it for you, they’ll change what they normally do, or they’ll under-record or misrecord what they’re doing.
If you ask them to talk about it as a retrospective activity — ask them what they ate yesterday or what they normally eat — again, memory and just the ability to quantify and describe things accurately get in the way of an accurate description.
So it is a frustration.
We’re all looking for this new tool or this new protocol that’s going to help us somehow be in the background and find out what athletes are eating, so that they’re less aware that they’re being watched and more likely to continue their normal patterns.
We need to see it in a way that is meaningful and describes either normative or just important periods of intake.
We’ve been playing around with different kinds of protocols where we can try to be an observer looking at what an athlete is eating, rather than relying on them to tell us.
It’s incredibly time consuming, and the manpower that goes into that is amazing. But maybe if we can find a way of making that digitized or somehow create a little avatar of ourselves that can just follow the athlete around and observe them while we’re not looking, we’ll get some of the information that we so desperately want.
[11:33] Dr. Iñigo Mujika
The Japan Institute of Sport Science has this really clever system that, when the athletes put their tray under a camera, the camera takes an image of the food that’s on the plate. They make a calculation of the total energy intake, the carbohydrate, the protein, the fat, and even the micronutrients.
But then nobody controls whether or not the athlete is actually eating what’s on the plate, or whether they are eating something else beyond what’s on the plate.
So, if you took a picture of Stephen Seiler’s breakfast this morning, yes, you can see that he ate eggs and chocolate, but did he eat something else besides that? And will he tell us?
[12:21] Dr. Stephen Seiler
You’re going to have to qualify, folks who are listening now, that is not my standard breakfast. Just so we’re clear.
I just got back from Bulgaria. I haven’t shopped. I haven’t bought groceries. And so that’s what was in the refrigerator.
Please do not accuse me of being the worst eater on the planet.
[12:40] Dr. Louise Burke
What’s wrong with it, though? Don’t make excuses. It sounds pretty good to me.
[12:45] Dr. Iñigo Mujika
The main question is, did you mix them, or did you have the eggs first and then the chocolate?
[12:50] Dr. Stephen Seiler
Separate. I never mix things. Even from the age of five or six, I always ate each part on the plate separately, and I still stick by that. So don’t mess me up there.
[13:06] Trevor Connor
But, Dr. Burke, I know exactly what you’re talking about.
I’ve had multiple athletes come to me and say, “I’m trying to lose weight. I’m really struggling. Help me figure out what to do with my nutrition.”
And I have them do a three-day diet log. I can’t tell you how many times they — and I always tell them, “I want you to record what you typically eat. Don’t change this because you’re doing a diet log. Eat what you normally eat and record it.”
Then they’ll give me the three-day diet log, and I’ll do an analysis, and they’ll average 800 calories a day. I’ll come back to them and go, “This is not your typical diet.”
And they go, “Yes, it is.”
I go, “If you’re eating 800 calories a day, losing weight is not going to be your problem.”
And they will argue me to death.
[13:49] Dr. Louise Burke
Yes, it is a frustration of my profession, I have to say.
[13:55] Dr. Stephen Seiler
Behavior is hard to measure, and even some of the physiology that we think is really straightforward.
I found with my daughter that when she tested, she just got so engaged that it changed her heart rate. Her heart rate responses were influenced by the feeling of wanting to perform, being on the treadmill, and so forth.
So I realized, yes, even heart rate, which we tend to think takes care of itself once you start exercising, has a layer of autonomic nervous system stimulus that can shift it up or down a bit — particularly up, depending on the setting.
We’re trying to measure breathing, and breathing is both physiology and perception. It’s both behavior and automated. When you think about it, it changes.
So there is this dilemma that Louise is facing. Hers is particularly egregious, but we see some of the same issues: trying to measure things on people who know they’re being measured.
There are always issues around, I guess, the Hawthorne effect or whatever you want to call it — the process of measurement often changes the variables we’re measuring.
[15:17] Trevor Connor
The last part of this question that I want to ask, because all of you touched on this, and I think it’s a really important question.
Dr. Seiler, you mentioned it’s very easy for researchers to measure VO₂ max. And I get it. In a lab, you want to control variables, and that’s a variable you can really control.
But does that, to a degree, disconnect researchers from the real-world setting?
Talk to any coach, and they’re going to say the ultimate metric is whether their athlete is performing in races or not. But that’s not a variable that you can control as well. There are a lot of things that affect races.
Should researchers be a little less purist and say, ultimately, we need to see if the athlete is performing better or not? Or should we continue to use very controllable variables that might not necessarily correlate that well with performance?
[16:11] Dr. Stephen Seiler
I guess it boils down to the fact that our whole history of sports science — what do we do?
We typically work on a semester schedule. We design studies around the realities of student projects, athlete-subject availability, and we have a whole history of eight-week interventions and so forth.
Why? Because that’s what fits into the academic calendar.
Measurement in the lab — doing a two-hour session, for example, like we’ve got a project going on where the athletes are going to be running 21 kilometers, doing a half marathon on the treadmill — that’s not a typical thing to do in a laboratory.
We like to keep it short and sweet. Interval training is super popular to study because it’s short and sweet, intense, and interesting.
So I do think that the whole corpus of knowledge in sports science is somewhat biased by some of these issues.
We’re not very good at longitudinal things because of the semester process. Anything that lasts longer than a semester, we’re probably not going to want to measure it because it’s not going to work. It’s not going to be efficient in our calendar process.
And in the actual measurement in the lab, we try to do things that take about an hour. We don’t want to spend three hours on one subject.
So I’m sorry, but that’s been our weakness. Our whole body of knowledge is biased.
We get better information on these longitudinal processes out with the athletes in the field.
[17:55] Dr. Iñigo Mujika
Trevor, I think your question takes us back to the first question about what has changed over the past couple of decades.
One of the things that has changed a lot is taking the lab to the field instead of taking the athlete to the lab. That also has to do with technology.
A lot of the technologies that we have nowadays, and that were not available when you started your episode number one, allow us to actually take the lab to the field and follow the athlete and measure things in the actual training situation, and even in competition.
Who would have thought a few years ago that football players and basketball players would be carrying time-motion analysis systems during competition, and we could assess basically everything that they are doing from the point of view of the external load, at least during the match?
So one of the things that has changed a lot is bringing the lab into the field.
If you’ve been following Louise’s Supernova studies, you would see a very good example of that. You see athletes in their real training environment. These are called research camps, but they are actually training camps.
Those camps include competition, and they measure a whole bunch of things when the athletes are in the real training and competing environment.
Louise herself can tell you more about this because they are a great example of taking the lab to the field.
[19:44] Dr. Louise Burke
Yeah, thanks. I’ll jump in there because I was going to say the same thing.
One of the things we’ve tried to do is embed research into the daily environment of the athlete for two reasons.
One is to develop the relationship with the athlete and the coach and really see it in a less artificial light.
But the other thing was to have the opportunities to co-design the studies with the athletes, so that when we were doing things, we’re not researching on them — we’re researching with them.
All our camps have been training camps. We call them research-embedded training camps, and we have athletes there pushing each other, developing their relationships themselves, helping each other, and everybody benefits because we know that they all go home from the camp having improved their performance.
But we put a range of different tests into the camp that measure real performance.
We had real-life races in our Supernova study. The World Athletics calendar now has a race in January called Supernova that happens in Canberra regardless of whether we’re running a study or not.
When athletes are doing that race, they’re doing it under real-life conditions. So we hope that the intervention that we’ve planned into the study has a chance of seeing whether it does translate to performance.
As well as that, we do testing in the lab or other testing out in the field where we can measure some of the things that might explain the mechanisms or give us the metrics that tell us what’s important to look at to explain what happened with the race performance.
The ripples of those studies are great because it’s not just that you did a study and got a publication and found an answer to something. You create interest and a culture among the athletes. They want to know more, and they understand this is a good way to find out some of the answers rather than Googling it.
They can be part of the process of finding the answer.
We’re up to Supernova 10 next year, which is remarkable to think about. Some of the same athletes will be turning up.
So we’ve had a wonderful relationship with the race walkers in the Supernova series, and they have continued to want to keep investing in that scientific process.
[22:20] Dr. Iñigo Mujika
I would link that to what Stephen said before about the limitations of doing your research around the semester.
In the past, a lot of the research that was being done was being done on volunteers and physical education students, or as they said in the lab where I did my PhD in France, medical students from Bulgaria.
Nowadays, we are not using volunteers or students. We are using elite athletes to do our research, and that puts a limit to what you can do in terms of research and what you cannot do.
When I work with elite athletes, if I am selfish, I will force them to do things for my research.
Whereas I can, on the other hand, think in a different way and think, “My research will be limited by what they are doing.”
So I cannot make them do what I want for my research because my research is not number one. What’s number one is their performance.
I will limit my research to what they are doing, and I will see then if I can produce an interesting paper out of what I can measure based on what they are actually doing.
My latest publications are about the total hemoglobin mass of elite swimmers and water polo players in a training and competition environment.
Would I like to measure other things if I could? Yes, but I can’t. I am there to follow the athletes in their training environment in preparation for competition.
My research is going to be limited by what they do in training. I’m not going to make them do things that they wouldn’t do and that are not interesting for them to perform better.
So we are nowadays working with elite athletes and doing our research on elite athletes in the real training and competition environment. That is a huge advance in the evolution of sports science.
[24:44] Dr. Stephen Seiler
I think also that teams like Visma in cycling, with a long history, know what they need to know. They are intelligent acquirers of information in their interactions with scientists.
So they are driving the research agenda, and I think that’s fair.
Whether it’s Olympiatoppen in Norway or the national governing body in orienteering in Sweden, they ask the questions and say, “Here’s what we need to know. Can you help us in this process?”
I think that’s kind of where we are now. Iñigo works that way. I work that way.
I started way back a couple of decades ago just saying, “Maybe it would be a good idea to just measure what they actually do and let’s see what highly trained athletes actually do. How do they actually train?”
That was my little dumb idea that turned out to be kind of useful, because there was this self-organizing process. Coaches and athletes were experimenting over time, and there was an aggregation of knowledge that was developing.
Now we’re better as sport scientists at tapping into that, I believe.
If we use cycling, because it’s probably the most technology-friendly, we can get at the external load, the physiology, and the perception. They’re sitting there in a lab. It’s pretty easy.
Even when they’re outdoors, they’re sitting, and we can talk to them. So they are often the vanguard of testing out new ideas, new technologies, and nutritional strategies.
But what they’re saying is, “We don’t need your laboratory. If you want to test us, then come out in our world. Your gold standard for validity is not our gold standard for validity — not anymore.”
They have become quite demanding in terms of saying, “Here’s how we want to be evaluated. If you want to play our game, then you get out here with us.”
Or if they come into the laboratory, they bring their trainer, their bike, their power meters, and they say, “We’ll use our equipment, thank you.”
So that’s the change of the game: the athletes and the teams are in the driver’s seat now. And I think that’s appropriate.
