Make Swim Testing Great Again: A Physiology First Approach to the Best Swim Season

0:00  about an hour of presentation. Maybe a little bit less, maybe a little bit more, but approximately that's what it's going to be. Therefore, we give it again like a few minutes more for people to drop in. If you haven't heard that yet, welcome to today's webinar. I've got Parker Spencer here with me, he will share some thoughts and some ideas on swimming economy and especially some experience on testing swimming economy. And yeah, that's going to be a big part of it. Me, my name is Sebastian Weber,

0:46  I'm the founder of Insight and I will guide you as the main host through this webinar today. And then we are also going to have some co-presenters via video, which I'm just about to make, we had some technical issues here. So I hope that's going to work as well. So the training zone build Okay, so while we are waiting here, I'm going to start share my screen and go back to screen here in a second. So here we go. You should be able to see my screen now again.

1:42  Okay. So with that, maybe Parker, we should get going. Yep, that sounds good. Let's not make people wait too long. So today's webinar about swim testing and how to make your swim testing great again, so to speak, in order to make sure that you do have a great season. We are going to talk about this agenda here, roughly guiding you through today's webinar, which is screening of physiological profiles to provide or to identify training priorities. We're going to talk about aerobic and aerobic energy contribution and also aerobic and anaerobic training stimulus.

2:24  And with that, we also need to address testing protocols and look a little bit at glycolytic power or glycolytic energy metabolism. Then, as I said, we're going to look at swimming economy and Parker is going to chime in here and we're going to look at recovery in between training sets and also building out specific training zones. Again, questions at the end. However, I ask you to send in questions here as we go. That would be great. Because the question that you have might trigger a sort or a question

3:01  somebody else who's attending and then, you know, how we offer some great snowball effect here. So that. So in general, to kind of, so to speak, to lay, you know, to lay the foundation of what we are looking at here, what we want to do here, you could argue is some kind of reverse engineering swimming performance. And I'm going to give you this example. So let's assume, just as a thought experiment, you have two athletes, two swimmers, who accomplish the same distance, let's say 200 meter freestyle swimming

3:34  in the same time. So looking only on that surface level, you could argue that the performance of those two swimmers is approximately the same because they, you know, perform the same in terms of time to cover 200 meter freestyle swimming. However, that is not the complete picture because basically what could be the case is that those two swimmers need a different amount of energy to cover that distance. Meaning their technique is better, their drag in the water is less, their position in the water is different. You know, whatever you want to sum up on swim economy,

4:10  so to speak, might be, might be different. Okay. And that is not where it stops because this is just so to speak, how much energy, metabolic energy they need to swim 200 meters, 150. The other question that arrives is actually, how is that energy made up? And as you will be aware, there are three energy supply mechanisms which can actually supply this energy. So energy partly comes from creating phosphate. It will partly come from glycolytic energy sources and the partly come from aerobic energy sources. And so in the first step, the energy can be different,

4:47  which is what we're going to look at here with swimming economy. On another step also, the makeup of that energy can be entirely different. So you can have different contributions from creating phosphate glycolytic system and aerobic system to this energy. And so you might say, you know, I don't care so much because at the end, they're both have the same speed. Yes, that's true. But if I would fold that again, right? If I would close that again, then how much does this tell you what are the limiting factors of the swimmer?

5:22  And this is basically the main thing which I'm trying to bring across here. If I just look at this picture here right now and I just have the best times or just time over a certain distance, I don't know what is the limiting factor. And if I, so to speak, dive one level deeper, then I can already understand, okay, wow, you know, one thing that maybe limits swimmer A is that he or she needs significant more energy than swimmer B. And if I then dive even deeper,

5:52  I can understand if it's maybe limited by aerobic performance or if it's limited by glycolytic performance or whatsoever, okay? So this is actually what, at least in my mind, and I hope Parker would agree here, maybe some others, is what you would want to do. You would first want to do, to understand the bottlenecks, the limiting factors, and to understand, to make like an audit, so to speak, of the performance of the swimmer and understand which factors provide the biggest room source improvement, what is limiting the swimmer.

6:25  And that's what we're addressing here, basically. And we're going to start with the demand side. So we're going to start with the energy demand versus speed, right? So swimming economy, so to speak. So how we measure that in inside, some unique way to it, is that we are looking at the energy contribution in the speed versus power relationship and be doing so by normalizing substrate utilization. So what do I mean with that? Is that if you normally, for example, take running economy, there's a common problem. Running economy is often expressed

7:03  just as oxygen uptake versus speed. But then think about it, if somebody in a test retest scenario increases their fat combustion, so they have better fat combustion, fat needs additional oxygen. If you just divide the oxygen by the speed, you would get a worse running economy, not because the running economy is worse, but just because somebody burns more fat. So that's a common mistake. And we account for that because we normalize oxygen uptake to substrate utilization. The other thing is that often overlooked, especially in swimming, a certain amount of energy

7:38  is coming from anaerobic sources, especially at race speeds. It's not so much of a problem at training speeds, but hands down, how much are you interested in the swimming economy for somebody swimming at a pace of 120 if race pace is whatever, 50 seconds for 100 meter? You know what I mean? So it's intensity, which matters to you in swimming. A significant amount of energy comes from aerobic energy sources. And you don't measure that by putting a mask on somebody's face because here you could just get

8:09  the aerobic contribution. So we take this into account as well. And then we display the economy in terms of energy demand as in relation to speed. We display that to you, not only in this form that you would have the pace or the speed on the x-axis and the energy demand on the y-axis, but we display this to you also on this chart where you can basically compare the energy demand of your swimmer to a comparison group and show what you see on the y-axis here, how much energy

8:41  the athlete saves or expense more than a comparison group. So you have, so to speak, a built-in benchmark system where you can say, oh, you know, is that actually good or bad and compare that to terms of energy. And we can even, which I don't have here, I don't know, Parker maybe shows it, but we can even then translate it into speed. So instead of going to an athlete and say, hey, you know, you are, you know, you are going to whatever, you need 10% more energy,

9:08  that's not really tangible. But if you can say, ah, if your energy would be the same as a comparison group, you would swim five seconds faster for 100 meter or two seconds, one second, that's tangible, right? Then you speak the language of the athlete. So yeah, this is just what I just mentioned. How you do that? So the best, the gold standard to do that is not putting somebody in the flume, is not putting somebody on a snorkel on these kind of difficult measurements. The gold standard,

9:37  which is what most people, most of our users are doing, is just put a view of two analyzer on the face of the athlete as soon as they come back, as soon as they finish an effort. You see here, Florian Velbrock of German Swimming Federation doing that. And then you look at the VO2, how it decreases. And from that, we can, you know, extrapolate and calculate the VO2 during the exercise. Reverse extrapolation of VO2, standard procedure in swimming these days, not affecting swimming technique using a snorkel,

10:09  not affecting, you know, whatever, drag or something by swimming in a flume where the water is moving and not actually the athlete. So that's that. How big are the differences? I know Parker has something for you here. I'm sharing this one, which is a measurement with a French group. So you see here three swimmers. You see the speed on the x-axis, the oxygen demand. So this is total oxygen demand, which means normalised oxygen uptake, normalised for substrate utilization, plus the anaerobic energy contribution just converted into oxygen.

10:47  So you can put it on the same, on the same scale. And the dashed black line is comparison group from the literature. And the yellow one is an amateur swimmer of this group. The purple one is an amateur modern pentadlete, so not somebody who has swimming as a main discipline, just one of five disciplines. And the blue one, which you can see almost as a linear shape, so not even as exponential shape, which you see at higher speeds, is somebody who prepared for Olympic Games at that time.

11:23  And what is remarkable here and what stands out if you look at the speed differences, so if you look at an oxygen demand of 50, to simplify it, let's say it would be an oxygen uptake of 50, right? One swimmer swims 1.2 metres per second, one 1.3, and the other is 1.5, or sorry, 1.45. So tremendous amount of differences that you can see sometimes. And I think this is where I ask Parker to chime in. Yeah. Yeah, so, yeah, just to give a quick brief background, my job is,

12:00  I coach USA Triathlon's Olympic development athletes. So I recruit them when they're 17, and then my job is to develop them over a 4, 8, 12-year period to an Olympic medal. So we're looking at every fine detail that we can. and one of the main reasons that I became a user of Inside is because I didn't want to guess when it came to programming what my athletes were doing. I wanted to know exactly where I needed to focus my attention. And I'll give a couple examples here.

12:34  I will share my screen.

12:40  Hi, this is Alexander Cherpel from the German Center. Not that one. Okay, so, this is, skip through this real quick. Sorry about that. This is a presentation I did with Greg.

13:09  Okay, so, as we're talking about the swim economy here, so, this is one of my athletes, Drew Schellenberger. Drew's given me permission to share all of this with you. Parker, just to let you know, we are seeing this slide number three with Reese. Okay, let me see. Just do it in the PowerPoint. That would be easier. And don't start presentation. Okay, can you see that right now with Reese? please share again, and then it should come up. Okay. Just don't start slideshow, just stay in the... Got it.

13:56  Okay, you got that? slide 23, Reese. Yes. Perfect. Okay. So, looking here at Drew, Drew came here from... He came to me as a triathlete, but he did have a strong background in swimming. Over the course of the season, one of the things that we started to see was his times in not just training, but in races were starting to go the wrong direction. He was coming out of the water further back than what he normally would, and so what I thought had happened over the course

14:39  of the season was he just got out of shape as we were racing and racing and racing. We weren't spending enough time on the actual training piece. So, my thought process going into the off season was he was going to do a lot more volume. We were going to gradually build the intensity in, and then that would get him back into shape going into the next season. What I did, though, is we did full inside testing to see if what I assumed was actually true, and it was

15:12  not true. So, what I saw is that from a fitness standpoint, he was actually very fit, but his swim economy was terrible. So, instead of him swimming 35, 40K a week over the off season, we spent a lot of the off season working on his technique, working on his economy. One of the other things that I think is interesting is if I were to take underwater video, which I think is how the majority of us have done swim technique coaching over the last decade or so, his

15:51  technique looked fine. He was doing all the points that we like to look at. It didn't look like there was anything major that we needed to switch up. And then when we did this testing and saw that this right here is what his economy actually looked like. And the faster that he got, the worse his swim economy got. over the course of the off season, we focused on that. And then he was in the front pack out of the water in every race that he did this

16:25  past season. One of the other features that I really like with inside is I can take one of my athletes like Drew and compare him to somebody who is coming out of the water first. So I have another athlete, Carter Stollmacher, who is consistently out of the water first in any race he does, whether it's a Continental Cup, World Cup, Super Tri Racing. He's one of the first guys out of the water every time, one of the best triathlon swimmers in the sport. And I can take Drew's

17:03  data and Carter's data and overlap them together. And a big part of my job is to make sure these athletes are able to compete at the demands of competition. So Drew needs to come out of the water in the front. So let me compare him to an athlete that I know is coming out of the water in the front. So even just looking at 115 meter pace for 100 meter, comparing Carter to that original test with Drew, for Carter to swim 115, his oxygen uptake only needed to

17:43  be 39. He's basically sleeping. Then for Drew to do that, he's at 71. So he's absolutely full on at that pace while Carter is just chilling. The goal over the offseason was to obviously bridge that gap and get it a whole lot closer, which is what we did. And Drew was able to swim on Carter's feet in most of the races and they were able to come out together and work on the bike.

18:19  So that's a quick example with these athletes.

18:26  Then, yeah, and then one of the things that I'll also say is that the other day we were videoing some of our athletes doing testing and I had someone message me on Instagram and say, oh, you're doing it wrong, you're testing them on the side of the pool. They sent me a video of someone using the Cosmet Snorkel and that kind of defeats a big part of what we're trying to do here with testing economy. If you use a snorkel, most athletes lose their technique when they turn

19:00  their head to breathe. And so one of the big points with testing this way and testing on the side of the pool is to make sure that we are getting an accurate swim economy from all that data. Yeah, you want to test as close as possible to the real world conditions, right? Yeah. So open water would be another possibility, but then it's a little bit difficult with the distance measurement, right? Even though I know some people are doing that. Awesome. Thanks. Yeah, great example, Parker. Thanks a lot

19:31  for chiming in. I know it has been difficult for you to make the time because I actually understand you need to go to the pool soon and coach again. Yeah, yeah. I have athletes warming up right now in the pool, so I'm going to jump out. Okay, thanks for chiming in. Thanks, Parker. Any questions you guys have for Parker, send it here and I will try to answer if I cannot. I see Parker again, actually Parker in three and a half hours, so then I can ask him

20:01  and get back to you, okay? So please don't hesitate to ask questions here, okay? Thank you, Parker. Awesome. Thank you. Okay, so that was on the energy demand side, right? So going back to the starting point, we want to look at the demand side and the supply side to reverse engineer how we can improve performance. So let's now jump into the supply side and in order to do that, obviously, with having different, you know, metabolic pathways here that contribute to energy supply, we need to look at

20:35  them all and here's another example of that basically, okay? So this is two athletes, okay? This, you know, you just get a snapshot here of the metabolic profile which you get inside and I want you to focus on the very right hand here first, which is the anaerobic threshold value. So both athletes here do have the same threshold, for 100 meters, which is 136 in terms of meters per second. And in this case, just to prove the point, they also have the same swimming economy. So it's

21:12  not what Parker just talked about, right? So what this would mean if you would do a normal lactate profile test with those two athletes, you would see very similar lactate curves. Of course, if it's in the area of measurement, the low intensity might look a little bit different, but approximately where you would define threshold, Dmax, fixed threshold, whatsoever, you would see very similar data on the lactate curve. The point is that the metabolic makeup of those two athletes still having the same threshold can be vastly different.

21:44  So you can see here athlete number one has a higher VO2 max, a higher aerobic ! capacity, aerobic power, and a higher anaerobic power, VLMX. And the athlete number two is lower on both ends. And I'm going to explain in a bit here why this can and will result in the same threshold value, in the same lactate values, at the same speed, basically. Okay? And if today we would be talking about marathon running, half marathon running, road cycling, you know, these kind of long events, okay, then you

22:21  could argue, let's say, if this would be half marathon or 10k, you could argue, okay, at least, at least the threshold is somewhat a close indicator to the race pace, and at least the threshold gives us some information over the race pace. But here, it is even a bigger problem, because if you think about a two-minute, three-minute, four-minute, five-minute, eight-minute effort in swimming, then you need really both. You need a high aerobic system, and you need a high anaerobic system. So, point is that if you just

22:54  have a lactate profile curve here and just some kind of threshold values, I'm not even going to argue which threshold concept you use, fix, D-max, whatsoever, that's not even the point. The point is that you can have similar thresholds, same thresholds, similar lactate profile curvature data points in the lactate profile and have tremendously different maximum aerobic and glycolytic capacity. And I think it's pretty clear that the guy who has both better aerobic system and better anaerobic system will perform better in almost any swimming competition, which is

23:27  just a few minutes long, because you need both systems, right, maxed out. So that is basically a visualization of the same problem here where I'm trying to go to. Why is that? Why can you have something like this? So why can you have a higher VO2 max and a higher VLMX resulting in the same threshold as lower glycolytic ! capacity and lower aerobic

23:58  capacity? So higher glycolytic power or anaerobic capacity, whatever wording, you know, resonates better with your world, means higher glycolytic power means higher lactate production, higher lactate production means higher lactate concentration, I'm going to show here next, and therefore the curve, the lactate profile curve would shift to the left. On the other hand, a higher aerobic capacity means that the athlete can rely more on this aerobic system, so more energy will be supplied from the aerobic system, and then very nice proven by the guru of lactate himself,

24:33  George Brooks, but also logical, if you have high oxygen uptake, you can burn more lactate, basically combust more lactate, which will obviously lower the concentration, and therefore the curve would shift to the right, which is arguable, maybe one of the most common assumptions, I'm going to come to that in a second here, okay? So both systems, so to speak, pull the lactate curve to the left on the right, and then of course, what I just showed you here with the previous slide is if both pull the same

25:02  amount, with the same strength, or the same distance left and right, then the curve is not moving anywhere, so you can produce very similar lactate curves with entirely different aerobic and anaerobic capacity, okay? And if this is somewhat too conceptual, too theoretically for you, I'm showing you this one, which is real world data, okay? So what I'm going to show you is a comparison of people within a training group like Parker's group and swimmers and so on and so forth, their speed at four millimoles, so the

25:35  delta speed at four millimoles, what does delta mean? Individual athlete compared to the average of the training group, okay? So we make an average of the training group speed at four millimoles, and we show how much each athlete deviates, and the average view to max and show how much each athletes deviate from that. And this is basically is a correlation. So, sorry, red dots, swimming, elite swimmers, yellow dots, triathlon elites, so, you know, triathletes. So what you can see is that the difference in speed at threshold

26:14  at a fixed lactic concentration, whatever you want four millimoles to be, I don't want to get into this discussion, the difference you see at the speed at a fixed lactic concentration does not really correlate a lot or at all. Maybe statistically you could put a positive regression line in there, but, you know, the ask where would be pretty messed up. So, the speed, the change of speed, the difference in speed, somebody's being faster or slower can not really be explained by just a better aerobic capacity. And

26:44  this is more or less just what we learned from the economy. And

26:52  because of higher or lower lactate production, aka glycolytic capacity. So, that's very, very important. Again, it's not only theoretically how it should be, but that's also what you see. This is measured data from two different training groups. So, what's the solution? The solution is mathematically to decipher, and that's what I'm showing you here, what I'm going to explain, to decipher the actual production and combustion of lactate that creates a certain concentration. So, what can be used basically is that if you increase the load, what you see here,

27:33  like this would be an example from a cycling test, so to speak, if you increase the load, in swimming would be speed, then the behavior, the kinetics of oxygen uptakes are different, almost linear, as you will know from measurement, than the one from lactate production, which is blue here, right? lactate production is the blue one and lactate combustion based on oxygen uptake. You can see the curve, the purple curve looks much like oxygen uptake, has a different behavior. And because those two behave different, it is actually

28:07  possible mathematically to decipher, if you have lactate concentration over different loads, it's actually possible to decipher, to disclose, to calculate, what is the actual lactate production and what is the actual lactate combustion that created a certain lactate concentration that we have been able to measure. And this is really a key part in the diagnostics, okay? Because, let me explain, when you are able to take the lactate concentration and decipher and explain what production and what clearance, so what combination of those two created the same concentration, what I'm

28:49  trying to say, oversimplified mass, if you arrive at two millimoles lactate, you can either have produced three millimoles and combusted one, or you could have produced four millimoles and combusted two, right? That's more or less oversimplified speaking, what I'm trying to say here. So if you can decipher that, then it opens up a whole new world of possibilities because the lactate production that you see in submaximum efforts is related to the VLMX, it's related to the maximum lactate production. The next thing is, as you will be

29:23  aware, the only source, the only substrate you can use to produce lactate is glucose. So if you know lactate production, you immediately know glucose or glycogen utilization, right? Maximum lactate steady state and thresholds is nothing more or less than the equilibrium between production and combustion or production and clearance. So if you know both, right, then here you can get to the maximum lactate steady state. The lactate clearance, again, as proven by George Brooks already with Donovan in 1983, I can send you the paper if you want,

29:58  lactate clearance is a function of oxygen uptake. So if you know clearance, you can basically calculate oxygen uptake. Okay? And the slides that I just jumped here is exactly doing this. So here you can see a graph where you see the blue lines is oxygen uptake, which is actually calculated from lactate measurements. And you can even you know, you see here, you can even like, you know, calculate a slow component like where you know, when you go above metabolic steady state where you can see oxygen uptake

30:29  increasing. So how to do that? As I mentioned, in order to be able to do that, all is needed is a set of a minimum three or more submaximum efforts below five millimoles. It can be anything. one millimole, 0.81, whatsoever. And it's recommended to have a minimum of three minutes per effort as a duration, except for maybe if, you know, you have a reason why you want to do longer. And it's recommended to have one all out effort, at least one. You can have several. And then

31:07  you just measure lactate before and after. Okay. And that's all, which means you are pretty flexible when it comes to mixing efforts, right? So you could do whatever, three times 400 or one times 400, one times 800, one times 600. You are flexible with the pause duration in between. So there is no fixed protocol. You can do 30 seconds rest, you can do 45 seconds rest, or you can have whatever rest is comfortable for you in between each effort. It doesn't matter. And you can even mix

31:37  strokes. You can do whatever, three efforts, which is very common, three efforts in freestyle, and maybe the all-out and butterfly or breast stroke or whatsoever. And many people do that, and many people do different kind of all-out efforts, right? Maybe two all-out efforts, maybe a longer and shorter one, trying to mimic race performances or the performances that you know, the actually training for. Okay? So, that is all that is needed because that gives the algorithm a very, very good picture of lactate production at lactate concentration at different

32:19  intensities. And again, because of the different kinetics, the different behavior of aerobic and anaerobic metabolites at different intensities, it becomes possible to decipher lactate production and combustion and therefore this whole universe of possibilities opens up. And with that, I would like to give the word to Alex from German Swimming. And I need to do that by changing here the screen. Let's see if that works, because otherwise you don't hear the voice. the head of diagnostics. Since 2020, we use the inside software for selected coaches and athletes.

33:04  To get the inside specific results, we are using a set of single distances. These can include, for example, two to three times longer distances, over 400 or 600 meters with low intensity, and also two to three sets of 100 or 200 meters with a maximal or submaximal effort. Here, not always a maximal effort is needed. To get also the inside specific results, it's just for us to get, for example, for 200 meters to originally measured VO2 max values. Since a couple of weeks, it's possible also to implement

33:42  a step test results. This is a big step forward for us, because in the past, we always did both the inside specific test and a step test results for our coaches. Now it's possible to implement the step tests and get also the 360 metabolic profile from inside. This is really, really good for us, because now we save time and money and get also all the parameters that we got before in two tests.

34:17  Thanks for that. So, we're going to see Alex again later when we talk about training zones. German Swimming Federation actually has created a new set of training zones and Alex is sharing what they're doing there when we come to the training zones. So, another thing, I just want to give you an example of how you can use that and what's the outcome. So, let me go one step back and review what I just said. We said we look at lactate production and combustion different intensities. And therefore,

34:57  from this graph on the left, which I already explained, we can get to a general behavior, where we say we can show what is the lactate combustion blue line as a function of speed and what is the lactate production red line as a function of speed. Okay? So, that's part of the output. And now what is interesting is to look at the gap, to look at the difference between the blue curve and the red curve. Because you want to look at it like this. The blue curve is the

35:26  ability of the athlete to combust lactate. You see millimoles per minute on the y-axis, right? So, it's not a concentration. That's the ability of the athlete to combust lactate. lactate. And the red one shows you the gross production. So, how much of that ability, so to speak, is already eaten up or occupied by the production that's happening anyway. And that means the gap, the difference, the distance between the blue and the red one is actually the ability of the athlete to combust additional lactate up to threshold values.

36:00  Threshold is by the way where production and combustion meet per definition. And that's something that has become super useful for users to use in training sets. And I want to give you that example. So, we just plot the difference. So, we take the difference between the blue and the red and plot it in a separate graph, which is this one. You call the lactate recovery. So, this shows the ability of the athlete or the speed at which the athlete can clear additional lactate as a function of speed

36:34  or pace. So, you can see the speed pace for 100 meters on the x-axis and the ability to clear additional lactate on the y-axis. And you can see, and that's always the case, just the question of which speed it happens, you can see that there's an apex, there's a maximum. So, there is a maximum at which the athlete clears lactate the fastest. And that is very useful and has been proven very, you know, valuable to set up rest periods in between intervals. Because if, for example, and I'm going to

37:11  show something specifically for that, if you want to set up intervals the right way to trigger the right training adaptation, you need to understand if there's a carryover effect, a compound effect, for example, from lactate accumulation from one interval to the other and what it does. Because if you accumulate one interval, a lactate from one interval to the other, what's happening, you can assume, or it's also given, so to speak, that the pH level will decrease from one interval to the other. So, you have a compounded carryover

37:46  effect of acidity or acidosis, so to speak. And this shuts down glycolysis, so the glycolytic stimulus will decrease. And I'm going to show an example about that. So, long story short, what you can do with that, testing is, you can understand at which intensity the athlete can recover fastest, or best, so to speak. And then, either use it for full recovery or avoid it if you don't want that, right? If you want to have a compound effect, so to speak. Okay. There's another video I wanted to

38:19  share, but unfortunately, it's not loading, so I will put it in the recording for afterwards from an amateur coach here, Avud from Thailand. Okay. I need to skip this, unfortunately. So, I'm coming to the example which I just mentioned here, okay? Training example. So, here's looking at what's going on in training, which you can do when you have this information about the metabolic profile of the athlete. Okay. So, we are looking at an example of 10 times 100 meters, with 57 seconds completion, and a passive rest of 13

39:00  seconds in between. And you just see here the low profile. Okay. So, somewhat a typical or representative training set. Okay. And we are looking at this, what does happen to two different athletes when they complete this interval set? And our one athlete has a super high aerobic capacity, 85 milliliters, elite, world class level, very high glycolytic capacity, VLMX 0.8, and a somewhat not so great swimming economy. And our athlete number two is a little bit less good, so to speak, in aerobic capacity, but still elite athletes.

39:37  So, same level of athlete in terms of training group. But now we are looking at, so to speak, a non-high anaerobic guy. So, that's the story here, right? So, we have a non-high anaerobic guy. There's a little bit better, not a lot, just a little bit better swimming technique. Okay. So, the main thing is, higher glycolytic guy, lower glycolytic guy, high anaerobic guy, no anaerobic guy. Okay. And because of this makeup, their best time for 200 meters is similar, same, 148. Okay. That's what they can swim for 200

40:12  meters on a 50-meter long course. And now we let those two swimmers complete this 10 times 100 meters interval and see what happens. And when I say, see what happens, we are looking at the aerobic stimulus and we're looking at the glycolytic stimulus. You might be aware, you will likely be aware from the literature that in order to understand or predict or have some kind of indicator of adaptation of the aerobic system, you want to look at the fractional utilization of VO2max, right? You may be aware of

40:44  this magic number of 90%. You want to utilize more than 90% of VO2max because the more time you spend above 90% of VO2max, the better adaptation in VO2max, like you're going to get, literature says, Rennestad and others. And there's also papers showing higher fractional utilization of VO2max results in better aerobic adaptation. So let's look at this. You will always see solid line of swimmer 1 and dashed line of swimmer 2. Again, swimmer 2 was the low glycolytic guy. And what you see here is exactly this percentage

41:20  utilization of VO2max.

41:24  And you can see immediately that they both spent most of the intervals above 90%, right? 90% is on the left side here. But you can see that swimmer 2, the lower anaerobic guy always is higher, receives this in what the literature tells us, the higher, the aerobic training effect because higher, more time above 90% VO2max and higher fractional utilization, which is great, right? Because if you go back and see, okay, he has a little bit lower VO2max, so you maybe appreciate that the swimmer has a higher

42:04  utilization of VO2max. Awesome. Good. That's maybe what you want. Okay. So that's, that's pretty good. However, the training stimulus is a little bit different in both. if you use utilization of VO2max as the indicator for that, right? So what does it mean? Swimmer number one does not get the adequate same training stimulus of VO2max and maybe VO2max even drops because of that, right? So maybe he's not able to keep the 85.

42:36  And the picture gets more extreme when you look at the glycolytic utilization. So if you apply the same logic to the glycolytic metabolism, here you see extreme differences. So swimmer number two, because his VLMX is so low, is triggering his glycolytic system. You can see at the beginning this more than 60%. So super, super high for glycolytic systems. The percentage are lower. Like in endurance sports, marathon, running, we look for something below 10%, just to put this in perspective. Very, very high glycolytic stimulus and much, much

43:13  higher than swimmer number two. So swimmer number two is not getting the same anaerobic training stimulus as swimmer number one. It's approximately half. And you need to ask, we need to ask ourselves in here, okay, wait a second. If this guy has a high glycolytic capacity and we let him do this training and he doesn't get an appropriate glycolytic training stimulus, maybe he will lose his strength. Maybe he will lose his glycolytic capacity. Right? And then, of course, the other story that you can see here, especially

43:46  in swimmer number two, is this compound effect of a non-complete recovery. So, for example, if your aim for this training was to give a high glycolytic stimulus to swimmer number two, you could argue this aim is fulfilled in the first one, two, three, four, something like this, sets. But then, because of the compound effect, swimmer number two is losing the training stimulus, going back to the problem or what I just described as being able to know the recovery time based on the swimming speed. So, recovery of

44:20  lactate and this goes hand in hand with the restoration of higher pH levels. So, different training stimulus, not on the aerobic system, but also on the glycolytic system, huge difference on the glycolytic system, and a massive compound effect. So, depending on what this training aim to do, that's the other question, it's the context, but what is clear is the outcome, the training stimulus for swimmer number two and swimmer number one are vastly different. So, how to fix that? How can you avoid that? And with that, I

44:53  need to change my screen, and I hope that the software didn't lock me out in the meantime, because there's a security lockout. So, I need to switch to the inside app here really quick, because I wanted to show you something live. So, what we built, really quick, and what I'm going to show you, is I would argue maybe the most liked popular tool for swim coaches. Let me explain why. It's called the training zone builder, and it allows you to create training zones, but I would argue up

45:24  to even training sets of what you want to do. So, normally training zone goes as a percentage of swimming speed or fixed lactate values or whatsoever. Okay? And now, what you can do here is you can set up a zone based on whatever metric you want. Okay? Let me do this real quick. So, you have an example, and let's say we select swimming freestyle, right? And you can give some context what you want to use it for. Okay? You give your zone a name. I will be easy

45:54  and just call it zone one. Okay? And just give it a one. And then you define how you want to display that. And because we are in swimming, let's say we want to have the pace for 100 meters. Okay? Now, you can define any physiological KPI, any benchmark, any physiological system that is of interest of you that you actually want to trigger, that you want to address in this training zone. So, for example, in more endurance sports, things that could be I want to stay at the

46:26  intensity which elicits highest fat combustion rate, fat max zone, right? Or very classic one, you can say, ah, give me 100% of lactate threshold one, for example. Okay? So, you can do that. And of course, you can do, you know, anaerobic threshold, maximum lactate steady state whatsoever. You can also do a fixed lactate concentration and say, okay, my training zone is a fixed lactate concentration. Okay, easy. So far, so good. Now, you can say the lower one, let's say, is 1.5 and the upper one is 2.5, whatever.

47:01  Now, you can also say, ah, I want to know what's actually going on. So, if the swimmer swims at two millimoles, I want to understand how much fat does they burn? What is the aerobic, anaerobic energy contribution? How much of the VL2 max or VLA max are they utilizing? Just what we looked up, right? So, you can set this up. Let me give you a more specific one. You could say, well, I want, for example, the lactate concentration, but I do want the lactate concentration not in

47:32  steady state, but I want it after a certain distance. Because think about it. For example, if you enter four millimoles of lactate to get, well, six, to get to this lactate concentration after 200 meters shorter time, requires a different speed than getting to it after 400 meters. Because lactate concentration is, you know, lactate accumulates over time when you're above threshold, for example. And therefore, longer times means higher lactate concentration. So, that's what this tool is allowing you to do. You can say, oh, I want something that triggers

48:06  six millimoles of lactate concentration after 400 meters. And then I would like to know how much percentage of that is of VO2 max, and maybe what is the actual accumulation rate of lactate, and maybe the heart rate or whatsoever. Okay? And therefore, you can also set up a training zone where you set it up as a percentage of VO2 max. So, I want, for example, a, you know, 50 meter effort, a sprint. I want a 50 meter effort, which gives me 50% utilization of the glycolytic system.

48:50  And then I want to know what is my lactate concentration afterwards, because that helps me to understand how long the athlete needs to recover. This is how you can set it up. And you can set it up also with, of course, percentage VO2 max and whatsoever. And we had some special request from German swimming on changing something on that, even extending it, so to speak. And therefore, I would like to show you another video here, which is again from Alex. Okay. Where he explains how they use it and what

49:29  they want to do. Because it allows us to define training zones how we want to. The beauty of the training zone builder is that each single training zone can have a different reference marker. So, let me show this.

49:44  Based on this example, for example, in German Swimming Federation, we have eight training zones. And each training zone can get a different or a unique master metric. So, for example, for our zone one, two, three, we have the reference marker to the lactate threshold one. So, our zone four and five have the reference marker to the second lactate threshold. And our zone six, seven, eight has the reference marker to the VO2 max. So, this allows us to design a really, really individual training zone metric. So, this is cool for us and

50:20  helps us a lot in our understanding of training zones. Moreover, due to the option to define additional output metrics, it is possible to get an idea how is the direction of the intensity and the interaction, for example, to duration. So, this means here you have additional output metrics. For example, you can say, okay, I would be interested to the lactate concentration, for example, which is here. If you run a set with the intensity zone five. And then you can give them additional information about distance or time, for example.

51:00  Let us choose here distance and you have a specification about 50 meters because it's different if you use zone five for 50 meters or for 100 meters or for example, for 400 meters. So, this helps us, for example, to think more deeply about how training sets should be designed and how is the individual direction for our athletes. The last cool thing is that Insight develops the training zone builder further and further. And at the moment, the follows was one of our wishes that, for example, we can

51:33  soonly define the percentage share of two zones between two markers. So, this means, for example, we have between lactate threshold one and two, the distinction of two more zones. And now we can now define the percentage of the first zone. So, for example, 50% between lactate threshold one and two will have the first zone and the upper 50% will have the second zone between the marker lactate threshold one and two. So, this also will help us for the future to have a better individualization of the training

52:07  zones for our athletes. So, then thanks again, Alex, for that one. I'm going to back to my screen here. So, this is how they use it. And you just seen the new upcoming feature of this being able to define zones in between two markers. That also means that we now include additional markers like maximum aerobic speed and maximum speed and therefore calculate, you know, other stuff. You might have noticed that we also have maximum metabolic steady state in there and so on and so forth. So, again, this is one of the most

52:52  popular features and really is used to implement, you know, these findings of the metabolic profiling into the training and actually apply that. And I think with that, yeah, this was a video from Alex and let me wrap things up with that. So, if possible, we always advocate for adding the economy testing to the test setup. If not, well, you can do it without. Many people do it without, but even Elite Federation do it without. But if you can, as you learned from Parker, it is a great addition.

53:31  Lactate concentrations and thresholds don't tell you the whole story. Like we've seen that. You can have the same, the same threshold. There's totally different aerobic and anaerobic power. But the lactic concentration let us decipher the aerobic and anaerobic energy supply mechanisms and therefore open up this whole universe of understanding VO2max, VLMx, lactate combustion rates and so on and so forth. So, for that, you get this holistic, and I just showed a few things. I didn't show glycogen availability and all that other stuff, really, to focus on something.

54:06  You get a very, very holistic and very wealth of data overview of the metabolic capacities of the athlete. And that, as hopefully I could have shown, I was able to show you this example of, and there could have been other examples of the 10 times 100 meter has a big effect on the training stimulus. And this is actually what we built the training zone builder for. So that, you know, instead of just using a max time, whatever, max time of 200 meters, three stars swimming or something,

54:42  and leave whatever the VO2max utilization is up to chance or the VO2max utilization flips that around and say, I want an interval that triggers 90% of VO2max, 95% of VO2max. I want an interval that has X amount of anaerobic energy. So instead of, again, using an extrapolation from a speed or an extrapolation from a lactate concentration or an extrapolation from a threshold value, don't do that because, you know, think about it, a threshold sits at a different percentage, for example, from VO2max, right? One athlete has this threshold at 80% VO2max

55:18  and the other one at 90% and the other one at 70%. So naturally, if you just extrapolate 20%, you will end up at entirely different VO2max values. And that's the same for VO2max and everything else. So instead of doing this, stop doing this, flip this around and say, I want a training that gives me 90% VO2max after 400 meters whatsoever. And the training zone builder, once you set this up as one of your training zones, training zone builder will spit out the individual intensity for all of your athletes.

55:46  So I hope you liked it. Almost on time. Well, you could argue over time because we didn't answer any questions yet. Surprisingly, there are not so many questions coming in. So let me call you for this again as I'm at the end of my presentation. I would really like to see more questions or remarks here from you. So don't be shy. Put it up there. I'd be happy to answer those, you know, here on the spot if you can do that. So I wait a little bit for that.

56:19  While this is coming in, again, you can also ask questions to Parker, which I'm happy to forward. We also recorded this webinar so you can review. What else? Yeah, that's I think almost it. Of course, if you're not an Insight user yet, you can reach out and get a personal demo and get your personal questions answered. If you want to find out how you can incorporate this into your current coaching or something, then just let me know. Okay. So it seems like some people came in with question.

56:59  So Igor is asking about the technique for Parker. He said that this technique was okay. Was it a visual assessment or some metrics? So I can partly answer Igor. And I know obviously where this, what angle this comes from. So Parker is using some camera systems to, and then analyzing the swimming technique. And he is, you know, using third-party consultancy to help understand, you know, or give their, yeah, give their recommendations and basically auditing the technique and give it fit be, but take on the technique. But there's not any IMU unit or something used at this

57:42  moment to, to, you know, to have some numerical insights into the techniques. This might change. So far it has been the bottleneck of limiting time to, to look at this. Now they staffed apps. So maybe there is, so there is a, so there is maybe additional value. Moxie monitor. Now we don't use any NEARS in swim testing. We had a few things that could be interesting, especially in swimming. I think when you make a hard start, like straight out of the gates to look at specific oxygenation of specific muscle

58:18  groups, the pilot that we did with that have been okay, but not super promising. So currently nothing really, nothing really is happening on that end.

58:34  Delta speed. It's the same for the critical speed. No, maybe that's misunderstanding. So the Delta speed Parker was showing, was basically saying at a given speed, the energy demand, the oxygen demand is higher or lower compared to a comparison group, which you can customize. And then instead of expressing the difference in energy, we were expressing the difference in speeds. We were saying, ah, if you use the same amount of energy, like you use, how fast, how much slower, faster would somebody be in the comparison group? So that is the Delta speed here.

59:10  Liz is asking to watch the webinar later. Yes. I answered that just now. Sorry for that. Liz, I hope you're still here. You recommend, Christian is asking three sub max efforts in the protocol, would you doing one sub max effort be enough as a bar minimum? No, no, no, no, no, no, no. Please don't do that. Don't do one sub max effort. That's by far too less. That's not good because think about it this way. If something goes wrong in that one effort, pacing is bad or most likely,

59:43  for example, lactate measurement is off, you have no way to identify that. If you have three and you make a nice lactate curve, so to speak, and at some point it dips or it spikes and say, oh, wow. And our algorithm does this automatically understand, oh, this is like an outlier and accounts for that. And so with one data point, you cannot do that. And I actually don't see the point really. I mean, yes, I do see the point, of course, if you would just be doing one,

1:00:07  then it would be much easier. But one single lactate sample after one single effort is really, really just not enough. What you can do is you can just use a warm up. Just let them swim, you know, for example, three times 400 meters or three times 200 meters if it's a slow pace. It's still pretty fast, right? You just need to take one lactate sample. It's, you know, if you practice with that, it's just 20 seconds. So no, but it has to be three. Victor.

1:00:37  Training is on to increase lactate combustion. So you mean the training stimulus that increase lactate combustion is either lowering the production or increasing the bare combustion. So the oxygen uptake. So if you mean the net lactate combustion, it's either lowering gross production or increasing gross combustion, which comes from the aerobic system. So you can do either, either, either or. Or. You can do that. You can do that. You can do that. You can do that. You can do that. You can do that. You can do that.

1:01:10  You can do that. You can do that. You can do that. You can do that. You can do that. You can do that. You can do that. You can do that. You can do that. You can do that. You can do that. You can do that. You can do that. You can do that. You can do that. You can do that. You can do that. You can do that. You can do that. You can do that. Look. No, we don't use that because we try and I didn't do that here because I tried to use

1:01:36  wordings that resonates with the audience, but a power means a flux rate. So if you use VO2 max in milliliters per minute, it's a flux rate and therefore it's a power. And there's an oxygen, an energy equivalent. You know that one liter of oxygen is approximately 20.9, 21 kilojoules of energy. So you can, you can convert oxygen into joules per second, which is essentially power. So therefore, sometimes VO2 max, even though we name it capacity, is actually a flux rate and therefore it's a power. And the capacity, it would be a capacity if you would multiply it with a time again.

1:02:16  So think about creating phosphate, right? Creating phosphate in terms of how many minimals are stored in the muscle. So this is a capacity or, and then the speed at which you can, which you can deplete it is a power. So the capacity, so to speak, is the bucket or the jar. So volume this can hold and the power is the speed at which you can empty it, so to speak. So therefore, no, we don't use this concept. And frankly, I love Jan. He's done a great job.

1:02:45  I have deeply respect for it. But scientifically speaking, this terminology of capacity and power has no base. Salah is asking, I don't see PPD or lactate has option for swimming. Yeah. So somebody is asking, they don't see swimming as an option in the Insight account. You just go to the feature store and there you have all the sports and you can just activate whatever sport you want. We just, you know, don't want to overwhelm you with all the sports. So if you've only worked on running, why would you want to see swimming every time you open the app?

1:03:26  So go to the app, go to the feature store and, you know, just activate whatever feature you want and swimming or each sport is a feature. However, swimming is only lactate testing with Insight currently. There is no PPD testing. Jens is asking, do you have information about the dependency of your metrics from glycogen store depletion? Yes, we do have that. It's not built in there. I mean, you don't see it yet, so to speak. But yeah, especially lactate production is affected by glycogen depletion. However, it's not linear.

1:04:03  So you cannot say, ah, I only have like 90% glycogen or 80%, and then therefore lactate production drops like 10%, 20%, and so on and so forth. Up to a certain point where you really have a significant amount of glycogen depletion, the lactate production is not really affected a lot. And the same goes by the way for VLMX. We did experience with sprints and microlactate concentration with partly rested, partly glycogen depleted, fully rested, and so on and so forth. And the effect, if you do it right, is not that big.

1:04:35  If you only look at the max lactate concentration, there is some effect, but even that is not huge. But you're absolutely right. In other words, if you're asking, can I do the test no matter what glycogen depleted, glycogen replenished, can I do it, you know, after eating only fat and protein for a week and training every day hard? And do I get the same results when doing, you know, after two days of rest and eating only pasta? No. The test will always reflect your current state of training, recovery, and nutrition.

1:05:07  And this is why most users test, you know, not in an artificial scenario. So not after a week of unloading and three days rest and eating only carbohydrates. Most users test more or less within a training region, a training block to get the most, you know, let's say the data which represents the retraining scenario the best. Okay. Seems like I'm running out of questions. No, there's one more from Osama. Could this be implemented in cycling and counting for metrics like power and cadence? Ah, yes. Osama, yes.

1:05:48  So this webinar was only on swimming, but yes, cycling and especially running, I would argue are the sports we work in even more, even though swimming was the very first one that was, inside was used for. But yes, we do have professional cycling team. We have amateur cyclists, recreational cyclists, professional coaches, amateur coaches, youth coaches, in cycling, running, triathlon. Parker uses it in cycling and running as well, obviously. So no, just this webinar was swimming specific, but you will see we have a lot of content and webinars about testing and running and cycling and using the data, especially in cycling.

1:06:25  I personally come from a professional cycling background in terms of coaching. So yes, you can use it all there. Don't hesitate. And if you want to see it, how you can use it, book an appointment with us and we're happy to walk you through that. Okay. Okay. Seems like I am running out of questions here. I give it another minute for you guys to send more questions if you have some. And if not, I'm wishing you already, how many tests each year should be done at minimum?

1:07:03  I see, you mean for an athlete, I assume. So usually people do three to five tests per year on an athlete, different times of the season. Sometimes they do a little bit more as a spot, the one additional as a spot check. If you know, like Parker explained, you have some suspicion that performance is not great, but mostly around three to five per year is approximately. We have some people who do it every eight weeks, so approximately six times per year. But that's not in the most cases.

1:07:40  I would argue it depends a lot on, you know, your ability to set it up, logistics, time and so on and so forth. In running and cycling, we do have some PPD testing, which we just updated last week, I think, so recently. And therefore, you don't resist testing. You don't have to be on site for the athlete. You can just use a series of all out efforts. And therefore, this is often done a little bit more often because it's logistically administrative easier. But like testing, I would say three to five times a year.

1:08:13  So with that, again, thanks everyone for staying on. Stay tuned for more updates and reach out to, you know, look at it for yourself and find out how you can use this for yourself. Ask additional questions and so on and so forth. With that, have a great evening. Good afternoon or good night, depending on where you are. Thank you.