The days when training software simply showed a power and heart rate curve are a distant memory. Whether you use TrainingPeaks, Golden Cheetah, or some other software, you’ll know that nowadays basic data is mined to reveal a wealth of information about your physiology, strengths, and training. But, as soon as the software starts to interpret data, unavoidably, certain biases come into play. Perhaps better called principles, they are built into the software and any interpretations it performs. It’s not necessarily an issue, but it is important to understand the biases.
Most training software is based on biases that Coach Connor fully admits he would use if he was developing software. Created by coaches and physiologists, many training software developers knew what they were looking for and hunted for it in the data. One training package, however, stands out from this. Xert was created by Armando Mastracci who is an engineer first. While he came to understand the physiology, he started by simply looking for trends in the data instead of looking at the physiology.
The result is Xert, a tool that has found unique trends which may seem unfamiliar to a physiologist but are certainly compelling. At the heart of Xert is the notion of failure: the idea that we reveal our true fitness and our profile as a rider in the moments when we hit our limits at these points of failure. Armando will talk with us about how he was able to identify these moments of failure in athletes’ training rides, and then use them to create an athlete’s profile and help direct training.
But before we dive into the conversation it is helpful to define a few terms that are somewhat unique to Xert and this conversation: First, Maximal Power Available. If you uploaded a workout to Xert, you’d see your normal graphs — heart rate, power, cadence, speed, and so on. What will be new to you is a line calculated by Xert called your MPA or Maximal Power Available. This is a second-by-second graphic of how much power you could produce. When you’re fresh, it’s equal to your sprint power. After a killer attack up a five-minute climb, it may not be much more than your threshold power. It is dynamic and it constantly changes over the course of your ride.
We’ve already mentioned failure — it’s that moment when an athlete can’t go any harder. In Xert, it is the moment when your MPA line equals your actual power — meaning you are going as hard as you can go. And if the rider beside you can go harder, they will drop you. Finally, Peak Power, High-intensity Energy, and Threshold.
All software packages have moved beyond FTP as the sole parameter used to define an athlete. TrainingPeaks uses a power duration curve. Neal Henderson talked with us in episode 33 about using five-second, one-minute, five-minute, and 20-minute peak power.
Armando uses three parameters: 1) Peak Power: simply the power you can hit in a sprint when fresh; 2) High-intensity Energy: our capacity to ride above threshold, which is also often called Watt Prime; 3) Threshold: you know this as FTP. Xert uses moments of failure in rides and races to constantly adjust these three parameters.
Our primary guest today is, of course, Armando Mastracci, creator of Xert and owner of Baron Biosystems. He is the original brain behind these concepts, but he has also brought in respected physiologist and owner of Pez cycling, Dr. Stephen Cheung, to interpret these trends from a physiological standpoint, making for a more complete package.
Along with Armando, we speak with one of our favorite Fast Talk regulars, Colby Pearce, who needs no introduction. He shares his thoughts on this concept of failure. We also talk with Brent Bookwalter, of the Mitchelton-Scott WorldTour team, about some of these new concepts.
Finally, we’ll touch base with Paulo Saldanha, owner of PowerWatts and coach of 2018 worlds bronze medalist Michael Woods. Paulo discusses lab testing in comparison to finding an athlete’s fitness on the road in slightly less structured but more competitive scenarios. This episode is too good to fail. Let’s make you fast!
Secondary Guests Colby Pearce: Elite coach and bike fitter Brent Bookwalter: Pro cyclist with Mitchelton-Scott Paulo Saldanha: Owner of PowerWatts and coach of 2018 worlds bronze medalist Michael Woods
Welcome to fast off the velonews podcast and everything you need to know to write.
Chris Case 00:10
and welcome to Fast Talk. I’m your host Chris case managing editor of bello news, joined as always by a man whose vocabulary does not contain the word failure Coach Trevor Connor. The days when trading software simply showed a power and heartbreak curve, or distant memory, whether you now use training peaks, golden Cheetah or some other software, you’ll know that nowadays basic data is mined to reveal a wealth of information about your physiology, strengths, and training. But as soon as the software starts to interpret data, unavoidably certain biases come into play, perhaps these are better called principles, and they’re built into the software and any interpretations it performs. It’s not necessarily an issue, but it is important to understand the biases. Most training software is based on biases that coach Connor fully admits he would use if he was developing software. With the help of coaches and physiologists, many training software developers knew what they were looking for and hunted for it in the data. One training package, however, stands out from this approach, exert was created by Armando Ostrowski who is an engineer first, while he came to understand the physiology, he started by simply looking for trends in the data instead of looking at the physiology. The result is exert a tool that has found unique trends, which may seem unfamiliar to a physiologist, but are certainly compelling. At the heart of exert is the notion of failure. The idea that we reveal our true fitness in our profile as a writer in these moments when we hit our limits at these points of failure, Armando will talk with us about how he was able to identify these moments of failure in athletes training rides, and then use them to create particular athletes profiles and help them direct training. But before we dive into the conversation, it’s helpful to define a few terms that are somewhat unique to exert in this conversation. First, maximal power available. If you uploaded a workout to exert, you’d see your normal graphs heart rate, power, cadence, speed, and so on. What will be new to you is a line calculated by exert called your MPa or maximal power available. This is a second by second graphic of how much power you could produce. When you’re fresh, it’s equal to your sprint power. After a killer attack of a five minute climb, it may not be much more than your threshold power. It is dynamic, and it is constantly changing over the course of your ride. We’ve already mentioned failure. This is that moment when an athlete can’t go any harder and exert it is the moment when your MPa line equals your actual power, meaning you’re going as hard as you can go. And if the rider beside you can go harder, they’ll drop you. Finally, peak power, high intensity energy and threshold. All software packages have moved beyond FTP as the sole parameter used to define an athlete training peaks uses a power duration curve. Neil Henderson talked with us in Episode 33 about using five second one minute five minute and 20 minute peak power. Armando and exert use three parameters peak power, which is simply the power you can hit misprint when fresh, high intensity energy, our capacity to write above threshold, which is also often called y prime and threshold. You know this as FTP, exert uses moments of failure in rides and races to constantly adjust these three parameters. Our primary guest today is of course Armando astrology, creator of exert an owner of Baron biosystems. He is the original brain behind these concepts, but he’s also brought in respected physiologist and owner of Pez cycling. Dr. Steven Chung to interpret these trends from physiological standpoint, making for a more complete package. Along with Armando we speak with one of our favorite Fast Talk regulars Colby Pierce, who needs no introduction. He shares his thoughts on this concept of failure. Finally, we’ll touch base with Paolo Saldana owner of power watts and coach of 2018 world’s bronze medalist Michael woods, Paolo discusses lab testing in comparison to finding an athlete’s fitness out on the road in slightly less structured but more competitive scenarios. This episode is too good to fail. Let’s make you fast.
Trevor Connor 04:35
This episode of the Fast Talk podcast is sponsored by oat route. What is our route? Well, it’s not a cycling tour. It’s more than a road race. It’s a multi day granfondo style event where everyone starts together each morning and you can ride with friends all day. You can indulge your competitive side on time sections if you feel like it, and explore iconic cycling destinations around the world. Old route takes services to the next level with pro tour style support on the bike and rider focus amenities often choose from a dozen events in 2019 and France, Italy, Norway, Oman, Mexico and China. In the United States, there’s still entries available for old route Asheville in May, and oat route San Francisco and September, try something new in 2019. Try odhran.
Chris Case 05:31
Today’s episode of fast Talk is brought to you by whoop. The performance tool that is changing the way people track their fitness and optimize their training provides a wrist worn heartrate monitor that pairs to their app that provides analytics and insights on recovery, strain and sleep. know when your body is recovered or when it needs rest by getting to know your nervous system through heart rate, variability and quality of sleep. Automatically track workouts and get strain scores that let you know how strenuous training was on your body and see even more data like average heart rate max heart rate and calories burned. Get optimal sleep times based on how strenuous your day was and track sleep performance with insight into your sleep cycles and stages of sleep, sleep quality and sleep consistency. monitors heart rate 100 times per second 24 seven to give you full insight into your day so you can optimize the way you train. Having used the whoop myself, I can tell you it provides fascinating data that will change the way you train, recover and perform. Whoop has provided an offer for fast stock listeners to get 15% off their purchase with the code faster. That’s f a s t ta lk. Just go to whoop.com w h o p.com. And plug in faster.
Chris Case 06:55
Well, today we’re sitting down with Armando Mastracchio of exert, and we’re excited to have him on the program. Today, we want to talk a bit about some of the I guess unorthodox concepts as he’s come up with some of that on orthodoxy has led to him being perhaps a slightly controversial figure. So Armando, thank you for joining us. Welcome to Fast Talk.
Great. Thank you, Chris. Thanks for having me.
Chris Case 07:20
And maybe we should have you clarify a little bit about that. Well, first of all, do you do you agree that you’re a bit of a controversial figure? And if so, why do you think that is?
Well, I’ve certainly don’t see this as being overly controversial, simply because, you know, we’re making all of our data and information easily accessible. I think some of the controversy surrounds that the formulations that we’re using, we have not yet made public. So I think there’s some concern at which, you know, concerning that, there is there’s some capacity, I guess, in what we’re doing. And I think the reason why we’ve gone we’ve gone this this way, because, you know, we’re really looking forward to working with various research institutions to help them use some of the things that we’ve developed for research purposes. So we think there’s a lot of opportunity in that respect. I am not a researcher, I’m not a scientist. I’m an engineer. And I guess the one quality I would say I have that’s probably above and beyond most people is an extreme level of curiosity when it comes to looking at this stuff. Very, very fascinated by it. And so I certainly want to have an opportunity to work with various researchers. So I wouldn’t say I’m controversial. Hopefully, I’m not, I’m just more curious and excited about some of the things that that that I’ve managed to uncover.
Trevor Connor 08:41
So I think what’s really fascinating, and I should say, Mondo approached me many years ago in the early days of exert to check out the software. And I’ve been fascinated by some of the things you found, and by your approach, and I think this is why some people are a little confused by you or even see you as controversial, is that most people who have designed software would do, or have done exactly what I would have done. I’m a physiologist who wants to have a software, show what I know about physiology. So I think, in most of these other SAP software packages, you had people that came in and said, here’s how physiology works. We have these two thresholds, let’s find those in the data. And they really tried to twist and squeeze the data until they found the physiology that they were looking for. That was not your approach at all. You as you said you weren’t a physiologist, so you weren’t looking for any particular aspects of physiology. You instead took a whole bunch of rider data and just said what are the trends? what’s what’s going on here? And you went into a very unbiased look for these particular trends. found some interesting things that I think those of us who are searching for physiology never even would have thought to look for. And then to The other the opposite approach of you brought a very respected physiologist and Stephen, Dr. Stephen Chung, on board with your software and said, Okay, here’s the trends. Please explain the physiology behind these, I think or some of the controversy comes in is because you weren’t the physiologist, you didn’t use the what would be considered the proper terms, you use high intensity energy instead of watt prime. So I think that might be a little bit of what threw people off.
I think yeah, that’s there’s really something to be said about looking at the data and what the data is telling you about what’s happening to an athlete, versus trying to insert into that data stream, kind of your some pre judgments of what the data should be showing. And so since I’ve come at it from a truly unbiased perspective, in fact, without even the guidance of kind of a research or institution, you know, I’ll be frank, early on, I did proach, various individuals about some of the ideas and some of the models that I had originally come up with, I found them working remarkably well. But because I was a non academic, because I really had no name in the space, you really wasn’t, I wasn’t provided really much airtime with any individual. So I was stuck really working through this on my own. And what sort of drove this process was, you know, I managed to uncovered various patterns. And when I did the research research, I was able to gain access to, I didn’t see any explanations for them. And so I thought, well, if there’s no explanation for them, then and they seem to be working really, really well, well, maybe I should just keep going, right? Let’s just keep running with this, because I really can’t rely on the research to guide me there isn’t any. So in the process of doing that, for example, I came up with a way of modeling power cadence and heart rate, to give you an example, came up with the formulation for that. And I spoke to somebody about it, and he says, you know, you should look at, you know, some of the formulations from AV Hill. So I went and looked up at Hill realize he’s a, you know, Nobel laureate, and describe the these force, velocity patterns and muscle. And when I looked at the actual formulations, there were very, very similar to the ones that I came up with. And so I thought, wow, I must be on to something, alright, if I’m, if I’m coming up with some similar results to this Nobel laureate, then there must be something here. So again, I just kept running with it, believing that I was onto something.
Chris Case 12:24
let’s jump into this, this concept of failure. And I know Armando, you have an example to help sort of visualize this, you don’t really understand someone’s physiology and their their strengths until they’ve reached failure. And you have a comparison between Ryder x out there, and the great Peter Sagan that I think will help illustrate this point, if you want to jump into that.
Yeah. So you know, I get asked all the time, about, you know, what, what, okay, and how to understand it or interpret it. And the example that I always like to use is, is to pretend as if you’re riding alongside, you know, Peter, there’s a guy and you’re on this ride together, stay for the, for the time being that you’re the same way riding the same bike, and you’re riding side by side. So you know, in essence, you’re, you’re both generating the same amount of power. And, you know, you’re climbing hills are going through descending sort of power is variable. And you come to a certain point in your ride, where you want to climb the hill or your climb, you’re both climbing a hill. And at that point in time, since you’ve been riding side by side, there really is no information in the power data to indicate who is stronger than who you don’t really know yet, because you’ve already been riding side by side, who’s stronger than him? at a given point, all right, let’s say you both decide that you’re going to put down 500 watts, and you’re going to see who’s stronger. So at that point in the ride, you both right up the hill, side by side, and you’re both climbing and you’re still side by side, we still aren’t aware who strongly and who yet, you know, you’re both putting out 500 watts both together. But at some point, right during that climb, you’re gonna break, you’re gonna stop, you’re gonna get dropped, and Peter’s gonna be able to keep going. And as right at that point, we would call that a point of failure. Because you’re no longer you get up, you can’t sustain that wattage any longer. At that point, you would say, Well, how much power Did you have available? To answer that question? It’s really simple. How much power Did you have available, it couldn’t have been 500 watts, because if you had 500 watts, you would have kept going, we know that it’s less than 500 watts, right? And so that marks the point at which you fail. So that failure point is marked by this value of 500 watts being your ultimate limit at that moment in time and we also know that was only at that moment when we actually knew who was strong within who. Right? Up until that point we didn’t know. Right? But right at that point, Peter kept going, you had to stop Peter stronger than you. And so not only do we know that Peter stronger than you, we don’t really know how strong Peter is yet because he hasn’t failed, right? He’s going, he’s going really strong you are. So that moment defines the point of failure. It also defines your fitness level, we know what you’re capable of. All right at that moment, in exert. What’s interesting is that that moment in time is actually totally predictable. Because we can take what we call a signature, your three numbers represented by your threshold power, your HIE, and your peak power. When we know those numbers, we know when this point of failure is going to happen.
Trevor Connor 15:58
I think we really need to emphasize this point that when you’re out riding most of the time, even if you’re going out at a decent clip, you usually have this ability to go a little bit harder. So like you said, you don’t really know what what an athlete’s true fitness is. So I’m going to say that the the one place where you can kind of throw a wrench in your analogy is if you had heart rate, and you’re riding alongside Peter, and you’re both going the same wattage, but you’re at a 170 heart rate, and he’s at a 130 heart rate, you certainly know who’s fitter.
You can also say the same when we’re measuring NPA. So for both looking at in MVA interactively, you would be able to see that, you know, at minutes before failure, that my NPA would have been drawn much further down in Peters.
Trevor Connor 16:45
But this, so just to make sure that the listeners understand that because that is a very unique concept. And I think it’s a really interesting one. Again, that idea is let’s say you’re out for a ride and you’re with some buddies, and you’re doing 200 watts, one of you might be breathing heavy, one of you might be sitting there nose breathing. But the point is, both of you have this ability to go harder. So if you saw a town line sprint, you could both probably put out six 700, or more watts, to sprint to that town line. And as you were saying these moments of failure are those points where no, you can’t go any harder. So you’re going up a climb with somebody, and you’ve hit your limit, they haven’t hit their they still have that ability to go a little bit harder, you can’t go any harder. So they lift the pace, and you get popped. And that as you said, that’s where you see who’s fitter. That’s where you see the limits of your fitness. And I think that’s a that’s a really amazing concept that I haven’t seen anywhere else that you’ve really kind of jumped on, and actually modeled a way of seeing in the software, here’s your moment of failure. Here’s your point where you couldn’t go any harder.
Chris Case 17:55
And I think that one of the critical things here, and we’re going to get to this, but I just want to jump in and say I think what’s really interesting is how that will help you understand different ways to train. Is that correct? Armando? Yes?
That’s correct, right? Because there’s, there’s two aspects to what we’re going to use this for, right? We’re going to use this for knowing how much what your capacity to generate power was on a given day. So we look at your data, and we uncover when we look at those moments of failure. And we say, Well, what would have been your three signature numbers leading beyond that day to make that happen? Then we can track that. And we can actually detect, for example, when your threshold power has changed from these moments of failure. So this, in essence, is replacing the need to doing formalized testing, we can just take your your field data, use that to uncover your threshold and your other parameters. And then we can track how they are changing right over time. And then when you flip that around, since we know how they’re changing, what led to those changes, what training Did you do that that showed that increase in threshold power that you had on a given day, and that’s when we can move into the training side.
Trevor Connor 19:19
finding those moments of failure in your real world data can tell you a lot about your level as an athlete. But as World masters, our record holder and top level coach Colby peers points out, you need to be careful about just looking at those moments of failure and working on your power for those durations.
Colby Pearce 19:37
I mean, that concept is definitely interested. I mean, really what we’re talking about is rate limiting factors. And so the objective of training is always to prepare the athlete for the demands of their event. And so where that would be useful, but also potentially misleading are really the same thing because if we decide that an athlete for example, if an athlete does a race like Core states Philly us pro classic. And you look at the file for that. And we say, Well, he wasn’t able, she wasn’t able to go up that climb fast enough to say what the leaders, you know, 10 times or however many laps it was, I don’t know, it’s been a long time I was at that race. Now that hill is going to be a specific type of climb, it’s very steep, it’s not very long, and it kind of slowly domes over the top and flattens out. And then there are a couple sections where you really have to lift pace before you hit the descent. So it’s got a very specific torque curve and power profile that will be involved in that race. So we could look at that file and apply it in this sense in this philosophical sense and say, Okay, this athlete wasn’t capable of staying with the leaders on the climb. So we’re going to improve her, whatever it is three and a half minute power, but it’s got to be under these torque demands, she’s gonna have to stand for at least 50 seconds of that climb, because it’s pretty steep. And then she’s going to have to build a lift, lift, lift pace over the top, and that’s gonna be more speed oriented. Because the top of the climb is very flat, it’s got a couple of corners, and she’s gonna have to jump out of the corners. That’s a great way to dissect that event. If the following year, she’s going to go back and wants to win that race. You can focus very specifically on that aspect of her performance. But how many other races require that exact demand of that event?
Trevor Connor 21:11
And it’s also but I’m here to prove it’s a little simplistic to say that your peak three, three and a half minute
Colby Pearce 21:16
power simplistic, and it’s also reductionistic. Or even you could argue allopathic, right, you’re looking at the athlete and diagnosing a single thing that is air quotes wrong. And then applying a patch to fix that thing that is wrong by directly counter opposing what she didn’t have. But that’s it. That’s a very it’s, it’s just simplistic because, of course, there’s so many other variables that go into the impact of how fast she went up that climb on the eighth lap, or whatever live it was her cumulative fatigue to the race, her nutrition, her hydration, her preparation, how many efforts she’d done in the peloton, you know, whether she was on the front going into the climb, or whether she got dropped simply because there were riders in front of her, etc, etc. I mean, there’s a lot of nuance to it. So while I certainly think that type of analysis could be useful in looking at an athlete’s rate limiting factors, because every athlete ultimately does have rate limiting factors, I think you have to be a little careful probably not to get too far down a rabbit hole with too many specifics. And assume that it’s good that plugging these leaking holes are going to make a perfect athlete, because that’s not really the way it works. Ultimately, athletic preparation is based on the body and the body as a system of systems. So you have to look at how all not only you have to train all those systems in different respects. But you have to have some idea of how those systems interrelate with each other.
Trevor Connor 22:39
Let’s get back to the show where Armando will talk about how those moments of failure define your athlete profile. And then it’s that profile you should use to help direct training. I will say before we did this podcast, I took some of those training races, I took some of my workouts I put them into your software. Remember, I picked particular races are workouts where I knew I had hit a point where I was at my limit, and wanted to see if this if the software saw that saw those moments where Yep, Trevor couldn’t go any harder. And it was really good. It found those moments where Yeah, he was at his limit, he couldn’t go any harder. So my question to you is, how do you model this MPa? How do you find these moments where the MPA is declining? And the second part of that question is, I noticed that the MPA only seems to decline when somebody is above their, their threshold or above their, their critical power. And I think this goes into you talked about three key variables. So maybe you can explain those to us.
So so the way the MP formula works is it relies on three numbers, these three numbers being your threshold power, your peak power, your peak power, representing sort of how much power you can generate over let’s say, one five seconds, your highest power output possible. And then this other parameter called high intensity energy, and high intensity energy represents how much work available Do you have above your threshold power? So this is synonymous, or now analogous to the w prime? Or you might refer to as FRC or anaerobic work capacity as it’s been called in the past. And it’s basically how much work available Do you have above threshold? Now what we do uniquely though, is when you work above threshold, you’re essentially becoming weaker. And that that weakness shows as a depletion of this available work above threshold. So your high intensity energy becomes you start to use up your high intensity energy. And so what we do is we take these three numbers, we apply them to your power data, and then we derive MTA in the process. So when you look at one of our parts, you’ll see it plotted, you’ll see your power. And you’ll see your MPa pilot, and MPa is being calculated interactively, second by second, based upon your power data using these three numbers. And when you apply it that way, and you plot it, you can then see when your MTA and your power reach when they touch, those are moments of failure points of failure. The really important thing to understand here, and this is this is a hard concept to understand is to have those variables. So when you’re talking about threshold power, and you’re talking about peak power, those are just power numbers. So for example, my peak power might be 1000 watts, my threshold might be 340 watts. So you can just plot those and say, here’s,
Trevor Connor 25:46
here’s the wattage you can sustain for an hour, when you’re thinking about FTP, here’s the power, you can hit for five seconds, this high intensity, energy is completely different. It’s a what’s called a capacity. So if you want to get really formal scientists, we refer to it as the area under the curve. The simpler way to think of this is, it’s a bucket, you have this bucket filled with energy that you can use when you’re going above that critical power above that threshold. So remember, critical power threshold is what you can sustain. So whenever you’re above it, you can’t sustain that. So now you’re you’re essentially taking that bucket of energy, tipping it over and starting to pour that energy out. And the point of failure, as you said that the point where this MPa meets up with the whatever power you’re at, is the point where that bucket is empty. So you’re slowly draining it out, that means MPa is dropping. And once the buckets empty, you’ve got nothing more, you’re all you can do is now ride at or below threshold. Is that is that a good way to describe it?
Not exactly. And in fact, I think the discrepancy that we have with the what, what you’ll see written in scientific literature, is that the scientific literature explains it the way you just explained it. Once your reach your point failure, then your available capacity is gone. You’re you’re here, you have no available capacity left. That’s not what we’re seeing. Okay, what we see is that you may have capacity left, you can’t draw down on that capacity, because you’re limited by your MPa. So MPa. So for example, if I reach my MPa at 500 watts, let’s say that is my moment of failure. It doesn’t mean I’m having nothing West, it means that I just can’t hold 500 watts, I might be able to work 450. Right. So I can still drive down, I just can’t drive down at 500 watts, because that’s my NPA. So that’s the distinction. And so when you look at it from that perspective, and you start to map it in NPA, and map the relationship, then we can start to discover these points of failure much more accurately, then what, what you currently can do with the existing models. And in many ways, what you’re describing is, is the essence of why ours works and the other existing models don’t, is that we don’t really see it as being a capacity. It’s much more dynamic in that respect, and how much you can draw upon is limited by by your MPa and in the end.
Trevor Connor 28:30
I do think it’s really important that the listeners understand that this high intensity energy isn’t a number that it’s a capacity. Whenever I hear capacity, I always like to use a bucket analogy. So the one question I have for you is when I revised it to basically say, MPa is at its at its peak when the buckets full as you start to drain the bucket essentially MPa is coming down.
That’s exactly what’s happening. As bucket gets depleted. An MPa starts to come down
Chris Case 29:00
to me. And this might be something that is hard for me to explain. But you know, you’ve got your your threshold power, and we equate that in our minds to a sustainable power for 60 minutes, and then you’ve got peak power, which is the power you can do it put out for one second or five seconds. But aren’t there like an infinite number of, quote, thresholds along that continuum, you’ve got a 20 minute sustainable power, you’ve got a five minute sustainable power, you’ve got a one minute sustainable power. And as how does that relate to this, this concept? It seems to me like if you’re putting out 500 watts next to Peter Sagan, and then he keeps going and you’ve reached that point because you’ve been sitting at 500 watts for three minutes and that’s all you that’s, that’s your sustainable power for that length of time. Then you have to drop back and you slowly drop Back to 450, then maybe it’s down to 400. And then maybe you’re down to 300.
No. And that’s, that’s exactly right. So one thing you have to, I should explain is that these efforts to failure that you’re describing kind of like, how long can I? How hard can I go for one minute? How far can I go for three minutes? The typical things you would do to fill in your way we call a power duration curve, right? This is how things are typically done today, people are measured for, you know, their 20 minute power, so to say, how much power can you sustain for 20 minutes, you start you work your you know, you do your 20 minute test, and then you assume that at the end of the 20 minutes, you cannot no longer can sustain that power, and that becomes your highest winning power. That’s the way things are kind of managed today. With MPa terms, those are simply special cases of how we would apply MPa that’s, that’s when MPa when we calculate MPa is being well, we’re going to hold a fixed wattage for a specific period of time. And where we are, we’re going to hold a fixed wattage until failure until we cannot sustain that wattage any longer. And when we map out MPa when we look at how MPa is derived, and we we calculate those across all these different durations, then MPa gives you a power curve. In fact, this kind of, you know, eerie in terms of how well here is not the right word. It’s quite remarkable how well the MPA derivation would provide a power curve and give you how much power you can sustain for one minute in power you can sustain for five minutes. And what’s really unique about that is that even though you may have never done five minute effort, or a one minute effort, that the calculation will give you our value, it’ll tell you how much power you can sustain for one minute, even if you’ve never ever done it before. And what we’re finding is that a lot of our users are quite surprised by some of these numbers. And in fact, find them quite motivational in the sense that they believe now that they can sustain those numbers. And in reality, oftentimes they can. So what we’re seeing that the model is helping them helping our athletes understand what they’re capable of. And because it’s giving them a target that they can sustain. And then they can realize these numbers. And when they actually go out and do these tests, they do these tests. So so I was saying, aka, derive the information that you would typically use in a power curve. But that’s not all it’s doing is giving you interactively how much power you can generate any given second. And that would apply whether you’re riding side by side with Peters again, and you’re getting all this variable work and eventually go and leave leads to failure, or whether you’re doing a 20 minute test, or a five minute test or an eight minute test, any kind of test, the MPA will give you a prediction of how much you can sustain for that given for a given duration.
Trevor Connor 33:07
I found that fascinating because you had this concept of high intensity energy, this capacity that we had, we have a certain capacity to to do work above our sustainable power. And you also came up with this idea or have found in the software, this, there’s a certain power that we can sustain. So like I said, you came up with your own terminology for it. But those are essentially what what Hill came up with a long time ago what he called critical power back then it was critical speed because nobody had power meters. And also what’s been in the research for a long time this concept of lat prime, which is this same thing, this this certain capacity for work above your critical power. So I found it fascinating, even though you had never read these concepts. You found them in the data without any bias.
Right? Well, it’s not like I went in this completely unbiased or completely unknowing of any existing physiology, I did a lot of research, the best that I could do and interpreted in the best in the best ways that I could. And you know, some of those concepts, for example, like critical power, I kind of saw it understood what it meant. And I tried to interpret how that would potentially work within the data. And so I had had some ideas, but how fatigue worked, how how fatigue impacted the models that I was working with, how it manifested in the data wasn’t all that wasn’t clear, and there was really wasn’t very, very much information on it. And the information that I did find didn’t really work all that well either. So there was there were some models out there but they didn’t I didn’t find they were working for what what I was trying to accomplish. And at the time, the model was really wasn’t the Model T i was modeling heartbreak connect you know, to be frank, I was looking at how how heart rate was affected from from exercise from power data from cadence data. And so I created this model of heart rate, power and cadence. What was interesting when you model heart rate is that I was getting I see the model was very effective modeling heart rate, under under a number of different conditions, where the model sort of failed, was where the athlete was under fatigue, was wondering why and what aspects, why did it not work, when the when the when the was under fatigue, what I was noticing, in fact, was that heart rate actually slowed in this response under fatigue, which is kind of interesting when you think about how heart rate variability works, in some ways where there’s less variability under stress, you can almost argue and see the similar analog under fatigue, heart rate tends to slow its response to exercise. And so I was seeing this in the data, and I couldn’t really understand why that was happening. And so when I look for various new information in data streams to kind of explain this, and the various parameters that I had, within my model, I tried numerous different things, you know, was your is your resting heart rate changing, or some of the time constants changing for your kinetics are, you know, are the various other aspects within our model changing. And what I found was that we had one parameter called p max, which is your maximum power. And I tried to play with this, to see might that be affected during fatigue. And I try one model, and I’m surprised that it worked well, then I came up with a new model and tested it. And it was combination of this high intensity energy and how it kind of varied over the course of a particular ride. And when I model it a certain way, all of a sudden, this HR kinetics model, Christmas lights turned on, it was just an astonishing fit to the data. And I kind of knew at that point that this new formulation that really showed that, you know, your p max, your maximum power was affected by this T. And I had a way of calculating that, that somehow this was, this was it.
Chris Case 37:20
Today’s episode of fast Talk is brought to you by whoop performance tool that is changing the way people track their fitness and optimize their training. Whoo provides a wrist worn heartrate monitor that pairs to their app that provides analytics and insights on recovery, strain and sleep. know when your body is recovering or when it needs rest by getting to know your nervous system through heart rate variability, and quality of sleep. Automatically track workouts and get strange scores that let you know how strenuous training was on your body. And see even more data like average heart rate, Max heart rate, calories burned, get optimal sleep times based on how strenuous your day was, and track sleep performance with insight into your sleep cycles and stages of sleep, sleep quality, and sleep consistency. I can tell you by having worn myself that it provides fascinating data, and can optimize the way you train, recover and perform. And the sleep stuff is incredible. Oop has provided an offer for Fast Talk listeners to get 15% off their purchase with the code Fast Talk, just go to whoop.com that’s w h o o p.com. And use the code FSTTLK at checkout to save 15% and optimize the way you train.
Trevor Connor 38:37
To tell you the truth, like I found your MPAA fascinating. But what made me look at your software and go boy, I need to get some of my athletes on this and look at some of their files is you can see the different natures of athletes with your your MPa. So to give an example, I’m a roller. So I’ve got a big threshold. But I have a very, very small capacity, that high intensity energy, I don’t have a ton of it. So I can sit there and sustain a very high power. But if you asked me to go above that power, I’m very quickly going to get to failure. Because I just don’t have a lot in the bucket to to use. You might have somebody else who’s got a lower threshold than me. But they’re this big anaerobic animal. And they’ve got a huge capacity of high intensity energy. And you might find that the two of us can be competitive with one another because well that other athlete doesn’t have the same threshold as me. They have a ton of high intensity energy to draw on before they hit failure. And so you might see us riding by side by side, both of us with our tongues hanging out. But how we’re producing that power is different. And it also means how we embrace one another would be different. His best approach is I know Trevor’s threshold is 340. So I’m just going to start attacking him at 400. Because he’s going to drain that high intensity energy really quick and blow up where my approach is, I know his thresholds 300 minus 340. So I’m going to try to keep a steady for a long time at 340 until he drains his bucket, I love that you
can look at those variables and an athlete and a See, here’s what’s different about them, here’s how they’re producing the energy. So here’s how they should race differently. But it also affects how they train is. So Armando, please take it from there. But is that a good way of describing how you can look at these variables and see the difference in the athletes will precisely and this concept of how much power you have above your special really plays into how how your what your strategies are, during during racing and how you need to be training as well. So certain types of racism are more conducive to those that have greater capacity, or so when you have greater capacity, your ability to hold, let’s say, one to four, five minute power might be greater with a greater capacity than someone with a with a with a small capacity or with a higher threshold. So if the race really depends upon these kinds of tactics, where you really need to produce a lot of power over a short period of time to create the gap, and to be able to kind of sustain that gap for a winning effort, then you want to be training that and you want to be able to improve that capacity, because that’s what the the race really depends on. And as, as well as those that have higher capacity are going to be more predisposed to winning these races. Because they have they have those qualities in their in their ability to race, the three numbers and govern, we govern as your MPa in your in your overall fitness really dictate the type of races you’re going to be most successful in, and also dictate kinds of training that you may want to do in preparation for those races.
Trevor Connor 41:59
So full disclosure here, Armando and I are actually members of the same cycling Club, which kind of surprised me, because we’ve been talking for a bit, he showed me a file, and I looked at it went, boy, that looks familiar. And then I realized, hey, that’s, that’s one of the training races that we do in Toronto. And when we got to talk in and discovered that we were both members of this morning glory cycling club, and you might go how to how do you be members of the same club and not know it? Well, there’s 1600 members in the club. So not everybody immediately knows one another. But I bring this up, because these training races are very unique, we go to a short circuit in Toronto. And basically, we sought out the the couple climbs that we have that are usually kind of one to two minutes. And the way we raise them is you do this loop, you hit the climb, and then it’s just everybody going all out to try to crack one another. So this whole idea of hitting those moments of failure. That’s that’s what our racing is all about. And I did take some of those races, put them into our mando software. And sure enough, you could see it a couple times on the climb. That software said, here’s a moment of failure, here’s where you hit your max. But also think, again, I can use these training races is a good example of what you’re talking about where when I’m on good legs, and I show up to that race, my way of going up that climb as I know everybody else is going at their absolute max. So often when they get to the top, they’ve got nothing more to give, because they’ve hit that point where as you said, the moment of failure is where your actual power and your your MPa, your maximal power available are the same, meaning you can’t go any harder. If I have good legs, what I do is I go up that climb about 90%, so that my MPa and my actual power never meet each other. And when I get to the top of that climb, everybody else has nothing more to give, I have a little more to give not a lot, but a little more to give. And I hit it hard coming over the top. And that’s where you can drop everybody, and you talk to any top Pro, they say that’s really how you race, it’s about making sure you have that little more in the tank, you have your MPa is a little higher than where you’re at. So that when everybody else is out there limit, you can go a little bit harder,
you know, some of us aren’t blessed the same level of fitness and capabilities as someone else. And so that really does highlight, you know, the various tactics that can be used in racing, you know, some people are simply weaker than others. Others may have different strengths and weaknesses. And they may find themselves at a point of failure in one given situation. Whereas they wouldn’t be in a point of failure in other given situation because their their how they respond to fatigue might be slightly different than someone else. So I think those kind of defenses often dictate what kind of tactics and strategies you would use in racing.
Trevor Connor 44:48
So to give a good example of this, and this is where I was saying I looked at your software and said boy, I need to get my athletes on this because it’s really going to tell me a lot about how to train them. I’m going to give you an example of an athlete, I coach and myself. And so I was quite literal about myself, I’m a roller. So high threshold power, my bucket is tight, my hike, high and tensity energy, I don’t have any, I have another athlete, he and I, we did a 20 minute time trial, we’re actually going to put out about the same wattage, but his threshold is lower than mine, he just has a lot of high intensity energy. So if I gave both of us the same interval, so I love to do these four by eight minute intervals with two minute recoveries. But let’s say I gave it to both of us at our 20 minute power. If you looked at mine, I’m doing those intervals at my threshold. And in your software, and I quite literally looked at this in your software, you’re not seeing any impact on my MPa, it’s not coming down at all. So I’m not tapping into any sort of fatiguing, essentially any really fatiguing work for me. So those might not actually be good intervals for me to build top end power. My athlete on the other hand, if I gave him those same four by eight minute intervals at that same power, he’s above threshold, so you’re gonna see his MPa line during those intervals really come down, because he’s tapping into that high intensity energy. So those intervals are going to have a very different impact on him than they’re going to have on me. Even though if we both went out and did a 20 minute test, we would put out the exact same wattage,
right, and I think this is really important to know, because you know, there’s a focus on training your FTP and training by your FTP. And when you start to compare individuals, you start to lose the idea that there’s other aspects of their fitness that may need to be trained, or may dictate how one athlete is going to do perform a interval workout compared to another. So you just can’t look at FTP alone, to determine how to prescribe training and how the how that training is going to impact them, you start at you, you need to add in these other variables, their high intensity, energy and their peak power. Because these the intervals that you do, the training that you do are going to impact those values as well, depending upon the types of intervals, how long you hold them. So we see that these other variables are impacted with your with your training, and can can gain improvement through training, and then can then be kind of optimized for the various event that you’re training towards. So when you have two athletes, like you just described, Trevor, they both may be doing the same intervals. But they’re, they’re going to be gaining benefit from those intervals in different ways. Someone with a greater high intensity energy capacity is going to see greater benefit to their high intensity energy system, because they’re going to rely on that more to perform those intervals. Whereas for you, you may rely more on your threshold power. So that interval is going to provide more benefit to your threshold power. And the end, because you’re relying on that more. So because the training that you do is really using these three systems, you can then regulate or modulate how much of these three systems are going to be trained, are going to be affected by your training. And that’s really what you’re going to be looking towards in terms of optimizing that training. So Trevor, we know we have, you know, these two individuals that you were just describing, in terms of the differences they have between their high intensity energy, one may have a larger high intensity energy, a lower threshold, and another may have a smaller high intensity energy with a higher threshold power. So how that manifests in their training is that you may prescribe the same interval targets. But because one relies more on high intensity energy in comparison to the other, they’re going to see more impact to your high intensity energy system, more value from that training to that system, then then you would and that’s because that the the training doesn’t isn’t always just about their FTP, we have these other variables involved. And that’s something that we can track and manage within the software to help you understand how much fat your training is going to have on each individual system.
Chris Case 49:22
So it sounds like you’re describing Me and you, Trevor, you are the guy that can sit at 340 watts forever. I am the guy that knows that and will attack and put it put in those surges you were thinking of exactly.
Trevor Connor 49:38
I think it was Chris and I go do an hour climb. I try to set a tempo where I know over time I’m going to crack them or Chris’s strategy is no I’m just going to go really hard for five minutes of drop Trevor Yeah, and then go stand on a cliff and take catches me because I find that really funny.
Chris Case 49:55
But But the thing I was going to mention is that we we tease some This out when we did our, our climbing time trials, we saw some of this and we actually, you did the analysis. But these are data into these heat maps, and saw that you were very steady. And I was going above and coming back to threshold above threshold coming back. And it speaks to this very issue. So, so people out there listening that want a bit more practical information on some of this, go back and listen to our podcast on the new science of climbing. Not sure which episode number that is. But it we did get into a discussion about a lot of these things. Interestingly, that we were sort of coming to those conclusions without having a system and analysis of data to show this,
Trevor Connor 50:47
that then actually brings us to a really good question for you. Armando is Chris and I saw this, but we are also doing this article with one of the best labs in the country. So we were working with cu sports going in and getting all you know, we did lactate test, we did vo two max test, we had Ryan sitting there on the climb, taking our lactate at the start and the finish. These are not things that people are going to be doing with their training. But it sounds like you’re saying you can find this in the software. And you can actually find this just by the the normal process of doing your interval work and go into doing training races and going and doing actual races. So that’s one of the questions we wanted to ask you is, do you feel this is powerful enough to replace testing, or to give you a good if you don’t have the ability to go into a lab and get tested to give you something pretty close to it?
Well, we’re seeing that happened time and time again, with the users on our system. And I think that’s the draw that we’re seeing people who are who are coming to exert and trying it and using it, I think that what you’re just describing is really what it boils down to is being the benefit is that we can track your improvements with greater frequency across three dimensions, and without without having to do any testing. So when you when you think of it in those terms you’re seeing, you can see, you know, in plain sight, we use a software that your variables, these three signature parameters are either increasing or decreasing. And you can see when they go up and down each time you reach your point of failure during one of your activities. We describe those points of failure, we call them fitness breakthroughs, right? And basically, what happens is, you’re at some point in your ride, you reach your maximum MPa. And the software says, well, there we have that piece of information, what was your signature at that time, and we record that and maintain that for you. And then we can trend, we can see how your training is impacting these numbers as they go up and down. So yes, you know, you don’t necessarily need to go in and do the same number of tests or the same type of tests, you can track and see the progress that you’re making with your training directly in the software, as it discovers these points of failure determines what the signature was for these activities, and plots them out for you for you to see.
Trevor Connor 53:27
And I think that’s a really powerful part of your software, which is at any given time your the software has a signature for you. It says your peak powers x your high intensity energy is why and your threshold is set. And we’re both Canadians here. So Christina z, z Zed. Armando, you want to chip in two against one, right? So what is neat is when you hit these moments of failure, if your profile is no longer accurate, so you let’s say you’ve been training and you’ve gotten fitter. So that means the profile it has for you is outdated. So when you hit that moment of failure, what the software is going to see is Hey, your MPa just dropped below your power at that given moment. That’s not possible. So now I need to recalculate your signature. And then it’s quite sophisticated that it’s going to try all the different variables to get the MPA to match up with your power at the time. So it might say I need to adjust all three numbers. Or I might say no your peak power still just fine where it’s at. But what we’re seeing is your threshold power has gone up so it might just adjust one variable, but it’s going to then find the best profile for you to get the at that moment of failure the MPA to match the power which I think is really neat, very sophisticated way to do it. You said it seems to match up pretty well with real data. And it doesn’t require to go and do these very sophisticated tests to get into a lap.
Chris Case 55:00
I was just going to jump in and say it’s going in one direction, does it also go in the opposite direction as you become less fit? Absolutely. So
so here’s, you know, what you’re describing covers exactly what the software will do, it will look for these moments of failure and points of failure in your data, and then determine will what would have been the three signature parameters that would have explained that particular point of failure. So the software will do that for you. And it will do that it’ll also discover if, you know, maybe your numbers haven’t gone up, maybe you got really close, and you weren’t able to break through the software, we’ll discover those as well. And we call those near breakthroughs, or a friend of mine coined the phrase a fake through, and he circles in circles on your chart, and bases, and you see your numbers go down, and everybody gets all upset, you know, because they’ve been training, where have you and you’re seeing the numbers go down and go, Why did my threshold go down. And it’s because you know, the software is seeing this and is presenting this information to you. And that can happen, you may have various things that may impact your ability to reach your best at a given point in time. Maybe it’s just, you know, fatigue from training could be other things, it could be that you just didn’t go as hard as you absolutely could have on that get at that given moment. So there could be a number of reasons why you had this near breakthrough, we the software will track those and map those for you. But what’s really important to note here is that the software also can predict what these numbers will be. So this is sort of the direction that we software, and we said, well, yes, we can discover what your numbers were on a given date. But how can we how can we determine how you got there. And you’ll see this in the data, when you use it, you will see for example, that your training loads have gone up for the three signature parameters, you’ll see individual training loads go up, meaning that you’ve been training more and more, but you haven’t had a breakthrough in a while. And what will happen, very predictive predictably on many, many occasions, is that when you do get the breakthrough, it will have been what the software had predicted that you would you would be at at that given point in time. So in other words, your training, your training, your training, you haven’t had a breakthrough. But you know, there’s one there, and the software will say we’re expecting this breakthrough to be, you know, you’re making your special go up by 10 watts, for example, you get your breakthrough. And lo and behold, your threshold will go up to roughly around 10 watts. So that’s the other side of this is that the software is is mapping and tracking how your training is affecting your fitness signature parameters. And then using that information to help you train
Trevor Connor 57:54
we did an episode a long time ago, where we talked about the the stages of data are the stages of software. And I believe that was when we had hunter Allen on the show. And he talked about the different revolutions. And we are you’re really getting into that concept of very predictive modeling where it’s not just analyzing your data and saying, Here’s where you’re at. But now you can go into the software and say, if I train this way, what happens if I want to raise my arm and vice versa, if you say I want to get my threshold power ups, my high intensity energy is great. The software can give suggestions on here’s what you need to be doing in order to change this particular variable.
And you know, going back to your original comment, Trevor about how we’re using the data to kind of inform these decisions in terms of how we’re making these predictions. We’re not inserting any kind of understanding of how your body generates adaptations. So we’re not we’re not modeling physiology of adaptations. We’re simply looking historically, at your, at your data in the past, and recognizing patterns in your historical data that said, Oh, when your training load was at 60, we saw your special was at this value. So we create that mapping between the training that you had done in the past, and all your fitness breakthroughs, all your fitness signature changes, we map those changes to what you had done in the past. So the software does that. under the covers, it creates that relationship and understands how your training is impacting your fitness. And then in planning your training, it uses that information to plan out your training. So then you can see if I do this amount of training and I increase my training loads by certain amounts. I can then anticipate and predict that might my my signature my threshold my feet power, height, this energy are going to be affected in the same way that they were in fact they were affected in the past.
Trevor Connor 59:57
exert finds a rider’s profile by how due for moments of failure, and a writer’s workouts and races, for those of us in the physiology world can be a little uncomfortable using something so unstructured over controlled lab testing. But interestingly, when we talk to physiologist pallisa data, who owns power watts and coaches some of the best in the world, he said that he also prefers on the road testing and created a competitive environment to get those maximal moments. Can you get good numbers out on the road? That can compare to lab testing? Or is there just no way to compare to lab tests? And so as a physiologist, What’s your feeling on this? What’s your opinion?
You know, what it depends on the lab, it depends on the lab testing that you’re doing. Obviously, the more realistic laboratory testing is to what they’re going to encounter in the real world, the closer you will approximate, and the better, you’ll be able to make some some estimates as to the capacity of the rider outside, but there’s so many elements in bike racing, not the least of which is you know, just strategical initiatives or terrain changes and, and and the duration of the events that are really difficult to to be able to say because you score a certain amount on a particular laboratory test, call it a vo two max or lactate threshold test or, you know, aerobic threshold, whatever you want to evaluate on a rider. It’s really tough to make big conclusions from that I think what you can do with laboratory testing, is you can get a sense, kind of like as a barometer to what the opportunity may be. And then you need, it’s kind of like, okay, we have a diamond that’s stuck inside this rock, the laboratory test will tell you that there’s a diamond in there. But you still have to carve away the rock to get to that diamond. I don’t know if that’s a good analogy. But that’s kind of how I think of it.
Trevor Connor 1:01:47
So you’re almost saying that you get good numbers in the lab, it tells you a lot about the athlete physiologically, but that doesn’t mean they can translate it into on the road performance, you’re actually saying there’s a real value to testing on the road that you couldn’t get from the lab. So you’re flipping this around?
Absolutely. Yeah, there’s huge value. In fact, I do a lot of testing on the road, you know, I mean, I test where the athlete is tested. And the other thing I do is I whenever I bring athletes into my center, I actually test them collectively. So I’ll line up for national teamers or for elite world class racers, and I will actually make them perform a particular test. For example, I have one that I call an anaerobic repeatability test where we, they ride around bikes, they’re on rollers with a cage around the roller. And they’re all lined up in front of me. And I put the numbers on the board and they start off two minutes on two minutes off. I measure lactate after the minute recover at two minutes recovery into the halfway of that two minute recovery, I measure lactate and the each start at the same time. And they all start at five watts per kilo. And they all do two minutes on two minutes off five watts per kilo, two minutes on two minutes off 5.5 watts per kilo two minutes on two minutes off six watts per kilo and they keep climbing the ladder climbing the ladder. So what does that do? First of all, it measures repeatability. Which by the way is one of the single biggest indicators of performance in a bicycle race. Doesn’t matter what your vo two Max is, if you can not repeat anaerobic efforts when the going gets tough and things get strung out, you’re not going to win a lot of bike races. So we introduced the concept of repeatability into the actual laboratory tests where we measure lactate and power output and heart rate and perceived exertion. And we just make it so that it’s a competitive event. Because in a laboratory, if you have one guy and I don’t know when Elodie or governor on a treadmill test or whatever you want to test them on, there’s really nothing to stimulate that athlete other than their own internal willingness to do well, which probably 5% less than you would get if you pitted them against each other. And so I do a lot of that where I bring athletes in and I test them collectively. And we get a lot more interesting data. And we get a lot more out of the athlete from that. It’s Last Man Standing testing, I
Chris Case 1:04:05
call it Wow. Yeah, sounds painful and good idea. It’s It’s It’s so true that, you know, everybody pushes themselves harder when they’re next to people that are also pushing themselves harder.
Trevor Connor 1:04:18
So what sort of testing would you do out in the road? Do you have any favorite tests that you do with athletes.
So usually what I do is I have a series of roads that I that I take these guys on that I’ve been doing for a long, long time. And essentially what I’ll do is I’ll measure different things, you know, so I’ll have a steady state effort over a three hour ride and then they come in and they have to hold a minimum of a certain normalized power, call it 250 watts normalized power, or 4.5 watts per kilo and normalized power. And then they’ll come in and they have to actually punch a hill. Sometimes it’s a one minute Hill, sometimes it’s a 30 minute, a 32nd Hill, sometimes it’s a fifth minute Hill. But that’s generally the three areas that I look at, and it basically hammering their way up there as fast as they can. So it’s essentially like a full capacity effort for the duration of the climb that they choose. And that’s just for GC type, climber based racers for sprinters and coolers, it’s some different stuff. But for a guy like Mike, that’s essentially doing is pretty simple. It’s not, it’s not that complicated to do that, it’s essentially just a higher intensity level of training, where we can see if we can push up the boundaries of their watts per kilo and their vam. You know, that’s what we’re trying to do, essentially, to some degree, it’s impacted by weather. So you don’t have the same environmental controls as you would in a laboratory. I’ve done a ton of testing in the laboratory at McGill here, where I live way back when I was a graduate student, but not anymore. I much prefer getting athletes out there and having them, do it do field testing. And I almost never measure, measure any physiological variables, I almost never put any vo to, you know, portal view to met cards on them or do lactate testing out in the field. Too many variables impact it. And it’s very hard to draw correlation between, you know, that an improvement or performance. So I essentially just measure, you know, power, their cadence, their perceived exertion and their times for different segments that we that we like to test on here.
Chris Case 1:06:22
Let’s get back to the show. It sounds to me like you’re proud and happy of this software, and rightfully so I’m curious to know, what criticisms Do you hear about it? And or what do you think still needs improvement in this system?
Trevor Connor 1:07:57
And I think I’m going to add to that some of what you’re seeing is a change in how we’re viewing training that is, by nature going to get more complex. I think 10 years ago, it was really FTP, FTP, FTP, how do you raise that one number? So we’ve now had Neil Henderson come in here and say, No, it’s not just FTP. And he actually had four variables that you need to look at and that you need to train. We’ve had Subash and Weber come in here and say it says balance between your vo two Max and your Vla Max and different training is going to have different impacts. I’m the jerk that’s sitting there saying, Well, what about your lower threshold that 85% of lactate threshold? Because that’s an important variable, too. And that was really Dr. nugo, sambal, on who’s been banging on that drum. So what we’re seeing is this, we’re realizing and training, there are a lot of different systems that we need, and we need to train all of them. And that makes, it just makes training more complex. But the if you take the time to learn this, if you use these various tools to to find these different aspects of your strength and figure out how to train them. Yeah, it’s tough. Yeah, it’s complex, you might need a coach to help you out. But it is going to make you a better cyclist than just saying my sole goal is to just raise my FTP.
Chris Case 1:09:14
So it sounds like this concept of MPa is pretty exciting. And it and we’ve talked about the the training applications and And what about the the racing application? What about seeing this available power in real time? Is that is that possible? And how does that work?
Well, Thanks, Chris. Yes, that’s a great question. And it’s a topic that we have a lot of our customers a lot of our athletes are very, very keen on is you know, seeing their MPa while they’re writing. So we can do that today. We have a garment app that will show you your MPa on your Garmin device while you’re writing. We have a way in which we can show your MPa on screen on on A web browser for example. And we have many users that are using that wonder racing on swift as an example. So they’re able to kind of see their NPA on screen. While they’re writing is with some, some folks are actually gone through the trouble of recording their NPA during races, while you’re watching them on Swift. And so there’s been some of that happening. From you know, members of the kiss racing team, for example, I think the applications for NPA, both in terms of informing you as an athlete interactively, so you have an understanding of where you are and comes with it, certainly you can feel it, you know, how it feels when you’re tired, and when you don’t have the power. But when you get reinforcement or more clarification on what that means, or what you can really do at a given moment in time with an MPa, datafield. That’s really great in terms of helping you understand what you need to do tactically during a race. So we’re seeing a lot of interest. It’s very, very popular for people, our users to use our MTA datafield on their Garmin and using them during Wisp racing. But there’s also the aspect of a spectator, right? What What will a spectator get out of watching somebody then PA,
Trevor Connor 1:11:13
and my only issue with your app is with my horrible high intensity energy, I gave it a try. And I went about 10 watts over threshold and it just flashed, boy, you’re screwed.
Chris Case 1:11:23
Stop now. Well, it sounds exciting to me, I hate to play devil’s advocate. But if this creates even more controlled racing at the World Tour level, and everybody’s staring at their MPAA on their screens, and they won’t go one watt over. That might that might spell doom for TV broadcasts. I don’t know. I think you know, you know, that’s
one sentiment. So there’s two ways to look at this, right. So you look at the the aspect that we know, we want to bring racing back to, you know, no more power, just race by feel, you know, create some more drama than the alternative is rather than, you know, hide all that data is now to expose it and use that as part of the racing spectator experience. I think there’s a there’s something to be said for that. And I think it’s because, you know, when you’re looking at an athlete, you’re looking at a rider, you know, you don’t really know what’s happening to them, you announcer can maybe describe what’s happened and you get a perspective for it from what the announcers describing kind of suffering that the athlete going through. But you don’t really know what it is. When you have our information you have, you can now see it, you see it in their data, you can see how deep their they’ve gone. So you’re getting an appreciation for the capacity of the athlete and the suffering, they may be going through at a given time, and how they’re going to be able to play their own their own cards at a given moment, adds a new dimension, a new aspect to racing that we currently don’t have. And it would be really interesting to see how this could be used to perhaps even enhance the spectator experience, rather than detract from it.
Chris Case 1:13:03
It’s not unlike a Formula One racing, where you’ll see some of the data on screen while while they’re doing the in car camera footage of you’ll speed, how much braking, how much throttle, tech ometer, things like that. And MPa is, you know, in a way, it’s an equivalent to the TAC ometer, how close you are to that redline. So that could be exciting.
Exactly. And we certainly see it that way. If you ever watch, you know, the cars racing team, or some of the others now that are overlaying MPa on their races, you’re looking at it, you’re watching it, you’re watching how deep they’ve gone, and how much more they can go, you know, maybe I’m biased. And I’m more keen on that number than others. But I would imagine that, you know, wouldn’t be alone and kind of wanting to see what that number is for a given athlete in a given point in the race and appreciating the kind of efforts they’ve just put themselves through to get there. You know, I think I don’t think I’m alone in believing that that there’s a lot of really great value in being spectator when you’re watching them.
Chris Case 1:14:03
Okay, Armando, you’ve got it’s puts you on the clock, you’ve got one minute, I want you to try to encapsulate everything that we’ve talked about here, give the listeners few of the most important, take homes from our discussion today.
By analyzing your rise in your activities, looking for moments in those activities. When you reach a point failure when you have a maximal effort. These maximal effort, your point of failures mean that you’re trying to produce as much power as you can, if you had more power, you would have used it at that moment. So So these really describe the limits of your fitness and you want those limits to increase. You want them to increase with your training. We see these increases is happening across three dimensions, your threshold power, your high intensity energy Your key power, and you want those to go up with your training, and you want to use those most effectively in your racing. So exert is a platform that’s going to help you with that, it’s going to help you identify your three variables can help you improve them, going to help you understand how they need to be used in your particular racing. And it’s going to give you a visibility of who you are as an athlete that you’ve never ever had before. That’s really ultimately what I think is draws people to use our software. And that is you gain an understanding of who you are as an athlete, and you see it depicted in the software, whichever,
Chris Case 1:15:42
you got one minute, what do you think?
Trevor Connor 1:15:45
So my one minute is, first, what I appreciate about exerting The reason we got you on the show is there things about your software that I haven’t seen anywhere else information in the data that that is quite unique and quite interesting, and I think it has there as a real value. The second part of my my one minute here is to remember that exert if I training peaks, all the golden Cheetah, these are all tools. And you’ve heard, I’ll give you full credit, you said this on your website, there is a difference between fitness and performance. And what you don’t want to do is to the end of the year and say, well, I’ve popped in every single race I did, but why you should see my high intensity energy. Now. These are numbers, these are tools to help you with your training. And so my one suggestion is view it that way. Use it that way, don’t get caught up in the trap. If you start using exert or any of these other tools to say, I’m going to try to have a breakthrough workout every single time because I want to I want to change my numbers, I want to see those improvements. Instead approach it as I want to maximize my training, I want to make my training as effective as possible. And then periodically do a training race or do a workout where you try to get one of those breakthrough moments so that you can see where your numbers are at. I was experimented a little bit getting ready for this this podcast. And so I still did my proper training, trying to do it as effectively as possible. But one of my interval workouts a weeks ago where I was doing my four by eight minutes. I didn’t work out effectively. But when I got to that last eight minute, I said I want to I want to hit that point of failure. So I can go in ended up doing a 12 minute interval where I went well above threshold and I blew up and sure enough on on exert. You saw it gave me that breakthrough moment and gave me information about myself. And that was really valuable. I’m not going to do that every single workout. I’m just gonna do that periodically and otherwise use the tool to say, How can I make my interval work more effective? How can I make my training more effective?
Chris Case 1:17:50
Yeah, human beings, their engines are pretty complex. So I think this this is complicated, but it also should be pretty exciting to people. I think it’ll help them train better, it’ll help them race a lot better. I feel like there’s a there’s a chance that we’ll look back at a time when, and I’m not trying to criticize FTP. But the focus on that may at some point look pretty simplistic because it’s just this single number. And as we’ve heard in the last few conversations with with physiologists and engineers that are working on systems and software to analyze this stuff, it’s way more complicated than that. There’s a lot more nuance to it. There’s a lot of more more variables to it. And just like we we’ve heard 1000 times before everybody is so different. Everybody is individualized. You can individualize things so much more with systems that look at more than just one value. That was another episode of Fast Talk. As always, we love your feedback. Email us at Fast Talk@velonews.com Subscribe Fast Talk on iTunes, Stitcher, SoundCloud and Google Play. Be sure to leave us a rating and a comment. Become a fan of Fast Talk on email@example.com slash velonews and on firstname.lastname@example.org slash velonews. Fast talk is a joint production between velonews and Connor coaching. The thoughts and opinions expressed on fast doc are those of the individual for Trevor Connor. Armando was Traci Colby Pierce. I’m Chris case. Thanks for listening.