The Biggest Sport Science Breakthroughs: Seiler, Mujika, and Burke Explain

[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
You and I just ate very large pizza, so we’re being like college kids here.

[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] Dr. Stephen Seiler
Can I talk now? When do we get—

[01:04] Trevor Connor
Absolutely. Absolutely.

[01:06] Dr. Stephen Seiler
Oh, you’re asking a question to say something. I can’t believe it.

[01:12] Chris Case
Well, you act like you’ve never done this before.

[01:16] Dr. Stephen Seiler
No, good. Good to be here. Four hundredth episode. That’s well done. Four hundred of anything is an accomplishment, I think.

[01:24] Guest/Host
Anything legal.

[01:26] Trevor Connor
Well, we appreciate that.

This is actually, strangely, probably going to be the easiest episode ever for Chris and myself because we have—

[01:35] Chris Case
Don’t jinx us. Don’t jinx us.

[01:36] Trevor Connor
Yeah, fair enough.

But we have three people like you — top names in the exercise science field. As I said, it’s not for Chris and I to be talking.

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.

I’m going to start with the first question. Dr. Seiler, I’m going to throw this to you.

What have been the biggest developments or changes in endurance exercise science of the last 25 years? And just as importantly, are they good changes?

[02:17] Dr. Stephen Seiler
It starts for me with the development of the internet. That coincided with my move to Norway.

I can still remember 1993. I’m a PhD student, and there’s one computer in the huge University of Texas library where we can get on something called the internet. I began to pursue it a little bit.

What has the internet done? If we go straight to the hardcore deal, it’s enabled training diaries. It’s enabled a tool for a digital process around this idea of recording my workouts.

We’ve gone from the wonderful old handwritten training diaries to digitization, and digitization has facilitated a lot of other things.

The three ingredients I would say have really added up to something on top of that layer of internet infrastructure are, number one, wearable technologies — biosensors of different kinds that are able to take whether it’s temperature, glucose concentration, or heart rate and generate an electrical signal that can then be properly smoothed, edited, and so forth to give us this data and information.

Then, what makes that come together is Bluetooth. That was developed by a company called Ericsson in Sweden. Nobody owns it now, and it continues to develop as a kind of personal area network device for connecting all of our devices.

Then the final ingredient is something that most of us don’t know anything about, but we’re using constantly: APIs, application program interfaces, which allow information from different data sources, databases, and so forth to be integrated, aggregated, and time-synchronized.

That’s the ecosystem, or the cyborgish kind of world that our athletes live in.

In answer to your question, is it good or bad? Yeah, it is both good and problematic.

Like many inventions through the ages, they can be misused and used, and they are. I’ll leave it at that to start with.

I would just say almost everything else — all the wonderful nutrition work, all the issues around psychology — a lot of that is enabled. We can be more holistic. We can connect things in part due to that environment that we’ve created.

[05:07] Dr. Iñigo Mujika
It’s interesting that you mentioned the internet because last night I was having a conversation with my partner, and out of the blue, I suddenly said, “It’s incredible what the internet has done for us.”

I’m updating one of my presentations that I have to give in Barcelona next week, and I remember when you wanted to put together a lecture, for every single slide you had to go to the library, pick a figure, photocopy it, and then draw it yourself into PowerPoint.

Now, just in a click, you can access the paper, copy and paste the figure into your PowerPoint presentation, and everything is so much easier thanks to that.

I know putting together presentations is not endurance training or endurance sport, but all I can do is agree with what Stephen said.

That said, from my point of view, one of the things that has improved a lot is individualizing the entire training process.

Nowadays, we don’t worry so much about the group we are working with. We can really focus and target the individual, in part thanks to all the technological advances that Stephen mentioned, because now we have individualized access to everything that’s going on during training, and we can adjust and modify our training program according to the individual data.

[06:46] Trevor Connor
Dr. Burke, what are your thoughts?

[06:48] Dr. Louise Burke
I had both those thoughts. But if I have to think of something original, I think one of the big changes in nutrition has been not just the personalization of the way we work, but also the periodization.

We now recognize that there’s not the athlete’s diet, and there’s not the diet that the same athlete eats every day once they’ve got it right.

We now follow the model of training, understanding that there are different phases to the season and different types of training sessions that athletes do. We now arrange nutrition around each of the sessions to fit the goals of that session, and know that that will change from day to day.

There’s so much more scope for creativity with nutrition, lots of different goals to be met, but also ways in which the same foods can be reorganized to meet those different goals.

[07:46] Trevor Connor
Going back to your point, Dr. Seiler, all this data that we can collect now — I remember we did an episode where we had two gentlemen who spent years seeing how the Ethiopian runners were becoming dominant in the field.

I always remember they talked about the fact that they would run in a group. These were Olympians. These were top runners. They would have one heart rate monitor, and they wouldn’t even wear the strap. They would just use it to keep track of pace and time, and basically hand it to the leader of the group and say, “Here’s your target pace.”

That was as sophisticated as they got, yet they absolutely dominate the running world.

So it seems like you can still get to that highest level without a lot of data.

My question is: is this just creating noise, or are we able to have athletes reach a level with all this data that they couldn’t reach before?

[08:47] Dr. Stephen Seiler
Right. The answer to your question is: it depends.

It depends on the athlete. It depends on the environment. It depends on the technology.

There are technologies that just don’t work in the real world. They work maybe in a very artificial environment, but then when you try to move them out into the field, the signal-to-noise ratio changes, and you don’t know how to interpret the data.

So it all comes down to the fundamental test of: does this new technology add information that helps me make better decisions? Does it help the coach and the athlete make the day-to-day decisions that add up over time to better performance, better health, or whatever it is that ultimately puts them closer to the goal — the gold medal or whatever it might be?

A lot of these technologies, I would say, don’t stand up to that test. They have good intentions, but they don’t work in that very challenging environment of high performance.

Now, I want to say this: I’m doing a project in Addis Ababa in Ethiopia with runners, and we’re getting a little bit more technical, so we’ll see how that goes. If I ruin them, then you’ll know here first — it was me that messed it all up. I got them to start measuring heart rate a little bit more.

But what we see is that our best endurance athletes actually are quite discriminating about the technologies they use. They don’t have the biggest technology toolbox.

It’s often the recreational athletes, the weekend warriors, the Stephen Seilers, who are using way more technology than they should be and not focusing on the fundamentals.

[10:55] Dr. Iñigo Mujika
I don’t think the sport you used as an example speaks for all endurance sports.

Endurance running is so dominated by the Africans that, yes, in that example, there are genetic components, altitude, etc. But in other endurance sports, such as professional cycling or triathlon, the technology has contributed a lot to the understanding of the entire training process and the understanding of individual athlete adaptation.

So I think there are different situations, and it’s not comparable. The world of endurance running in Eastern Africa is not the same as the world of professional sport in Europe.

The technology can be used or misused.

When I was coaching cyclists and triathletes, I would say, “I’m not interested in the power output today. But tomorrow, yes, when I said 342 watts, I mean 342 watts.”

I don’t want an athlete who is completely obsessed with the numbers and the data. But sometimes we can guide our training very well using the new technology. That’s a positive aspect of it.

The negative aspect would be being over-reliant on the technology and then being completely lost and unable to make your own mind or take a tactical decision during competition unless you have the data in front of you.

That would be a clear example of misusing the technologies — being lost in the numbers and unable to make up your own mind on whether you should attack, hold it, or make a surge.

[13:06] Dr. Louise Burke
I think some of the data you’re receiving are also really spurious.

There’s a danger to looking at your watch when you wake up to see what your sleep rating is, especially on a day of competition, because you don’t want to see you had a disastrous sleep and think, “This is going to be a terrible day,” when you need to feel confident.

I’m a disbeliever in the benefits of CGM at the moment. I see far too many people worrying about their glucose spikes and attributing them to crazy food patterns which aren’t causing the problems that they think. They become so focused and fixated on that, rather than thinking about the bigger picture of what their nutrition is to be providing.

So there are times and places, and I think too much information is definitely too much.

[14:00] Dr. Stephen Seiler
If I can chime in there, metrics — whether you’re working in leadership, industry, or anything else — have a tendency to skew us.

We have good intentions, but if a scientist is told that part of their research time is based on the number of publications, because that’s what we can count, then you game it. It becomes gamification.

There’s always a tendency for metrics to skew our attention away from the original goal and into the metric itself.

In this case, your behavior starts being driven by the metric itself: “Oh, I’ve got to get my heart rate variability up,” or “My sleep quality was down, I’ve got to get that better.”

You’re forgetting that this is part of the process, but that’s not what you’re training.

We get derailed by these spurious metrics.

Marco Altini has said something really useful. He lives from a product that measures heart rate variability, but he’s very open and says, “Look, most devices, like our heart rate watches or whatever, measure just the one thing. They measure heart rate, hopefully validly. Then we get all these darn estimates of everything else: my readiness to train, my sleep quality, my form, my fitness, and my VO₂ max.”

All of them are estimates that have a huge amount of noise associated with them. By the time you work your way out enough, they are only slightly better than a 10-day weather prognosis. They’re just bad.

Unfortunately, that’s the nature of the industry. They make more money by iterating software and algorithms than they do by iterating hardware.

[15:58] Dr. Iñigo Mujika
This past weekend, I was at a conference and somebody reminded us of the classic: not everything that can be measured matters, and not everything that matters can be measured.

I know we’ve heard that a million times, but it really applies when it comes to technology used in sports.

[16:19] Trevor Connor
Is there a technology that you would love to see happen? If you could make it happen, what would that technology be?

[16:31] Dr. Iñigo Mujika
I remember that question being asked at the Australian Institute of Sport in, I don’t know, it must have been in 2004 or something.

I talked about this movie called The Island, with — what’s her name, the American actress? You can cut this later.

It’s this movie in which this guy wakes up in the morning, goes to take a pee, and as he’s peeing into the toilet, there’s this screen in front of him saying, “Oh, you haven’t been taking your vitamins this morning. You better make sure that you do this and you do that.”

So everything is being measured automatically as he pees into the toilet.

I think if we could do this — get everything immediately without having to put on any kind of gear and without any waiting before you get your numbers — it would be fantastic.

[17:55] Trevor Connor
The only thing I’m picturing here: we talked about how people are scared to look at their sleep score. You’re going to have people in the morning who absolutely have to go to the bathroom but are scared to pee.

[18:06] Dr. Iñigo Mujika
Yeah, because I don’t think I want to know the answers to all that stuff.

We’ve been talking about whether the numbers are valid or not, whether there is variability or not. Of course, when you have something like this, it has to be valid numbers that really tell you something that is properly measured.

Not something like, “Oh, maybe your vitamin D is not high enough.”

We need precision in the measurements, and we need proper answers to what those measurements are showing and what is required as a result of those measurements.

[18:46] Dr. Stephen Seiler
I think you could think in terms of a pyramid.

What do you need to be able to measure at the most fundamental level and get it right every darn time, kind of like vital signs in a hospital? Then you go from there.

But if you don’t get that right, then the other stuff doesn’t matter.

You have to build the data capture process stone for stone, from the most fundamental to the most esoteric and detailed.

Unfortunately, maybe sometimes we get that turned upside down. We get caught up in the esoterics and forget the fundamentals.

[19:25] Trevor Connor
Before we move on to the second question, Dr. Burke, you mentioned earlier that we’ve really advanced nutritional periodization.

I would also say on the exercise side, the training side, we’ve also improved periodization.

I remember 20 years ago, if an athlete hit their peak on time for a key event, it was as much luck as anything. Now, particularly in the last 10 years, you see athletes that just seem to hit top form again and again and again through the season, right at the right times.

Is science driving that, or is that just continued experience from year after year, athletes just experimenting?

[20:07] Dr. Louise Burke
I think it’s a bit of both.

Periodization of the model is very much more sophisticated, but it only becomes useful when an athlete can work with it and then tweak it to suit their individual requirements and experiences.

The best scientists are those that, as Iñigo said, work with individuals and listen to the individual, take feedback from prior experience, and then move it into the future and continually tweak.

That’s the relationship between the athlete, coach, and scientist that makes a really important contribution because people have to trust each other.

The athlete can get feedback, but needs to have that interpretation from the coach and scientist’s perspective, and then trust that all those learnings can be modeled into the next iteration.

[21:14] Dr. Iñigo Mujika
If I can add to that, I would say that all the research on tapering and peaking that has been done over the past 30 years is finally having an impact in many athletes.

Starting with Costill and colleagues, and then the work we did with Thierry Busso on the mathematical modeling based on Banister’s studies of adaptation, it has provided some useful information in terms of learning about tapering and peaking.

I’m still surprised when I get invitations to speak about tapering and I go somewhere, and it’s the first time some people hear about it.

So they are not even thinking about individualization. They don’t even know the basics.

Stephen mentioned the pyramid. We already know the basics of the pyramid in terms of peaking or tapering to peak for a particular competition. Then you need to add on top of that to the individual athlete.

People still don’t know the basics, which is quite surprising because we have a background of research that has provided us with those bases.

[22:35] Dr. Stephen Seiler
Periodization has been part of my mindset since I traveled to Moscow in 1986 at age 20, and I was committed to learning the secrets of Russian periodization models.

Well, I was disappointed.

It turns out that when we talk about periodization, we have to start with that Maslow’s hierarchy again and talk about just intelligent variation as a starting point that athletes have figured out.

We can’t go out and train hard every day. That solves a lot of problems: understanding that there needs to be a rhythm in the training.

Whether you want to call it 80/20 or polarized or something else, you can’t go hard every day. You need to manage the load.

Then you layer on top of that more precise periodization, where you’re saying, “I want to have a specific order of the emphasis of loading.”

So my lesson often is: get the simple things right first. The rhythm of training, the need for recovery, and things like that.

Then on top of that, you can build a platform of periodization where you’re actually ordering mesocycles in some specific way toward a peak.

But if you’re going to look at periodization, you have to compare it against the backdrop of just intelligent variation in the load from day to day.

Your control baseline cannot be just monotone training. It needs to be a reasonable variation.

Athletes have come a long way on these things, and I want to say that we have contributed to that in sports science and the internet, because this information is so much more available.

Young athletes and teenagers are already able to go in with their coaches, get help, and make better decisions.

So I think all the things we’re talking about — all the way back to the start of the internet and access to information — are making a difference.