The Complexity of Training with Manuel Sola Arjona | KoopCast Episode 166

Trail and ultra runners, what is going on? What's happening? Welcome to another episode of the KoopCast. As always, I'm your humble host, Coach Jason Koop. And our podcast today is all about training complexity. And while this might seem like a benign topic, or maybe even an elementary topic, do not confuse complicated with complexity. Complicated systems, like a computer program or a search engine algorithm, are ones with many linear variables that we can eventually figure out through math and computation. Complex systems, on the other hand, which include the human body, are ones whose variables are nonlinear, and the relationships between cause and effect are much more spurious. So to help explain this further on the podcast today is Manuel Sola-Aroja, whose book, The Nature of Training, The Science of Complexity Applied to Endurance Training, attempts to add some clarity to this topic. What I want the listeners to come away with during this podcast is a greater appreciation of the cause-effects relationships with training and nutrition interventions on performance. Many times we want to say that this caused that. And that's something that I get into as a coach a lot. When I read research, we look at

a specific intervention and say, yeah, we can look at this and then this thing happens. But what I'm beginning to appreciate a whole lot more is that it is much more complicated than that one-to-one ratio. And if we zoom the lens out far out, we need to look at many variables in order to explain adaptation, particularly in endurance events. One final word before we start this podcast is that Manuel's native language is Spanish. It is not English. And his accent is quite thick. I hope you guys in the audience can appreciate that the courage that it takes for him to come on to this podcast and explain this very difficult topic in a secondary language. I think Manuel did a fabulous job with this. And the information that he has to convey is certainly valuable enough to warrant some extra focus from you, the listeners, whether you're listening to this on the trail, in the car, or just sitting there at your desk.

I hope you guys enjoy it. I enjoyed this podcast very much. And with that as a backdrop, I'm going to get right out of the way. Here is my conversation with Manuel Sola Aroja, all about the complexity of training. So Manuel, welcome to the podcast. I appreciate you. I appreciate you coming on board. I'm super interested in your work because I think it presents a very elegant blend of research and practice. And ironically enough, I got to translate a few of the chapters of your book that you've written. And the philosophies that are contained with it are very much in alignment with a lot of the practice that I use, even though it's across a completely different sport group. So I've been looking forward to this for a while. But before we kick into anything, and so the audience can get to know you just a little bit better. Can you give us a little bit of a brief background on just who you are and the types of athletes that you work with?

Okay. First of all, thank you for inviting me to your podcast. Well, I'm from Spain, from a small town in the mountains. I have competed in cycling from the age of 14 to the age of 25. And during this time, cycling has become my life purpose. First as a cyclist, and then now as a coach. I have lived a buy for cycling. When I was in training, I was reading about science, nutrition, materials, maybe I was too obsessive. And that's why I studied sport science at the University of Granada, later a master's degree in sport nutrition. Leaving competition, I began to focus on training cyclists. I mainly work with competitive cyclists, some professional guys under 23, but mostly veteran athletes. However, training then is not my main activity. Fundamentally, I dedicate myself to studying, reading and researching sports science and other topics. This is because I have a podcast in Spanish, which is called Ciclismo Evolutivo, where I already have almost 200 episodes and I share what I am learning and researching. Where I have been able to interview some of my references, such as Inigo Sanmigán,

Juan José Vadillo, Inigo Mujica, Natalia Balague, or Kilian Jornet. Last summer, I published my first book, The Nature of Training, The Science of Complexity Applied to Endurance Training. It is still only in Spanish. The book has been a great success and has been the most selling book on cycling and training categories on Amazon in Spain, of course, since the launch. This is not a book only about sports science, but about a new way to approach the health performance by the human as a complex adaptive system perspective. I am a person who likes to learn about different topics and not only about sports science. Last year, I have been learning about complexity, ecology, economy, physiology. Well, to say that.

And one of the reasons I wanted to bring you on the podcast is because you're from, also, I'll kind of say an era of coaches that is starting to more appreciate that we're training athletes that are more than a bioenergetic system. So I grew up in an era of coaches where we focus very much on the bioenergetics. Here's what's happening. Here's your lactate threshold. We want to train this system in order to improve this other system. And it seems like within the past, I don't know, maybe decade or so, they're becoming more and more practitioners in the space. And then you being one of them and a couple of our earlier podcast guests that you just mentioned, being some other ones that are starting to understand more of the socio-biological interplay between athletes.

So I want to know how you initially got involved to understand and to try to add some of this complexity to this socio-biological interplay to where we previously thought it might have been more of a bioenergetic proposition. How did you initially get involved in that? Okay. So my career as a cyclist first and foremost, as a coach, I have felt lost and even frustrated for not being able to find a pattern of sets, loads, or periodization that work better than the others. And as I was gaining experience, I realized that this pattern did not cease and stay. The pattern that I was observing did not make any sense with the theory. So I thought that learning how the body works to achieve maximum performance, which was the most important thing in the world for me at that time, was like putting a puzzle together. But the more I learned it, the closer I will be to finish it. But the reality is that the pieces did not fit.

The more I learned it, the more I learned it, the more I learned it, the more I learned it, the more I learned it. So I was getting very frustrated because I thought that I was the only one that had not finished this pattern. But talking to athletes of level and experience, I began to realize that this was not happening only to me. Some did not want to admit it, but the reality is that the majority of athletes and coaches did not even consider it. In no case, they did they question whether the things they made sense or not. They just followed what the canons dictated. Most of the things that have been done in sport training do not have evidence to support them and are done out of tradition or a phenomenon of part dependency where the trees don't let you see the forest. As I realized that no matter how hard I studied, I still did not have satisfactory answer to the main question of the training. And I did something by this. I began to read and become more interested in other disciplines that I like it. And I found that these same problems occurred in branches as different biology, ecology, economics, and that there was a branch of study that it did with the interrelationship between components. And that was to us.

What was the science of complexity? Well, and what you what you are describing completely mirrors mine and a lot of other coaches experiences out there where we prescribe certain parts of training and we expect them to have a certain effect. And when you when you start to analyze that over many athletes over long periods of time, you start to appreciate more and more that the effect from the intervention that you're applying has all of these complicated differences when within them, not only between individuals, but also with one individual over over many, many years.

And you only come to understand, you only come to understand, you only come to appreciate that. If you're really scrutinizing the data, if you're really looking at if you're really looking at the training effects year after year through through through a very through a very fine tooth comb. So what you're describing, you know, not only mine, but a lot of other coaches experience and it kind of gets to this root of the problem that humans are complex systems. And you've taken an attempt to describe what a complex system is, and I think that that's important for the listeners to know, like, what is a complex system and how is that different than just something being complicated? Okay, that would question. A complex system is a system formed by interconnected components of mind characteristics is that collective behavior emerges from this connection that cannot be inferred or predicted from the study of its parts separately.

Complex comes from the Latin word plexus, which means braided, intertwined. This refers to the relationship between the entire system, which make it work as an integrated and inseparable whole. It is very common that, as you say, to use the word complex and complicated interchangeability to describe systems that are made up of many parts. But this type of system are very different and the difference does not depend on the number of parts that make it up, but how they interact with each other. Okay, for example, there are systems like a rocket that are made up of a huge number of parts that do behavior is complicated.

Another system made up with very few parts such as a couple with a complex. For this reason, we can predict, for example, the position of the rocket during a space trip, but we cannot predict how our partner will feel if we buy a new bike. So the number of parts does not make the system more or less complex. The difference between them are not due to the number of components, but to the type of integration between them. When a car, for example, breaks a wheel, we either repair it or it doesn't work. The function of the motor is independent of the operation of the wheel. His pieces are always related in the same way. The same input causes the same output. It is predictable. He doesn't learn.

However, a complex system like the organism can continue to function despite the condition in one of its parts and do so with same success. The same function can be achieved involving different organic structure. For example, an amputated or injured people can generate compensation to continue performing the same action. And in turn, the same physiological structure and synergies can give risk to very different attacks. For example, the muscle not only adds to generate movement, but it is a hormonal signal. It adds as a protection and support for other organs. It influences metabolism and so on. For that, in complex system, the relationship between components varies over time and can gain or lose importance depending on the purpose and contents.

For example, model model. For example, model, much of the blood flow can go to the mask is free of exercising, but it will go to a later extent to the digestive system. If we have used eating a strong meal or to the skin, if what we need is thermoregulation. And the way that I've always tried to encapsulate it very simply or simplistically is it's the lack of the ability to predict what is going to happen from the output side of things. We can always control the inputs from an athletic context, run at this pace, cycle at this power output, do this many hours, this set of intervals and things like that. But the output of it, how that actually affects the individual is what leads to the complexity of things.

And the fact that we can't predict that as well, no matter how finely tuned we try to hone in those variables. I think that that encapsulates this difference between complexity and just simply being complicated. So let's try to get it kind of like down to what we call brass tacks. I don't know if there's a Spanish equivalent there, but into the reality of actually training an athlete, right? We mentioned that there's this disconnect between the input and the output. I'm going to do these workouts and I expected to have this output and it might not in fact have that output. How do you actually apply that knowledge to the training process, either in terms of how you prescribe things or how you actually evaluate what is going on?

How do you apply this theme of complexity to the actual training process? Well, after knowing that an organization, an athlete is a complex system and knowing all the properties that the complex system has, people usually think that we don't know anything or that it doesn't matter what we do because everything is uncertain and it's chaotic. And the message I would want to convey in the book is just the opposite. And then, with the basic science, everything is integrated and mediated by this relationship and side effects, we have to forget about looking for the perfect or ideal training because it doesn't exist.

And focus on getting the basis right, the important things only. I like to say that a well-designing training program is the one that flows by itself, the one that is easy to follow. if we are doing it right we will train hard when we are ready and slow down when we are tired i'm not saying of course that you never have to train tired or without deciding but as a general rule these days should be a minority and we will not do them knowing that they are part of the plan perception are an ancient mechanism that allows us to know the state of our body and what it needs we have to flee from the concept of training recipes the same training that makes you improve in one context can make you worse in a different one as natalia balague says athletes have to change the question what what do i what do i have to do by the question what do i have to take into account yeah at the level of methodology we must avoid a reductionism and focus more on what happened as a world as a whole traditionally training has been analyzed through isolated parameters lactate concentration squad strength fat percentage or of sleep and so on but this is these isolated parameters don't know how to determine the overall state of the group a drop in your blood last day

levels might mean that you are exercising with less effort or it might assume that you are oxidizing more fatty acids because you are more fatty you can be stronger in the squad and have less power on the bike or lower your fat percentage and at the same time lose performance no so it is not so much a question of working with parameter in isolation but of improving the whole through coordination between them in this aspect i am a lower of simplifying and going into what it is really important lower indicators that explain the state of recovery and internal load of the system as a whole such as perception and global performance indicators too such as power speed or times in controlled situations that indicated how the group the whole is a world being training is also seen as a non-linear process where the relationship between stimuli and response is lost in other words and increasing loads does not have to mean a proportional increase in performance but sometimes it can even be counterproductive i want to i want to point out two pieces for what you just went over the first piece is what you have done in the past or what an athlete what one athlete has done in the past is not necessarily going to be

predictive for how they are going to adapt in the future and we we see this a lot with coaches and athletes where it's like if it ain't broke don't fix it right that's the phrase we would use i did this in the past it worked i'm going to do it in the future and it's surefire going to work to work again because i have this pattern more commonly what we actually see in the coaching realm that would be an athlete scenario that i just went over more commonly what we see in the coaching realm is i did this with this athlete and then i'm going to do the same thing with that athlete or with another athlete in the future and and i've always viewed that as a coaching error partially because first off it it doesn't take into account the individualization of each particular athlete you need to apply a different type of stimulus but in addition to that it kind of falls afoul of this this this complexity phenomenon where what worked in the past even across the same athlete might not work the same in the future the other error that runs along kind of the same pathway is that of that that you mentioned to the very end is this non-linear relationship between the the the load or the training and the actual effect if i increase something by 10 it's going to be 10 harder or and or 10 more effective that relationship is very spurious as well and we also see sometimes there's a negative relationship between an increase in load or an increase in stimulus and the actual effect that the

uh that that the athlete receives or the adaptation that the athlete receives at the end of the day so i think that when the athletes are thinking about this at the end of the day you have to take those two things into consideration that you can't always rely on what has worked in the past it might be a good guidepost but you can't simply copy and paste that nor can you simply copy and paste and add 10 percent to it it because you don't know if that is going to be the same if that is going to be the same moving forward right that's uh a mistake that i have to do when i was cyclist i tried to to reach a ctr a certain level of ctr and then try to maintain it but what i feel is that i can't maintain it because i can't train as hard as i was training two three months ago and then when i was trying to train so much my performance was a degenerating but now i understand in that moment for me it was like what the hell if i am trying this the to do the same ctr why i am not in a good shape you need sometimes to make face to learn yeah and what manuel is uh referring to for the listeners

out there ctl is this chronic training load which is it's predominantly used in a i wouldn't say in a cycling context but across the people who use training peaks and all it is is a 42 day rolling weighted average of the mathematical training stress scores that are produced from the uh from from the workout files and that math is really not all that necessary but the effort is a novel one right and it's a it's one that i think a lot of coaches and athletes can appreciate we're trying to come up with a formula that will tell us how hard the session was we're trying to apply math to it based on threshold and duration and time at intensity and all of these other variables and say okay this workout is a hundred and this workout is 90 and the workout that is a hundred is about 10% harder than the workout that is at 90 or i guess the better way to put that is the workout at 90 is at 90 of the of the intent or 90 of the training stress as the workout at a hundred but in reality as you have experienced and now as every athlete has experienced who's now gone through that is is the reality is is is much different is that the the the stress or how difficult the actual workout is cannot be merely uh represented by by this by this mathematical calculation you can use it as a gauge of yeah okay this might be a little bit harder than the other one but to say that it's

exactly 10 harder to 10 easier would be an error because it's disregarding all of those other things that are affecting the athlete on the social side of things and on other areas of biology and complexity that we that the math can't essentially take into uh take into consideration you mentioned a way that the human has to integrate it all which is rating of perceived exertion and i'm ex i'm extremely curious to hear your thoughts on what how you view it and what is what is it dependent on so can you take the listeners through how you view an athlete's rating of perceived exertion and what that internal cue is dependent on okay this is a huge topic no so i am going to try to to resume but uh for listeners they need to know that perception of effort is the main feeling we experience about how hard is the exercise we do and how hard is to our body although it is not the only one that in the exercise we can feel a magnitude of perception and sensation pain first cold heat and very long etc but the perception of effort is capable of encompassing

all of these uh waiting them according to the importance they have at each moment to explain it easily i like to simplify the perception of effort as a kind of high capacity processor that can monitor in real time this stress data that affects the entire organism waiting then importance according to how much they affect at this moment and in relation also to the importance that this tax has for us and in addition this processor will have a machine learning ladder it leaves from a each performer so it's a machine learner right that's like really big right now it's literally a machine learning correct correct uh physiologically the perception of effort emerges from the non-linear interaction between the sensory dimension so is the physical mental effort in relation to our physical abilities the affective dimension which is the motivation and affectivity for the task and the cognitive dimension what we know as mentality or our capacity to build the effort and in turn these three dimensions are nested with an environment environment and attacks that are dynamic that are never the same it is interesting to note that fatigue and passive exception are dynamic because all these variables are continuously

related to each other for example it has been seen how free cyclists enjoy the activity more and lose less affectivity with fatigue or in addition they are able to tolerate more mental fatigue without losing performance lowering the pace can decrease the perception of effort if we do it freely but it can increase it if we lower it because we have been unable to keep up with our rivers and vice versa if we are able to withstand an opponent attack and we begin to feel that we are performing better than we thought or perception of effort might decrease even though the pace is higher due to the sudden increase in motivation as the perception of effort is the only indicator that is capable of integrating the global state of the organism with its demand and context signaling signaling signaling signaling signaling signaling signaling signaling signaling signaling that we want to provoke to the changing capacities of the elite.

The speed or the watts are not capable of taking into account if one day you have a sleep worse or it is hot or if you are sick. But the perception of effort can. And there is no evidence that watts or speed-wide intervals are superior to a structure or sensation-driven workouts when not turning around. When I use our sensation as a light to know the stress that we are generating to the organism. I was just reminded of a couple of arguments that I've had with people in the past about using rating of perceived exertion as a means to control intensity. And you kind of hit the nail or you kind of encapsulated these arguments really well.

And I think it's important to kind of recap this for the listeners. You know, you have been around long enough where you saw how the consumer adoption of the cycling power meter, it kind of revolutionized the sport in many ways. But it also opened up a lot of blind spots kind of like unintentionally. And that's with all due respect to the practitioners out there. And one of the areas that it did so in is how it forced the granularity of prescribing intensity kind of on the users because you had this tool that was so accurate and so easy to get a hold of.

We could prescribe things in these five watt increments, 10 watt increments, 15 watt increments and things like that. And a lot of the criticism around prescribing things based off of based off of perceived exertion is that you can trick it. Right. Just that you mentioned, if you like the intervals, you're going to run them faster or at a higher power output than you probably should based on some sort of physiological profile, just because you like them and your rating of perceived exertion is going to be less. You're probably running them at a slightly faster speed. And the opposite is also true. And we see this in the ultra running and community as well, where they're very intense adverse. They don't like doing things at very high intensities because they spend copious amounts of time running, running at low intensities.

And because they don't like doing things at a higher intensity, when they do do them, their rating of perceived exertion is probably higher compared to whatever pace or, you know, power output that they should actually be doing. And I've always looked at that as a good thing. The body is naturally calibrating what where you should be. And we're just using emotion, right? As the as a piece that can actually calibrate it. But the other pieces that you also mentioned, poor sleep, excessive fatigue, other life stressors that are going on that absolutely do influence your your perception of the actual effort. That's a good thing. That integration of all of those things with the actual raw physicality, the raw physical output that the athlete is going through, integrating all of those into a into the way that the athlete controls their effort is actually a good thing, because it's a representation of everything that is going on, not just the physiological bioenergetic output that a lot of the zone based systems are actually using today.

So actually use the argument kind of like the anti RPE arguments and almost flip it around as a good thing, because you want to incorporate that in order to make sure that you have the correct load or in order to try to get closer to the correct load of everything that that that is that is going on. So I like I said, I just really appreciate that that description of how RPE can be influenced and we can use that to our to our advantage. This whole conversation is kind of reminds me of one of the things that we try to do as coaches is we want to make sure our athletes are improving. Right. We apply training to them.

We hope they're better at the end of the day than they are at the beginning of the day. Once you kind of go through the entirety of the training cycle. But because the body is so is so complex, how can you measure the training process or improvements in the in the training process? Should we even be applying numbers to this in the traditional way that we demark personal records and your fastest 60 minute power output or your highest 60 minute power output or whatever? How can we actually measure the training process or improvements over time? Well, in a way we need to use the information or the data we have to know how the training is going.

So as I said previously, we can use LPE, positional effort to train. But also I like to use global indicators of the whole the whole organism is evolving to know if the training is working or not. So for example, for example, you can do tests of, for example, 20 minutes test on cycling. OK. All of them. And I think they are better than trying to measure isolated parameters as a state or P2 mass. But also there is a problem in the way that we think that the only thing that matters in the training is what we can measure.

It's very famous this quote of Kelvin, he says, but can't be measured, can't be improved. But the reality is that thing that can be measured are the exception, not the norm. How do we measure courage, justice, we sure despite this thing just because we can measure them. No, human beings are capable of perceiving the enormous complexity of nuance that this world triggered to emotion and perception. So if I try to transfer everything in training to a number in the world scale, I am losing information about enjoyment, about energy, pain, pleasure, purpose.

For this reason, a conversation is often much better than a piece of information. And of course, some power or speed data without knowing the perception of effort behind it are useless for almost nothing. So I like a quote that is from Donela Meadows that says, be careful not to confuse effort with results or you will end up with a system that is producing effort, not results. If your goal is to improve your critical power or your VO2 mask, you can end up generating training programs that optimize these parts of the set because of degrading performance.

A few days ago, a man came out of the news in Spain who went to the doctor worried because he is a small watch, she always said oh, her rates. It went viral. Many doctors commented that they had a patient like this. As you say later, we have to try to reconnect with our body and learn to listen to ourselves. Our body has a goal to inform and add in response to two different needs and indicated the most most adaptive behavior at all times with thirst, pain, effort or cold. So it's a serious mistake that we are leaving this ancestral mechanism. We are trying to inhibit them by stimulation, for example, with caffeine or with pankillers.

But here's the thing, though. It entertained me for just a second. Athletes want to know, are they better, worse or the same this year compared to last year? They want some sort of stoplight style indicator system, right? Green for you're better, yellow for you're the same, red for you're the worse. And there's been a tremendous amount of effort amongst physiologists and coaches and even the device manufacturers, right? The wrist watches and the power meters and things like that to try to tease out this. Are you better? Are you worse? Or are you the same? I know that we want to take a complicated, integrated approach to it.

But at the end of the day, the athlete wants a relatively simple answer. Can we or should we try to boil it down to one of those simple answers? Or is it just one of those things where we have to be okay with the unknown that you don't know if you're better, worse or the same? That's kind of what the athletes like want to get out of it. Like, can we, can we have a realistic way to determine that? Or is it so complicated that we have to leave it up to faith, which is what a lot of athletes are not going to want to do, right? Yeah, no, the athletes need to learn to dance with uncertainty because they want, of course, I know they want you to listen to this.

You want a exact number of how fit you are, but there is no this number because as you can see in any professional athlete, you can race this week and have one performance. And next week, seven days from now, you have a much higher or much lower performance. So you need to understand that you have no performance level because our performance or fit state is dynamic. It changes because everything that surrounds us is changing all the time. I think that you have to live with some degree of uncertainty is something that everybody can take to heart.

And in the cycling world, I know that there's been a, there's always been a bigger and bigger push to make things more certain, right? We know if you want to win the Tour de France, you have to have X watts per kilo, right? You want that, you kind of like want that level of certainty kind of coming into the race. But I think that once again, the audience for this podcast is predominantly going to be trail and ultra runners. They have to deal with a lot of uncertainty because the data just isn't quite as good as it is on the cycling side. But your point is well taken that I think that, you know, there is this kind of like fine line that we do have to degree, we do have to live with some degree of uncertainty. And once an athlete becomes really well trained, they become highly trained.

It's hard to find that signal through the noise because the differences that you are really looking for, the meaningful differences that you're looking, that you're really looking for are so small compared to all of the other things that are impacting their athlete, the athlete, their mood state, you know, how well they slept the previous night, how much they're enjoying things, the purpose and things like that. All of those things are usually orders of magnitude or we can envision that they're orders of magnitude difference as compared to the things that we actually can measure that living with it without uncertainty is kind of a reality. And we see this, you know, this just as well as I do. We see this in the actual physiological testing data where we can bring an athlete in and I'm going to have my lab manager come in just a couple hours from now, to be honest with you, to do a podcast on this.

We see athletes come in once a quarter, every single quarter. And at the, after a certain amount of time there, you can't tease out any additional improvement from the physiological data yet. They can perform better or worse, depending upon what, what all of these other variables are going on. So I guess what I'm starting to say is, is what we can, excuse me, what we can measure starts to decouple from the actual performance in the way that we can explain that decoupling or try to explain that decoupling is just the complexity of the entire system. Okay. Okay. Yes. In my book, I explain this decoupling with a distribution, a probability distribution, because for example, the performance of an athlete is, it's like a Gaussian distribution of air curve.

You know, you can, for example, do, I don't know, 20, 20 tests, no, 20, 20 minutes test. And the media could be a, a, a, 300 bucks, but there will be some randomness. Sometimes you will perform better than the average. And sometimes you will perform below. When you improve the medium of the Gaussian distribution moves to the right, but there is also possible that you are a fighter, no. On average, but you perform below the, the, the, the, the performance that you had, uh, two months ago.

So the reason is, or the problem is that you can be fitted in overall, but one specific day because motivation, because I don't know, sometimes we are not machines, no. But because everything you, um, you perform on that day is, is below. And you don't need to be worried about this because it's normal, but you can't, uh, seeing that your performer or your feet to stay depends on the previous test. Uh, this is a problem of many cyclists that seem that I only worked as my previous best. The previous best test. Yeah.

Well, here's, and here's how it comes into reality, right? And you know, this is a coach. The athletes always want to know if they're better, worse, the same. We just went through that. It takes a lot of data to actually tease that out. And sometimes you can only tease it out with a cert with, uh, with, uh, uh, some degree of certainty, right? Plus or minus 10% or 20%, kind of whatever you want to, whatever you want to use. And when you're at a really trained state, finding that signal through the noise becomes very difficult. And like I said, you have to have a lot of workout data. What, from a pragmatic point of view, I want to drill this down into things that the athletes can actually take away. So one of the things that I do with it, with an athlete is just take their performance over their workouts for an entire three month period.

And so that's going to be 20 or 30, you give an example of a hundred times, right? That's only going to be 20 or 30 performances that we're kind of like averaging together and seeing how that average stacks up with the previous years data. And even then it gets extremely fuzzy. So it would be an error to say, I did this one workout better or worse than I did last week, the week before the phase before, or things like that, because it's only one instance at a point in time. The real way to get at it is to pull a lot of data over long periods of time. And most people just don't want to, they don't want to take that, that kind of global approach with looking at it, but you really have to do in order to get kind of the best.

Assertation of things and then realize that those that's still going to have some shortcomings in it because of the picture that you're, that you're, that you're trying to encapsulate. Correct. I think songs, especially in cyclists, because in state runners, I see that they know themselves better, but especially in cyclists, I think some people are bullied by numbers or they train worse than they could because they want to continuously to perform better than last session, better than last week. And when something is wrong. When you, when your last ride is worse than last week, there is a problem.

And they want to change everything to train harder to eat less. So, so a lot of times if they will not have power meter, it will be better for them because you work. I remember when I started to racing, you work without knowing if you are improving or worsening. There is some problem with it, but the good thing is that you work and don't think about it. Yeah. The results come. Yeah. Yeah. Yeah. Cause it'll cut, you do the work, it'll come. And sometimes you have to deal, like you said, you have to deal with a certain amount of uncertainty.

I think that that's one of the big take home points that I, as a coach, and I try to relay to my athletes, I try to reemphasize with appreciating these complex systems even more is that it's okay to have that level of, of uncertainty. You do need a blend of feeling and data to kind of, to, to, to, to really tease things out, but don't assume that just because you know, the numbers are going up, everything is better or the numbers are going down and everything is worth worse. You have to take a more comprehensive approach with it. And that's just something people just don't like, they're not wired to do that. They would kind of, they want to know the answer, right? Just give me the answer. I want to know what the number is. Is it red, yellow, or green? And then I can kind of, kind of go on with my day.

Um, I, I really appreciated this, uh, the, this conversation. Like I said, I, I, uh, I, I've, I've enjoyed your work. I've tried to get a lot of it translated as, as you know, the listeners can, can tell English is not your, your first language. So I appreciate you coming on the podcast and being a, a good sport about it. Before we, um, let you go, where can the listeners learn a little bit more about you, your book and your podcast? Well, uh, I say, um, I have a, a, a podcast and a book in, in Spanish. So they can, uh, search for cyclismo evolutivo in whatever Spotify, Google podcast, Apple, but I, I am trying to, I am working on translating my, my book to English.

So I hope, uh, soon, uh, they can read it directly. Uh, I also hope that I improve my, my English, almost everything, my pronunciation, because I, I can understand you, but for me, it's hard to, to talk. So I'm sorry if people don't understand me, uh, as good as they could. Dude, don't apologize one bit, Manuel. Like I, I, like I said, I really appreciate your work. I appreciate you coming on and you'll get better, man. I've brought people back on this podcast or English is not their, uh, first language and that the audience appreciates it. And I appreciate it because you bring good information to the table. So that has to be the star of the show. Thank you for coming on the podcast. All the links to what, uh, uh, Manuel just mentioned will be in the show notes.

I hope you guys go and check it out. All right, folks, there you have it. There you go. Thanks to Manuel for coming on the podcast today. I really appreciated all of his insight into the complexity of training. And this is an area that within my coaching career, I am beginning to appreciate more and more. I used to think that it was a very specific thing that caused an adaptation. We did an intervention. We took a nutrition supplement and we saw this kind of linear or one-to-one relationship between cause and effect. And you see that out in some of the popular literature today, where I take a supplement and it caused an improvement in my heart rate variability or my sleep or an improvement in performance or whatever it is.

And when you scratch down beneath the surface, what you should be beginning to appreciate is that there are many variables that go into that. Those variables are nonlinear and it's very difficult to understand all of the interplay within all of those variables to explain these types of phenomenon. Yes, we can come up with direct practices, but I think all too often we tend to oversimplify what is going on and we need to broaden the lens out and appreciate all of the different many nonlinear types of interactions that are going on within the day to day within the human within an athlete in order to track outcomes and performance. That's it for today folks. That's it for today folks. I appreciate the heck out of all you listeners. As always, this podcast is brought to you without any sort of sponsorship or endorsements.

And that's so I can keep it as unbiased and unfiltered and unadulterated as possible. I hope you guys appreciate this. If you do, please feel free to share this podcast with your friends, your family, probably your training partners. That would mean a lot to me and I hope the knowledge means a lot to them as well. That's it for today folks. And as always, we will see you out on the trails.