Ro men, welcome back. For years, we've been obsessed with power meters and heart rate monitors. But what if I told you the next big breakthrough in training is focusing on something even more fundamental?
Your breathing. It's not science fiction. Vizma Lisa Bike is already using this cuttingedge wearable technology from Timeware to track breeding in their training, effectively establishing new training zones.
To help us understand this shift, our guest is the founder of the technology Timeware. This innovation has the potential to be the biggest breakthrough since heart rate monitors first hit the scene. So, if you're ready to learn why your next secret weapon might be as simple as breathing better, stick around.
This conversation's going to be a breath of fresh air. Oh, that that's brutal. Let's dive in.
Let's dive in. Arnor, welcome to the road map podcast. Thank you.
Thanks for having me. Really interesting innovations coming out of you guys and I'm hoping I can somewhat democratize some of these big physiology words today and show people how this could be useful for them. Thank you.
Yeah, most cyclists we obsess over heart rate, power, but how big a role does the respiratory system play when somebody's looking at performance? Well, it's pretty fundamental. If you if you try holding your breath, you're not going to last very long.
Uh so I think that that alone underlines kind of the the the importance of of just the mechanics of breathing the the fact that we're we're getting oxygen in returning CO2 uh that is going in and out of our lungs. So the respiration or ventilation uh is is fundamental to just getting fuel uh into the body and using that using the fuel within our muscles and uh the efficiency with which we we get it out uh can all be gleaned uh uh from how our respiration responds to uh to the workload that we're putting it putting ourselves under. So where would you say it sits in a hierarchy of heart rate, power and now this new respiratory system for measuring?
Uh so um if you in a in a lab it's the it's the fundamental thing we measure um maybe that plus lactate uh to understand how the how our muscles are are performing in terms of the output and efficiency. uh it is the the only thing that we that we want to measure. So if we think of of of heart rate as kind of a proxy for oxygen, uh power as a a proxy for for workload and output, um those are those are proxies that we can also measure in the lab.
And if we want to uh take any sort of u metrics outside of the lab and and apply them in the real world, um they are calibrated based on ventilation and and breathing in in the lab setting. And then we take those assessments and take them out out into the field and and use them as proxies. Uh breathing really is the fundamental thing that that we care about and and can use to understand an individual's response uh to exercise.
And uh and so the the way our system works for example is uh we measure the chest wall uh expansion and contraction and from that we get metrics that are called uh breathing rate. uh we get an index for tital volume. Uh and when you multiply those two together, you get the flow rate in and out of the lungs.
So how much volume title volume is the is the volume per breath. So how much air goes in and out of the lungs uh with each breath. And so by tracking the expansion contraction of the chest cavity, we're getting an assessment of how much stuff is actually going in and out of the lungs with each breath.
And then so do we have to baseline that chest cavity expansion? Uh no. Yeah.
So we uh we do um uh we do basically what's uh you can call it a factory calibration. So uh we actually output the um the actual circumference change uh very accurately u and uh and then that uh directly correlates with the volume change. The important thing is that it's it's uh it it's not so much that you're you're getting an actual uh leaders.
Uh the important thing is that you're getting the the relative change and that that relative change is consistent day-to-day for each person. Um and so if you have a consistent change and and you're you have u you've sort of a concrete measurement tool to get that consistently, you know, workout to workout uh dayto-day. Uh that's the the key thing that we that we that we really should care about.
I'm so torn in this new data age which we're entering because I love geeking out on it on the one hand and I've been really excited about this podcast since we put it in the diary because this is one of the IP I spoke with Professor Steven Syler about six months ago when I was asking him two things that he's really excited about. This was the first thing and continuous lactate monitors was the second thing. So I've been waiting for this for quite a while.
But on the flip side of that coin, I spoke earlier today with a journalist and elite runner who embedded himself in the Ethiopian training camps for distance runners. And he spoke about just the total move, not even a move away because they never embraced technology in the first place. They run off stuff that's more like it's more spiritual.
They they believe in like they believe in things like the energy of the collective and it's seen as a very selfish pursuit to go training on your own because that's an output of energy and that output of energy only benefits the individual rather than benefiting the collective and it's almost woohoo on one hand but there's something very romantic about it on the other side. So I suppose if you were to straw man the argument against data, what would that look like? Um well I mean I don't think they're necessarily um I mean uh they're not necessarily in conflict.
um you know even though they're you know if we take just that example um you know you can't take the physiology out of what they're doing even though they're doing it with a certain intent or purpose. Um you know the fact that they're improving their their physiology and and needing record getting record times is a is a fundamental fact that their physiology is improving and getting better. Um and so we can measure that independent of whether they want to know what's going on or not.
uh and we can know how to how they go about doing that from a physiological standpoint. And um and there's a lot of there's a lot of wisdom in uh you know the you know in coaching practice and and and and and sort of you know the trial and error approach of seeing what works and then and then implementing that uh from a from a training standpoint for for individual athletes and so forth completely independent of of any sort of measurement or physiology. Uh so so there are are things that that work and and if you're in that environment where you're immersed in it and you have people that really are I mean like artisans have their craft and and and and know what to do how to turn those dials and and um and then you know eventually someone comes out and is just like this you know amazing world record uh uh shattering uh type of uh uh person.
um you know, you've probably figured something out and to produce that, right? And that's what a lot of u a lot of coaching is. It's like you create these different systems and then you churn people through it and um and and out comes you know someone that can uh be an Olympic star or so forth and and um uh but then there's also like the counterfactuals where like a lot of people going through that didn't achieve that and and so I think that's where individualization and and understanding the physiology of like why did someone why did it work for this person and not that person and that's when we get into kind of what I think is super interesting with with different measurements is how do we understand the kind of the the truth of what happened in that process?
Uh and in order to start to answer that question, we need good measurements of what's actually going on. And um uh the fact that people respond very differently to different types of training uh on its own is a really interesting question because it gets to the whole idea that you know uh you know you can have a cookie cutter kind of mold and and and uh and it will produce some put enough people through it and it'll produce a a result for someone. Uh but then a lot of people will going to be left by the wayside.
And when you put when you actually measure someone's unique physiology, you can start to understand why they didn't respond. And um that's where I think technology andor sort of measurements and understanding these types of things uh uh starts to play a role. And when we talk about um you know when when you're when you're looking at sort of um you know ecosystems where in in that in that example that you gave where you know their life is they immerse themselves in this practice.
uh it's it's literally their life goal and and they maybe do very little else other than training for these things uh these types of events. Your your average person, you know, they they don't have that um uh type of and they're not in that type of environment. You know, they're you know, they're they have a 9 toive job or, you know, they have busy schedules and and and they've got a lot else going on.
And so, you know, you you could try as much as you want to tell the, you know, couch to 5K person, you know, you just got to, you know, you just got to feel the feel the spirit. Um, you know, they're it's probably not going to help them much uh because they they don't have that sort of infrastructure of uh both like community support that that you just mentioned, like they're all in it together. Um, and then the the uh sort of the trial and error approach that they've accumulated over time to produce the results that they produce.
It's an interesting take you have on it because the temptation I think for a lot of tech people or sports physiologists is to be super dismissive of these traditions and low tech solutions. But in reality, we talked about respiration, heart rate for a long time being a proxy for respiration. Well, heart rate variability and the other various wearables we're getting are a proxy for how we feel.
So they're one step closer to understanding how we feel than we are with the data a lot of times because they've learned to tune into the voice that we've tuned out. Yeah, I think there's a lot to be said about that. And um uh you know there's a you know we're we're quite I would say we're quite disconnected in our digital age and um and I think that you know if you're if you're an athlete and you're and you're practicing your craft day in and day out you know you're at that you're at that professional level you're going to be much more in tune with kind of how your body feels uh how your body's responding.
But even there we see like at the at the top of the the you know at the at the top levels of of of of like cycling and other sports you still get a disconnect um right of like how I feel today versus uh how this effort feels uh you you get a sort of a a gradual slipping of that of that calibration. Um, so if it's hard for the best in the world, can you imagine how hard it is for for the person that's just trying, you know, taking the first step to steps towards that? And then you have that whole spectrum and and and where like, you know, whether it's u, you know, HIV or or or or in our case respiration or ventilation.
Uh, it can sort of re help you recalibrate, not to mention it can help you understand kind of what steps to take. It shortcircuits a lot of the kind of the the trial and error guessing because we can know certain things within you know 30 minutes uh and say this is your profile. This is the type of training that is appropriate for you for the next four to 6 weeks.
Um here's the the workouts that you can uh you can put into your schedule and and then we'll see over the next four to six weeks how you respond to that and by measuring that response we can see how effective that was. Um and then we can we can eb and flow and iterate uh in a in a very autonomous way based on the actual physiological input that the that the user is is is submitting to the system. Yeah.
Because at a certain point, heart rate for busy athletes began to make a little bit more sense even with all its inherent drawbacks of, you know, bad nights sleep, poor hydration, stressed, fatigued, all affecting heart rate. But and we were led to believe that power was a step change. It's an improvement when we all move to power meters.
But the problem was I would head out the door on a Saturday to do by 2 by 20 threshold and sit at 380 watts at a perceived effort of seven and a half eight out of 10. But on a Tuesday evening after a long day in college and commuting I would try and sit at the same intensity and I blow my lights in with inside four minutes perceived efforts 9 and a half 10 out of 10 can't hold the wattage wattage is sliding. So a lot of people then were left with do I default back to rate of perceived exertion and ride this as an eight out of 10 effort?
Do I default back to heart rate even knowing its inbuilt limitations? And we're left a little bit uncertain. Do you see respiration as being a solution to this problem?
It's yeah it's definitely part of the solution because we see that u um when we look at at minute ventilation for example so the the air flow in and out of the lungs um it it stays u much closer to uh the the true effort that you're you're trying to do independent of heart rate or power so um so if you uh there's a nice study that was done a couple years back where they uh by uh Ed Manders and and Dan PL they they had um uh they had these uh uh subject objects go through I think a a one or two hour kind of VT1 which would be like kind of your top of zone 2 you know so endurance pace uh type of a of a ride and uh uh and they tested the uh the power ventilation and heart rate uh associated with that first vent uh threshold ventil ventilatory threshold one uh before and after and they found that ventilation stayed consistent before and after. So there was no u apparent uh effect on on the ventilation response but there was a uh about a you know I think it was like a 10 15% increase in heart rate and about a 10 15% drop in power and what that tells us is that fatigue there and the stress of the workout that uh uh even though it was a low intensity workout the stress induced um or or possibly slight dehydration we don't really there any number of the factors that you mentioned uh could have been contributing on the heart operate side and then the fatigue setting in as you're kind of you know working your muscles and and over that over that period of time uh impacts the power associated with the thing that you're trying to target. Uh so ventilation seems to be and we're seeing this also uh uh in the data from our from our users uh across the board uh from the from the top of the world tour down to uh kind of your casual casual athletes.
uh it's a much truer signal of the the effort that you're trying to uh produce in order to elicit the change that you're that you're trying to produce. Hey everybody, let's take a quick break to talk about the bike I'll be riding this season, Reap. I've been lucky enough to ride all the top brands in the world over the past few years.
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I absolutely love my one and I couldn't recommend it highly enough. Back to the show. So when I get that cardiac drift on a zone 2 ride, so 220 watt ride, 5 hours, 120 beats for the start of the ride, then I try my best to stay on top of, you know, using as much as can athletes Kitchen Hexus, whatever to plan out my fueling, stay on top of my hydration, work on efficiency, whatever that means to some people.
But I inevitably have this decoupling of heart rate and power as the ride goes on. heart rate rises for a constant power. Does a ventilary threshold become like a moving target that adjusts downwards as I fatigue during this ride?
Well, it gives you that that that ceiling to to to uh to have as your target. Um and so and so you can when you have the ventilation on on your on your uh bike computer uh you can allow the power and heart rate to do uh what they naturally will do whether it's to drop the power to uh allow the heart rate to drift um by controlling the ventilation controlling to the ventilation. Uh and so it it really becomes a so so the fact that the heart is heart rate is drifting is actually very interesting.
It's it's a signal. Um and and we would expect that to change depending on a number of circumstances and and fitness level and progression of fitness level and durability and so forth. And we would expect the the power uh at that at that effort to uh to drop less over time.
Um so if you're if you're progressing, you can imagine the you know if you're if you're just starting out, maybe two hours is is going to you're going to have to drop your watts, you know, 15 20 watts and then as you uh and heart rate might have drifted, you know, 10 15 beats. Uh, and then as you gain fitness, three hours, it's going to cause that same response. Four hours, it's going to cause that same response.
But when you go back to the in that three-hour ride, you go back to the two hours, you're much more stable. And and so that's actually a signal that that your body is adapting in a in a positive way. Uh, and and there are acute things that can change that uh, you know, on a day-to-day basis, but over the long run, that's the trend we want to see.
Uh and so when we have ventilation, we can much better control for the thing we're trying to control for and allow these other things to tell us what it's actually telling us that no, I'm actually getting fatigue. My durability is not greater than this or no, now my durability has actually improved by this much. Uh and and so on and so forth.
So it it allows us to use those metrics in a in in what we think is the the way that they were meant to be used. Uh not as the thing to control for, but the thing to actually see how our body's responding to the thing we're trying to control for. Yeah.
Because we've been led to believe that there's a fixed basket of physiological adaptations that are in each of these zones. And each of the zones are like stepping off the edge of a cliff. If you step out of your threshold from zone 2 to zone one, now you don't get the associated benefits from zone two.
So, if I'm in error five, even if my perceived effort has gone up and the bottom of my zone 2 is 200 watts, I don't want to ride a home at 160 watts because I've been programmed to believe that riding a home at 160 watts isn't the goal I set out to achieve. I'm not getting the basket of adaptations that I set out to achieve if I drop below that. Well, yeah.
So, I think the there there are a few really nice ways to think about this. So, one is is managing your your st the stress on your body. um uh as you train and and I think the one of the the key things is is the consistency with which you can apply stress on the body in in a manageable way and and you sort of string together uh a series of of of of days and weeks and and months of of really good training uh that's going to if you can manage that then that's going to produce uh really good results.
And then it's the spectrum of of of stressors that produce a result. And um uh and and uh I think u uh it the the uh I got this from from Steven Syler. I sure he he got from somewhere else but uh Ste they call it this bow tie um uh mechanism for for stress in something happening in the middle and then the the results happening on on the on the back end of the physiological adaptations that happen.
And so a a lot of there's a whole range of stressors that can create uh the the same responses and and the and the key thing so you can think of like low low stress over long periods of time, high stress over short periods of time. They go into this like bundle of of stuff that's that's changing and and adapting your body to those stressors and outcomes these out come these results uh improving your fitness, improving your durability and all these things. And and the key thing is to manage that stress going in and and in in order to be be able to string together those those series of of weeks, days and and months and years of of training effectively without burning out, without overtraining, without um uh without injury and so forth.
Like does it open up a new frontier of coaching for us? Because as you're talking, I'm wondering because the first time we can begin to understand and have truly individualized plans, we can begin to understand why I got an adaptation from that training block and you didn't. Exactly.
So, so breathing gives us that that sort of that that view into uh and and it's great when we triangulate all of them together, breathing, heart rate, and power. Uh but it finally allows us to kind of see a much clearer picture of the stress that we're placing on on the person. So, so the way I think about it, like ventilation gives us the individualized zones.
You can do that in like a ramp test and you can establish your VT1, your VT2, your V2 max. You can you can delineate your zones that way in a in a sort of a somewhat static way, right? Like you do a test and you get these results and that creates your zones.
But then breathing as this as this new way to understand the stress on the body uh gives us a completely different view of of how much stress at a given time we're applying to the body and how um and it's telling us a different signal or different uh it gets giving us different information than what heart rate and or power is giving us. And so you you might have significant heart rate drift uh on one day with stable ventilation. That's going to be telling us a very different thing than the same day when you have, you know, moderate drift, but ventilation is going along with it.
That's a different that's a different stressor. And and um and so we can help us kind of tease apart what's actually going on with the individual in uh understand the stress that's being applied. And then on the on the back end of that we can then measure okay did your thresholds improve um what were all the stressors that led to the change that we're observing or we're able to measure and so it gives us this sort of like uh um uh kind of you know book ending and also all the books in the middle to understand you know what what's the what's the starting point what happens in the middle and then how did you change and we can compare that we can then say like okay you adapted really well to this uh you you didn't adapt very well and it's all end of one.
It's all just you. It's not like you know you com you you as an average of the population we're assuming that you have XYZ traits and therefore you know you're going to we we're going to assume you respond in this way. No, it's just like here's your starting point.
Here's what happened. Here's how it ended. Uh and then we can make decisions based on that.
Then we can we can take that end of one and compare it to kind of other populations like is this a high response or a low response compared to where we've seen in other places. That's a totally different conversation than using the the the the b getting a baseline that is based on population averages. And so the with ventilation we can completely flip this whole model around of saying like you know using heart rate zones which are usually based on uh uh uh averages on uh based on on on the population uh and and they have very wide error margins.
So we don't really know where you actually are but we get a you know we get maybe an order uh first order approximation of where you where you should be and then a good coach can kind of work with that and and and sort of fine-tune that model. Uh but as an individual who who doesn't know how to fine-tune that model, you're kind of, you know, up shit's creek a bit and um you don't really know, you know, how what what's happening, what's improving, what's changing, and so forth. And so you can kind of get lost in the weeds.
And I think that's that's a big thing that that we we see is there just like the simplicity when you just know where you are. Like you literally just get a measurement like this is my fitness level. This is what I do to improve it.
It it can't be simpler than that. the the complexity comes in when we're trying to fit these like square pegs into round holes of like you know using all these crazy formulas and and and and this estimations and and you know we're going to you know correct for this and that and because of you know xyz parameters and like that's when it really gets complicated. you know, we we're kind of like, you know, we're we're we're trying to be too smart and and uh and uh but we're just using the wrong data and and that's really where it comes down to kind of that's that's, you know, fundamentally that's where I see ventilation playing such a big role is that cuts through a lot of that noise and just allows us to measure the individual how they respond and and it's really simple.
And how do you think about load management with it? is traditionally we've tested our threshold. We've assigned 100 training stress points to 1 hour full gas at threshold power.
And then everything else has been a function of that. A 2-hour ride at 50% of my capacity becomes 100 stress points. A three-hour ride at 33% becomes roughly 100 stress points.
Then we've taken a 42-day running total of that and that's become chronic training load. A 7-day running total of that and that's become acute training load. And collectively we put these together a training stress balance and we have the performance management chart which a lot of cyclists and coaches rely on to figure out when an athlete is doing too much ramp rates.
This turns it all on its head. Yeah. Because I mean it's not that you can't use that as some kind of starting starting base, but but you're just making massive assumptions by doing that.
You're assuming that that that is that you know all those numbers you quoted that you're assuming that those are are correct and appropriate and uh and then and and you have no visibility of then if if the input to that especially if it's only power then then you only know what the person did not what it did to them and and that's and that's the key even to run with our example from earlier the kind of cardiac drift you're assuming a totally linear relationship between hour one and five that it's the exact same physiological taxation on the system which anyone who's ridden for 5 hours knows it's not. Yeah. 100%.
Yeah. And that's that's the key thing. So So the way I the way I see it is that we can start to create um assessments based on data um and uh and really start to just describe okay this is what's happening and and when we know this is happening then we can we can adjust it in this way.
Uh or this is the response that we're looking for uh in terms of what it's actually doing to the person. You know we want this level of stress for this amount of time. um or uh because we saw this amount of stress for this amount of time that means that we're we're going to change tomorrow's workout uh in in this way in in order to sort of stabilize or keep things you know on an even keel.
Do you see a future where athletes are pacing time trials not off power but off respiration? Well, it's a it's a tricky question because, you know, once you're when you're at the time trial, you're executing what you've already put in the bank and um and so I you know, first and foremost, I think it's it's building building that bank account and that's where I think ventilation and all these what we've been talking about really comes to play. uh and um and uh there's probably a a level of understanding of of kind of seeing that data and how it's responding, but but really like you're building that bank account in order to deploy it on the time trial and and the the bigger that bank account can be created again by stringing together those effective workouts over really long periods of time um is is going to produce, you know, the the optimal result that you can produce on that on that race day or that time trial.
And um so uh you know in in one way once once you kind of have have that bank account you you might not even be you might be looking at the power as kind of your your proxy because you know that you know you're you're going to be going for this this many uh this many miles or or this many kilometers and and you need to you need to produce a certain average output. Um but um you know it's you're really executing you know and another way I think about it is like not not necessarily in a time trial but like in a race like if if uh if if someone's if someone's attacking like strategically you're not going to be looking necessarily at the at the numbers on your on your on your cycling on your on your heads up you know on your uh bike computer you're going to be you're going to be making a strategic decision. do I follow or not?
You know, and and and um and again that comes back to, you know, what have you done? I'm sorry to cut across you, but there is a school of thought there if it's a hilltop finish that you ride point A to point B in the fastest time possible, which totally takes the romance out of cycling because the aerodynamic benefit at lower speeds isn't as great. And you're probably going to gain advantage from just riding A to B as fast a time as possible.
Yeah. So, you know, I'm not uh definitely not an expert on on on race strategy, but you know, kind of just being a being a um being a competitive athlete myself, you know, in the in the past, like you can have you can show me all the numbers like if you there there's a certain time in a race and and and maybe maybe it does depend and and uh at certain uh at certain times you you make certain strategic decisions and the data might inform that. Uh but you know, you're I think at the end of the day, you're either going to you're either going to follow or or execute your strategy um uh uh or not.
And um and I don't really see I um I I have a hard time seeing any kind of data really kind of uh giving you a red light like no, you're not going to try to, you know, win this race. You know what I mean? So again, just thinking out loud here, maybe the answer is no to this, but we've used that acute training load as kind of a like a little bit of a a dubious yard stick and when someone is overreaching or maybe you had a CTL ramp rate and you said that's getting into the area where somebody's overreaching a little bit.
Is it possible to baseline someone's breeding rhythm and look for deviations from baseline like changes in breeding patterns to give us early warning signs of overtraining or overreaching? Uh the way I think about that is the relationship between for example your your ventilation and power and it goes back to that that sort of you know um uh ventilation being kind of again this like true uh especially for the for the easy endurance you know the the stuff that we do you know 80 90 95% of the time um the that sort of true indicator of that of that uh intensity or effort and uh if you see that shifting considerably so so what happens s when you kind of overdo it, you overcook it, you you start to see a a sort of a a shift in that in that relationship where the same ventilation is going to produce a a lower power and and if you see that sort of going in the wrong direction or being becoming, you know, chronic, then then that would be an indication that someone is overly fatigued and and then you might I suppose I'd look at that as a micro indication like I'm thinking more on a macro trend. If we seen patterns of this day after day, would that be a indicator to you for somebody to not race the planned stage race coming up or to take, you know, two, three days rest instead of the planned one day rest or is that a stretch?
I don't know. I just don't know. The honest answer is I don't I don't I don't know.
I don't think we're we're there yet in our understanding to to to know if we can answer that uh that uh that exact question. Uh I do know that fundamentally it like it gives us a new window into uh into that uh that effort level and uh and there are really interesting things that we can start to see in terms of how that uh shifts uh as someone fatigues. And so um you know from from that perspective I I think that there there are some indications to say someone should pull back.
Um the other thing we've seen is like uh when you fatigue there's uh you know there's this sort of you get this sort of dampening effect on the on the higher end as well. So uh you might be pushing watts a little bit too aggressively on the low end and that kind of dampens your ability to output uh watts on the on the higher end and uh you become less responsive. you you kind of, you know, you're you're you're stiff, you know, you're stiffer, you're kind of you're not able to produce as much output.
Um, and and when you dial in the the lower end, you start to see the the opposite effect. You become fresher on those on that higher end. And and I think that has a lot to do with kind of that chronic um you know, you guys going out, you know, six, seven, eight hours and and and if they're 10% above where they should be, like that starts to add up uh a lot.
Uh and um and so uh you can get into you can probably it's probably in in an insidious way you can start to get into kind of a a negative feedback loop of of of excess fatigue or unnecessary fatigue. We have three long form podcasts every week. Some of them are 90 minutes or 2 hours long.
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Go sign up. What's your relationship been like with uh Vizma Lisa Bike? I know some of the guys there are using it.
Is there other world tour teams using it as well? And you know, if so, what's the interaction between you and the world tour team or teams using it? So we uh we have a very close relationship with with Visma um u number of their coaches and um so right now the the whole world tour men's and women's teams are uh are uh equipped with our sensor and uh the coaches are so bisma takes a very u they have a a very methodical approach which is awesome for us because it it really allows us to uh to to learn very well with them.
And uh and so we're in this phase now where we're collecting data and and starting to implement on on on on small scales uh with that with those insights. And um and so uh I think we've we've learned just an incredible amount uh from our interactions with them. They've been to two camps now um basically embedded with their their coaching uh their performance uh coaches and and the athletes and um we're seeing things every single week that you know on on their own could be uh just really nice features for understanding all the stuff that we we just talked about from uh from intensity control, threshold detection, um uh sort of this chronic uh uh load assessment and and and and how that changes over time and uh uh yeah to even in in some cases respiratory uh uh you know patterns that could be conducive to you know lack of performance.
So uh there's a a lot of stuff that we're uncovering with uh with them. Some of Have you had any surprising insights from observing the Vizma writers that you didn't expect? Um, I guess, you know, I'm always surprised by how similar the physiology is, uh, at its core.
So, like you you take kind of the the general response of of someone at the World Tour level and the general response of someone that's kind of, you know, your your your normal um, cyclist or, you know, someone that's very casual and and like it's at its core, it's the same thing. It's just they're just oceans apart in terms of their capacity. Um and um and that you know I always I before we we got a lot of these measurements I I kind of expected them to be just like completely complete anomalies you know in terms of like how they respond to certain things.
But really the main thing that changes is just the the watts associated with with those things. And um uh so that's one thing. And then and then uh it was a bit uh a bit surprising.
Some of the some of the things that we're seeing is just that you know the you know the that the fact that they're they're also human like you know they have they have they're extremely competitive. Um and um and there's a whole range of kind of you know emotional responses that that some of these guys have to uh or psychological responses that they have to training. you know, they they want to they want to improve and they want to they want they they're extremely competitive and so you you can have a you have a whole range of of so what what the the main um uh thing that I'm thinking about is you still have this sort of like uh creeping of the calibration of like what is easy right like these guys go out and ride eight hours and and for professionals you would you would think that they know what easy is but uh that even they are susceptible to kind of a you a gradual creeping of that of that uh calibration and and having something to recalibrate that we've seen like produces you know big jumps in in improvement and um so you know they're they're human also as as much as they look and and perform in inhumanely and is there big observational differences in the data between like a hardcore classics rider like a wenart and a straightup GC guy like Yonas Um can't really comment on that.
Yeah. No, that's in case boggy's listening. Yeah.
Does this have potent and again I think so much of what I'm thinking here is like this is year one of power meters. We didn't begin to understand and put together performance management charts and understand how it impacts various aspects of physiology and the different applications for it until 2, three, four, five years. But is there an impact on fueling strategies and recovery strategies off this?
Um on the recovery side, I think so because it's like it's like you're you're proactively managing the recovery, right? So so uh if if the if the input into the workout is is appropriately dialed in, the recovery uh in in many ways has you've sort of mitigated the need for excessive recovery, right? So the that sort of that 10% that you're you're excessively overdoing it by if you if you dial that back, you know, you're you're going to save that on the on the back end, right?
So, uh I that's the way I think about it. like you have like a recovery like like like aura or whoop, they they assess that recovery on the on the back end and and we can kind of inform that on the front end saying you know this is the appropriate intensity to control uh you know stay in this range uh and so forth to to mitigate any sort of adverse effects that that would necessitate higher demands on recovery. Um, the fueling stuff is interesting because, you know, we're we're not measuring O2, we're not measuring CO2.
Um, and and fundamentally when we uh when we inhale oxygen, it gets transported to our muscles. It burns fat and carbohydrates. It turns that into uh uh CO2 that then gets exhausted out through through the lungs.
So, we're measuring the stuff that's going the volume of stuff that's going in and out. Uh, but we're not measuring the contents of it. So we're not actually we don't know you have this many uh uh uh milliliters of of O2 coming in this many milliliters of CO2 going out but we know the the the the net net of what's what's being exchanged.
Uh so uh I do think that there there are there will be opportunities and and and uh using this data to kind of uh inform you know um certain fueling strategies but it I don't see it going to the level of like you know you need to take in 130 gram uh right now uh otherwise you'll you know not not perform but but uh but these models are usually based on power alone and so do I think that we can sort of inform that by saying you by overlaying ventilation data to say, "Yeah, power was this, but ventilation was that, indicating that, you know, power today was not the same as power yesterday." And that might mean something, you know, for your fueling strategy or refueling. Um uh yeah, I think that that's a reasonable uh a reasonable uh take down the line.
Arnard, it's a fascinating space and I'm definitely going to have you back on in 6 12 months where we see where the next iteration of this is. Thanks very much for your time today. It's been brilliant.
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