THE PHYSIOLOGY BEHIND WINNING THE TOUR DE FRANCE: FROM DATA TO ACTION

0:00  So being a bit mindful of the time we have today, I'd like to start with the presentation. So thanks again for joining and feel welcome to this webinar about the Tour de France. So just from a practical perspective, my talk will be like 45 minutes for the presentation. And afterwards, I take all the time needed to answer your questions, so feel free to put your questions in the chat or in the Q&A section and happy to answer them at the end of the presentation. So hopefully, I wish you a great afternoon for European based learners in this webinar,

0:45  or morning or evening, depending on where you're following this presentation. Hopefully we get some interesting discussions afterwards. So let's start with showing some data. And I'm really honored and pleased that so much people are joining this presentation about winning the Tour de France and learning about the physiology behind this amazing performance of winning the Tour de France. So I'll definitely show some big numbers today. But maybe a bit more important than just only showing some numbers is really to get the learnings from it. What can we do as actions in training, talent identification and other applications that

1:32  can be used. So of course, the Tour de France, and that's maybe the reason why so many people are joining this presentation. It's one of the most iconic cycling events and professional cycling. So that attracts a lot of curiosity. And especially this year, we had an amazing addition of the Tour de France with, for instance, the technical sections, technical stages on gravel roads with an amazing Jasper Sturven. I'm a Belgian sports scientist, as you might know. So I'm a bit biased here to mention Jasper Sturven for the stage.

2:07  He did a really big effort in this stage. Unfortunately, he didn't win. But also in the sprints, we have seen amazing sprints, time trials, and of course, the performances of Saudi Arabia and Jaguar are really amazing and worth analyzing and seeing what we can learn from those performances. Which is interesting. Just maybe to make sure about the objectives of this webinar and some learning objectives. Of course, we are presenting some numbers here about Tour de France performances. So that's the start of the presentation. But we try to find out which physiological requirements are behind those numbers to better understand.

2:59  And that's maybe the major topic for today, to really understand what's needed to be able to perform at this amazing level of performance. And last but not least, some practical applications, what you can do in training and maybe in other possible applications with the methodology we used in this study. So let's start with the numbers, or at least with some numbers. And which is really nice these days is that a lot of riders are sharing their numbers of training data, racing data. And it's really interesting to look at those power numbers, especially the power output files

3:38  are shared on their Strava accounts or on social media. And just as an example here, one of those files that really struck my attention here is the power file of Alberto Contador 2009 during a 20-minute all-out training test on a climb. And he averaged like more than 450 watts, which equals 7.4 watts per kilogram, which is, as most of you will definitely know, an amazing, amazing amount of power he produced. So no surprise that he was one of the best riders at that time. A different type of rider is Mathieu van der Poel, for instance.

4:21  And I took this one as an example, an example of stage 10 in this year's Tour de France, when he did the lead out for Jasper Philipsen in the sprint. And again, he showed his numbers. It's a completely different type of effort, of course. But again, we see amazing performances as well. So please don't underestimate the efforts domestiques are producing while performing their tasks in the race and sometimes a bit in the shadow of their leaders in the team. But anyway, they do a lot of athletic performance during these efforts.

5:01  So interesting data as well. And to summarize a little bit like here, Richard Carapace also in this year's Tour de France in the 17th stage, did as well like an amazing 20-minute effort on a climb, almost 400 watts, which means for him like a 6.4 watts per kilogram. So you see a lot of numbers, you see a lot of amazing numbers, big numbers, but also you see that these athletes have different roles in the race. So when we look at the GC contenders in the race, then we have to look a bit differently and look maybe on those stages that make a difference in the Grand Tour.

5:42  And that's mainly like time trials and climbing stages. So that's why I search for data in climbing stages. And this one is an example of Jonas Finnegard in the last year's Tour de France 2023, the fifth stage, when he climbed the Col de Marie Blanc in an amazing 22 minutes, 56 seconds, which when you try to calculate from that time and knowing like body weight and the weight of the bike equipment and stuff like this, you can calculate the power output needed to climb this or to perform this effort.

6:20  And when you do so, then you arrive at the power output of 6.9 watts per kilo, which is again a very high number of power produced during the stage by Jonas. And of course, I couldn't give this presentation without showing some numbers of the Depodiacar this year in the 15th stage of the Tour de France. You might remember that it was a stage with five heavy climbs and in the final climb called the Plateau de Bay, which he did in an amazing 39 minutes, which if I remember well, was a new record.

7:04  The previous record was from Marco Pantani, who covered the same distance in like 42 minutes or 43 minutes. So he shaved off like more than two minutes of this time. And again, we can calculate from this time and knowing the characteristics of the rider and the climb itself, a power output of like 455 watts, which is an amazing 7 watts per kilo. So you see that we are showing today some really big numbers, but we have to be a bit careful. And of course, this evidence of this information is really interesting to read and to be impressed by it.

7:44  But more importantly, what can we learn from it? So we have to be a little bit careful and I'm not. Yeah. We have to be careful that the data that has been shown is only the data they will show or they like to show. So it's all always a fragment of the big picture, so to speak. So it's important to know that it's important also to know that. Yeah. How much trust can we have in this data? Also the type of power meter. And I go a bit into the more methodological questions here.

8:22  But again, this is really important when you want to calculate physiological requirements from power data, then you should be confident that the power data is valid. So that's why I put these questions here. So what's the type of the power meter? Not every power meter is as accurate. So we have to be aware of that. And also some power meters are quite sensitive to changes in temperature, which means if you have, for instance, like a climbing stage and you calibrate the power meter in the valley, it's 25 degrees and then you go up the hill.

8:59  And it can be the case that when you're on top of the hill, the temperature is five degrees lower or seven degrees lower. And this change in temperature might affect the power output readings. So you have to be very mindful of those influences that can impact power and can impact also the validity of the data presented in the social media posts. Was it the power meter calibrated properly? So I don't expect that there will be big issues because we are talking professional cyclists here and they do know very well the importance of having good racing and training data.

9:39  So I expect that they will do according to the manufacturer recommendations. But again, you don't know. So there can always be some issues here. Last but not least, if it's racing data, in most cases, even not maximum performance. And that's maybe a bit strange to hear when we talk about racing and when we talk about fighting competitors during a race, then you expect to see maximum performances. But that's not always the case. And the reason why that is can be from a technical point of view. For instance, if you analyze the training data of a domestic is a very different role in the race than the leader of the race or the leader of the team.

10:24  So racing tactics can have an impact on this. Also, when you perform at the beginning of the race at the maximum effort level, then you will probably not finish the race. So riders are very mindful for that to have always something left in the tank for the final of the race. So also fatigue can influence power data as well. So there are many confounding elements here, which makes it a bit tricky to calculate a physiological profile from this type of training or racing data. So maybe we should look at the different source of data and then I'm a sports scientist.

11:11  So it's not a surprise that I look into science and see what we can learn from scientific data. And the good thing about science is that the requirements of scientific publication is that you have to explain how you capture the data. You have to explain what you did to maximize the quality of the data. So at least you have some information about that and then you can make your judgment as a reader of these kinds of reports. If you can use that data for further analysis. So I took some data and this one is from a paper published in 2012.

11:55  2012 so that's already almost 15 years ago from the research group of Lucia. We did like an update or did like an analysis. How do those different stages in the two the front look like from a physiological and performance perspective? And as you can see, they made like three types of stages. And the first column you read some characteristics of a flat stage mostly in the beginning of the tour, more like sprinters stages. And then you have the high mountain stages for the tour. It's more like in the Pyrenees and in the Alps.

12:33  And of course, the time trial stages as well. So you see different characteristics when it comes to racing distance exercise time, as you can read on top of this table. Also like the average racing intensity, which is relatively low to moderate for the flat stages, but it's really high. And in the mountain stages, of course, and in the time trials as well. Average velocity. So you can read those numbers here in the table and also on the bottom of the table. You get some idea about power output requirements, which struck me really of which struck me.

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26:11  the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is

26:41  is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important

27:11  the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is that the most important thing is

27:41  so I check a little bit so I check a little bit if I can see the results of the poll so I don't see it I'm not sure if you see it in the group but anyway I can give you the answer and then once you are read the paper I published a couple of weeks ago then then you know but let's dive a bit deeper into this question and see what the reason is that Oscar from in my opinion will definitely win the tour de France and Oscar Svensson unfortunately despite his high aerobic power is maybe not equipped to do

28:38  so so so let's dive a bit into the research methodology I've used here to answer that question so I used in those both publications I used the data set that's in there and I have calculated metabolic profile as you can see I've used inside for that purpose and there's really nothing magic here that's something every inside user can do so it's quite easy to derive that information from from software and then you get a complete metabolic profile and the second step was to analyze the data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's

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30:48  and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a

31:18  data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a lot of data set that's

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32:18  you can't win there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there and then you get a complete data set that's in there

32:48  not really an issue I think for the professional writers here and then I've chosen as the second type of stage climbing stage which was one for a backrest room and allowed me to get more data about certain aspects of this stage I use for instance this his performance in the climbing aspect in the final stage and the final 70 kilometers climb I use this data I use this data for calculations this is the mathematical model I used to derive power the p on the left of this formula to drive power from speed mainly from speed I don't go into every detail of this formula it looks quite complicated it's not that so much to be honest you can read all the details in the paper I've mentioned

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36:48  So the solid lines are the data from Froome and dashed lines for Oscar Svensson. So for Froome the power output he produced in the time trial at almost 440 watts equals 0.45 millimoles per liter per minute that you can read on the y-axis in this graph lactate accumulation. So for Oscar Svensson it's just a bit higher that you see when we use his power output at the 460 watts and look at the dashed lines here then you come just above the 1.5 millimoles per liter per minute lactate accumulation. So from a starting level of let's say 1.5 millimoles or 2 millimoles they accumulate every minute that amount of lactate and will end up for the stage with a calculated

37:40  blood lactate concentration of 12 millimoles for the junior and 10.6 for Chris Froome. So these values in my opinion are quite typical for this type of efforts. We of course don't have their maximal values they can perform so it's difficult to say for instance in the junior if he can indeed accumulate that number of millimoles and of course we'll be able to do time trial at that speed but it's very likely he would be able to do that for of course Chris Froome he finished the race so he did so we don't have to have that question for him which is from this data to be concluded is at the same speed Oscar Svensson at a slightly higher lactate accumulation rate compared to Christopher Froome and my guess is that he would be able to produce the same speed because the value at the end of the time trial is

38:38  is a 12 millimoles which is I think a possible value. So to sum up who is going to beat Chris Froome so I give him a zero he didn't want the time trial he was I think not at its best at that point I don't remember anymore the reason why but it didn't want so I give him a zero I'm sorry for the Froome fans here and as Svensson probably didn't beat his opponent in this virtual race I give him a zero as well so we have we have a draw here

39:17  so let's look at the second stage that's the climbing stage remember if you have seen the course profile we had a flat it's not really completely flat it was a bit up and down or some smaller hills along the roads and I estimate that Chris Froome was well protected by his domestics so it didn't have to go to ride into the winds and produce lots of power so he could do at a relatively low power output and what I calculated here is the 270 watts that you can read in the first section of this table

39:52  this corresponds with a carbohydrate utilization of 150 grams and a fat utilization 270 grams for the same speed and same conditions I did also the calculations for Oscar Spencer if he would have been in the in the peloton and you see the numbers are a bit higher when it comes to carbohydrate utilization so we have 216 watts here at 216 16 grams here but almost a similar value for fat utilization that's maybe not the most interesting part because you have a big bunch and you're approaching the hill and then the race the fight is going on on the hill as you remember Chris Froome won the stage so that's I think a really valid performance to have a look at

40:36  so we have speed that he produced to climb the hill based on that speed we can calculate power outputs you've seen the formula I've used here 370 watts average equalling like five points almost 5.6 watts per kilo when we look at the carbohydrate utilization they would have burned 203 grams of carbohydrates and 55 grams of fat utilization honestly I don't mind too much the fat fat utilization because fat is never a limiting factor in an athlete even if you have a very low body fat percentage you still have enough

41:20  fat stores in your body to fuel these amounts of fat utilization so I'm not much interested in fat utilization per se I'm more interested in carbohydrate utilization because that's a really limiting factor you have a limiting amount of carbohydrate stored in your body and you have a limited ability to consume during race meaning that once the tank is used that then you can't perform anymore at the required power output so that's why we are focusing here on carbohydrate utilization and the junior if you would have done the same speed on the climb he would have burned 360 16 grams of carbohydrates so the question here is is this limiting their performance and if you add up those values then it's still within their available glycogen content so maybe it's not like a limiting factor here for both riders

42:25  so maybe you're interesting how I derived those numbers I use this graph this analysis for that purpose this requires a bit explanation I guess so what you see on this graph on the x axis is the power output and on the y axis you see you see in kilocalories per hour or in grams per hour you see the utilization of carbohydrates and fat so the green curves are representing fat combustion the red curves are carbohydrate utilization curves again as in the previous slides the solid lines are the data from for Chris Froome and the dashed lines

43:07  is representing the data of Oscar Svansson so when you look at the green curves you don't see much difference especially in the lower power outputs are below 300 watts it's almost identical values so again first of all I'm not that much interested in fat combustion because it's not a limiting factor and if you compare those two graphs it's not a big difference regarding fat combustion which is more interesting to look at is the carbohydrate utilization rates and in red here in the curve and it's clear that Oscar Svansson is using all the time at any power outputs more carbohydrates than Chris Froome so Chris Froome is a bit more economical with these carbohydrate stores compared to Oscar Svansson

44:03  so at the same absolute power outputs Chris Froome at lower carb combustion rates compared to Oscar Svansson but again if it's the question here is is it a limiting factor yeah you can maybe need more carbohydrates but if you can have enough carbohydrates stored in your body and can can eat enough then it's maybe not a limiting factor and that would mean that Oscar Svansson could beat Chris Froome on the climb so let's let's dive into that question a bit more in detail and for this reason I pictured this graph you have in blue the data for Oscar Svansson in green you have Chris Froome's data and you see the carbohydrate utilization in the dark bars and the available glycogen in the light bars and as you can see for both riders the carbs they needed for that stage

44:59  were lower than the available glycogen so you can theoretically say that they even have not to eat to have enough carbohydrates to fuel the stage and a practical context and definitely I would not recommend to stop eating in a tour de France the opposite is true you should eat of course to start already fueling your body for the stage and maybe also preparing for recovery afterwards after the stage and preparing for the stage so eating is definitely important in the next stage so eating is definitely important in the tour de France so that's why I also considered what would be the total available carbohydrates meaning that you add up the glycogen and you add up what you can eat and that sums up the available glycogen and that's been shown here on your right side so

45:54  again in dark you see what is needed for a stage and you see also in light what is been available but not used so to speak and that's the sum of the glycogen stores and the muscles and also what you can eat during the stage and for that reason I used carbohydrates consumption rate of let's say 110 grams 120 grams which is nowadays like a standard approach in professional cycling and from that amount of glycogen and from that amount of glycogen and from that amount of carbohydrates I calculated the utilization of 90 grams because it's not if you eat those amounts of carbohydrates that's all these carbohydrates are available for your body so there's a certain percentage you should consider here and that's why I used the 90 grams as a

46:41  the available exogenous carbohydrates so but still Chris room on the stage so he gets a one for me and Svensson could have beaten him maybe so he gets a one for me as well but we should question maybe a little bit points awarded to Oscar Svensson here maybe not for the stage but as you probably know a lot of stages have much more climbing altimeters than I've been shown here in the in the stage of the study so for that reason I did an extra analysis so what is on this picture is on the x axis you see the amount of altimeters for stage going from 1000 altimeters to 5000 which is a crazy mountain stage

47:28  and on the y-axis you see the amount of glycogen and on the y-axis you see the carbohydrates here the solid lines are representing the available or the I'm sorry are representing the carbohydrate needs to cover the the climbing distance and the dashed lines is the carbohydrate availability in relation to the climbing distance and blue again for Oscar Svensson and in green for Christopher Froome and what can be seen from this analysis is that from a certain amount of altimeters the need for carbohydrates will be bigger than the available carbohydrates in the Oscar Svensson case so he needs so much carbohydrates during those type of efforts that at certain points of altimeters he will not be able to do because he will have run out of carbohydrates and need to reduce

48:24  reduce cycling intensity or even stop stop the effort and this is not the case in Chris Froome so when you consider the context of a grand tour you will definitely make the conclusion that Chris Froome with this metabolic profile here presented is better equipped to win the GC than Oscar Svensson who is in some cases on some stages will be in in trouble definitely so let's sum up a little bit the learnings from the study here and what we can do in training so what it takes to win the GC you need an amazingly high aerobic power that's without any doubts

49:07  any doubts VLMX values it's not the more the better in this case as you have seen here with the two cases Oscar Svensson outperformed in VLMX Chris Froome but at the end of the day he needs more carbohydrates and at a certain moment that will limit his performance capabilities in a grand tour context so you don't have to have VLMX values that are above those 0.4 it's our ballpark numbers of course but that's the direction we are thinking of that's the direction we are thinking of we haven't talked about today about gross efficiency but what can be derived from the data here in both cases is that the gross efficiency in Chris Froome was also way better than in the Oscar Svensson case remember that he was still quite new in the sport at that time of capturing the data so he was an alpine skier he retired from that and

50:04  was competitive in road cycling for only couple of years so he didn't develop all those skills needed to be efficient and in a peloton for instance and to have an efficient cycling pattern so that needs more training so that's why his values were a bit lower compared to Chris Froome also body fat percentage we didn't stress too much on this today but Chris Froome was more leaner than Oscar Svensson and that's very important in grand tours to be lean in a healthy way of course may not harm your health and of course and because you need to perform three weeks without any problems here health based so

50:56  Chris Froome is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so on this is a little bit more on this and so

51:26  what the amount of carbohydrates is that your body can burn during the effort and that's more or less 75% of what you what the intake is of course we have focused today on the physiological requirements but we all know that to be able to win the GC in a Grand Tour there's much more things needed like you you need a strong team you need support from that team you need that high performance culture and the team mental strength tactics racing gear also be healthy stay healthy during the race and the three weeks of racing recovery management and so much more things you need to have in place to be able to win the GC so it's it's of course way more than just physiology but again physiology is a big part of this picture and especially gives you the characteristics of the possibilities to to perform

52:22  so having these numbers in mind and having the numbers of oscar svensson in mind so what would you do as a coach if you oscar svensson knocks your door and he says i want to win the tour de france so what should he do in training i think that's a quite common question we have as coaches or sports scientists what should i focus on to to be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a

53:18  GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that would be a GC contender and that

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1:02:48  hopefully you have now the information to see that it's more than just Viet to max here in this game of winning the Tour de France or any other Grand Tour it's the full metabolic profile you need to consider and see in a more holistic way what's important to win to win the GC or at least to be competitive to win the GC. So there's a lot of the GC. There's a lot of stake here and a lot of elements that isn't important. So I'm checking here how was VLMX measured on the two riders so it wasn't measured so we used published data that's a question from Lars Johansson so we didn't measure it we derived it from the calculations and we could derive it because there was a V or two max value we could use and in both cases

1:03:39  if I remember well there was a power output and the formula like that concentration so you can use the lactate protocol in our software to use those data and get a VLMX value out of it. So that's how I approach this and how I calculated VLMX. How is gross efficiency measured? Thank you for that question. It's an interesting one. It was published in the paper of Chris Froome. So there was a value into the data set which I used. In case of Oscar Svensson, I did a bit differently.

1:04:21  To be honest. So in the case of Oscar Svensson, it's calculated value. So what I did is based on the available data sets, what are the settings that I need to adjust to get the best fit of the data. And to get a good fit in data. And to get a good fit in data. I needed to adjust gross efficiency. I had to lower it down to 21.1%. So again, it's a calculated value. It's not a measured value here. I hope that answered the question. A question from Juan Carlos Hernandez. What intensities would you use an interval time in talk training? That's an interesting one. Personally, I don't use it a lot. So I can't speak from my own.

1:05:15  I'm coaching experience. At least I use it in very specific cases. Almost only in an Ironman athletes to indeed try to get VLMX at desired value. So I use quite long efforts in this case, and I'm talking about professional Ironman athletes. So there will be intervals like starting from 10 minutes and building up into the 20 minutes. Into the 20 minutes range. The intensities will be between fat max and maximum leg steady state somewhere in the middle to also challenge those fast, which fibers in that effort for a long time. And that's what you aiming at. You'll want to train those fast, which fibers to be more oxidative. And that's a bit the idea behind the strain practice.

1:06:08  Again, we don't have scientific data to support that idea. But we do have a lot of training experience by experienced coaches that confirms that. So we need more science to be honest. So it could be an interesting scientific topic to dive into that and give maybe more training recommendations about the training practice. And your opinion, how much do you think the central government model comes into play in the onset of fatigue and grantor?

1:07:12  And you see it's one of the first one. And you see it every day now watching the Olympics, for instance. You see how it works. You see how it works. One athlete is able to support pain more than other athletes. You see what's going on in their heads. And that's a bit what differentiates one athlete from another. And that's not about physiology. It can be physiology. But at that level, sometimes it's more like mental strengths and how you can cope with some pain sensations and stuff like this.

1:07:49  So indeed, it's you have to analyze performance in a holistic way. And of course, the topic for today was more from a physiological point of view. But it's not the first to admit that it's not the only thing that matters. And there's many other aspects in performance that's important once you're fighting for the metals. What format you can use? Hopefully that answers the question why. What format you can use to make your VLMX better in training? And do you need specific food before that training? So VLMX is a is a measurement of glycolytic.

1:08:28  Flux rate, glycolytic power. So what it means that is the higher the value represents the ability to produce a lot of energy from the glycolytic system. Tried glycolytic system, the name says itself comes from carbohydrates. So when it comes to feeding strategy, you should be well loaded with carbohydrates. So indeed doing this in a training low strategy is, in my opinion, not recommended. You should be. Well fed with carbohydrates before this type of training. What type of efforts you use. And I can refer to information on our website to get more details about recommended training strategies.

1:09:12  But in general, briefly, we can say that you need short efforts. And that's in the ballpark or twin 10 to 20 seconds. With long rests so that you are able to perform every interval at a very high intensity, almost maximal intensity and challenge your glycolytic system maximally. That's what you want. If you shorten the rest or if you extend the sprint, then you will increase very high proton accumulation. So your pH levels drop down and that's impairs glycolytic flux rate, which means that your glycolytic system will not perform at its highest value.

1:09:56  And it's therefore not as effective as if you do shorter sprints with long rests. So that's my recommendation for this type of training. How do you lower VLMX? That's the opposite, of course, how you can lower it again. There are many string strategies to do so, but I must admit that we don't have a lot of scientific information to support those strategies. So that's definitely worth to investigate how we can manipulate VLMX with specific training to lower it or to increase it. But to lower it, if you know how to increase it, then the opposite you should do to lower it.

1:10:36  So train low can be a strategy. So train with low carbohydrate stores, challenging it less, meaning that you train at a lower intensity level and accumulating work, doing a lot of low carbohydrate stores. Doing a lot of low intensity training might help and some athletes be careful with a lot of sprints or with strength training with 10 to 20 repetitions, for instance, which will also challenge at a certain point your glycolytic system. So all those aspects can help to lower down VLMX. So that's a good question.

1:11:11  So that's a good question. So that's a good question. So that's a good question. So that's a good question. So that's a good question. So that's a good question. So that's a good question. So that's a good question. So that's a good question. So that's a good question. So that's a good question. So that's a good question. So that's a good question. So that's a good question. So that's a good question. So that's a good question. If you implement strength training and you want to control VLMX that it should that it's not increasing, then you should implement strength training that it's not challenging your glycolytic system too much.

1:11:39  So what can be done here is to use high loads, a few repetitions, lots of rest. And that's that's maybe the way you can approach that. So high, like, maximal strength training. And so you do a treat for repetitions and use a lot of rest in between. Then you will not challenge your glycolytic system too much. And then you shouldn't be afraid that you you're increasing VLMX in this way. Depending on high torque training, then you should be mindful about the training intensity here and focus a bit more maybe on the training duration or the amount of work you accumulate with those high torque.

1:12:16  sessions. It's maybe more important than the intensity here and especially stay away from intensities above maximum lactate steady state because then you will the more and more introduce VLMX into your sessions. So stay away from that. And that should be, I think, the good as a strategy to keep that VLMX value as low as possible. So that's from VLMX of 0.38 refer to a certain period of the season. So I don't know. Probably yes. So why I say I don't know because I don't know. I don't have the data during the whole season, so I can say I can't say for sure.

1:13:02  But I've used the data again. I use the data that was published and available in the paper from VL. So, and I calculated, I derived VLMX from that and arrived at the 0.38, which is if I see another athletes, a specific like marathon runners and long distance athletes, Ironman athletes, it's like a typical value for this type of athletes. So it seems to me that it's a valid number. And also when you calculate with this number, what I've shown in the presentation, and then you get realistic results from it.

1:13:40  So in my opinion, it's like a good number. Can it be much lower? So it's lower like 0.25 and 0.3, maybe, maybe in the Tour de France, maybe at the end of the stage race in the third week, maybe because of the accumulated work can be a stimulus to that. It's drops a little bit. So that's a possibility, but I can't answer for sure. And I'm not sure if it's will help performance on certain aspects. It will. You will use less carbohydrates, for instance. And that's an interesting one, but maybe, and as we have seen this year in the Tour de France, to anticipate or to react on accelerations on those climbs to be able to cope with project car, then you might need some VLMX to do so to get those numbers there in those accelerations.

1:14:34  So I'm not, I'm a bit hesitating to go below 0.3 because the race dynamics require a certain explosiveness. And that's, yeah, you can't do it without a certain number in VLMX. How would you maintain VO2 max in Oscar without triggering VLMX? That's a nice one, especially when you want to apply high intensity training to increase VO2 max or at least stabilize it, which is a powerful method to do so. It's been shown in many publications that you can, that you can increase VO2 max even in well-trained athletes with high intensity training.

1:15:23  So that's, that's been shown many times. Uh, but again, the more intense your efforts, the more your challenge or glycolytic system. So you have to balance a little bit what the priority is. Do you want to improve VO2 max? Maybe the downside is in this case, if you use high intensity training, that VLMX will increase as well, or at least not lower down. So you have to be careful with those shorter high intensity efforts or repeated sprints. I should be careful with those and maybe choose like more than longer.

1:15:56  It train sessions, uh, two or three, four or five minutes intervals, uh, at the bit lower exercise intensity that you can at least accumulate a lot of work in the zone. 90 to a hundred percent of your VO2 max. That would be, I think an interesting way to approach this. Can you explain the car, please first, the altimeter calculation, but more, I was a bit fast maybe on that one. Um, and, uh, I was a bit mindful as well for, for the time I was approaching one hour presentation.

1:16:31  Uh, so that's why I was a bit faster on that one, but I can indeed explain. So what I used here is the racing speeds from that specific case I've explained. So from that speed, I know how fast they go from a certain altitude to the finish line. I use that same speed to do the calculations for that graph. I've also calculated what a carbohydrate combustion rate is. And we can use the available glycogen. Add up what you can eat during the efforts. And I remember the 90 grams per hour, add that up.

1:17:12  And then you, you come with a, an available glycogen number. So that's how I build those graphs. And because if you have more altimeters, you have need more time to cover that. Uh, those altimeters. So you can eat more during those, uh, during that time. So the availability goes, or goes higher. But as you have seen in the Svensson case specifically, your needs increase as well. And you see that the need is increasing faster than your ability to, uh, to eat, uh, the carbohydrates. And that's why at a certain altimeter, the two curves are crossing and meaning that Oscar Svensson is getting in trouble.

1:17:54  So I know that it's a bit like a game what I'm, I'm playing here, but at least I think it's, it's, um, an example, how you can approach data and how you can benefit from that data to answer specific questions, which are very practical and meaningful. I think for the case in, in grand tour racing. Hopefully that's answer your question. James. Um, the topic about fatigue resistance is an interesting one. Um, it's an interesting one. I think we, we like scientific information to really get a good grip on that concept of fatigue resistance.

1:18:38  At this point, I know there's a lot of information going out and there's a lot of attention to this concept of fatigue resistance, meaning how much of your maximum performance is still available. Even if you're fatigued. Uh, and we see that there's, um, that we get some power data about this concept, but what is missing now is the link with the physiology. To be, to be honest, I think we are missing some physiological data. So I don't know if I can answer, uh, uh, this question. At least I can't, uh, demonstrate with scientific data.

1:19:15  Um, there's in my, uh, knowledge only one paper out, but I am not remembering the author of the paper anymore. Uh, that fear to max it's related to the amount of fatigue resistance, meaning that athletes with high fear to max numbers have less fatigue resistance, which is quite logic. Uh, maybe, uh, as the aerobic system is an important one, uh, to enhance recovery. So, but more data is, uh, to my knowledge, uh, not available yet. So that's another topic to, for the scientists here to, uh, to investigate in more detail.

1:19:55  So I'm checking here more questions. Uh, Tom, if I have magnitude of the car. What magnitude of decrease can you expect for Svensson with appropriate threshold, high torque training and over which timeframe, uh, months, years? Um, I'm not sure if I get this question. Um, well, um, it's about, I think what's, uh, questioned here is about, uh, the speed of adaptation. And that's a very individual one. That's why we need to monitor at regular times, the metabolic profile of our athletes to, to get those data because it's, it's, uh, it's not predictable.

1:20:42  It's not well predictable. The speed of training adaptation. So my recommendation here is if you want to be sure about training adaptations, you need to measure, uh, regularly. Um, hopefully that's a bit of an answer to that question. We're shifting from zone two to more zone three training to reduce VLMX, reduce, maintain, or increase base aerobic fitness. Um, that's a question from Gabriel today. Oh, uh, that's, uh, an interesting one. And we have, I think, uh, some nice resources and previous webinars about those different training zones and training models here and the effect on metabolic profiles.

1:21:26  Uh, so please, uh, if you want to have more details, um, about this topic, you can check out our resources on the website. In my opinion, any type of training can have the potential to increase VLMX. Uh, not all, all type of training, uh, the potential to reduce VLMX. So that's different ball game here, uh, to manage VLMX. That's what I've discussed in previous questions. Um, you need very specific, um, training sessions to increase it. You need short sprints to decrease it. You might need, uh, more aerobic work, uh, maybe a little bit more.

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1:22:33  the validation plan is what the objective is what type of racing you're preparing and that's different if you want to run 1500 meters on the athletic track compared to winning an Ironman race or winning a GC in a Grand Tour so there's so many contexts here that it's difficult to to answer that question another one if Oscar starts preparing for the Grand Tour should he start working on reducing VLMX at the beginning of the season or closer to the race that's that's not a nice one definitely closer to the race you should achieve the desired numbers how you approach this and what your training strategy is

1:23:18  that's that's more like a coaching philosophy in my opinion and as a coach you take your decisions based on your data and they and based on your knowledge of the sport and based on your experience and your your experience with your athlete for instance and how he or she responds to certain training methods and I think that guides you with type of periodization you will implement but I can't give you I think and one size fits all the answer to that question so we are now approaching to really the coaching approach which is

1:23:56  science informed in my opinion and data informed but it's you can't predict it like you can have in a mathematical model so to speak so it's more like a coaching philosophy you want to implement and indeed we see that a lot of coaches try to fine tune that VLMX value more towards the competition and are not so worried about it in a general preparation phase and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's a lot of coaches and I think that's

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1:27:23  you want to see if you want to lower down here to the LMX then it might be a bit more challenging and what I do in these cases is to use like the longer interval efforts so I stay away a little bit from those very high intense efforts and the short ones like 30 seconds effort 30 seconds recovery and this type of effort so I stay away a little bit from the type of training and I use like longer longer boxing train so that's what I use to manage that scenario

1:28:00  can you share some tips on how you do lactate shuttling workouts in terms of rate of lactate accumulation you tolerate

1:28:08  that's a big question here and an interesting one lactate shuttling workouts so what it's meant here I've meant here is that you create a workout that your body's challenged to use accumulated lactate use it as a fuel so in most cases you design a training session like an interval workouts where you increase lactate concentration so you do an effort above like the steady state and after that accumulating work you add like a steady state effort so that's the general design of this type of work again you can use the software to really design that effort to the profile of your athlete so it's difficult to

1:28:59  give here one size fits all approaches so I will definitely recommend to use that lactate accumulation graph to design this type of efforts so that at the end of the training session the athlete is still able to perform the required work and indeed there is a kind of a risk if you don't be are not mindful for the lactate accumulation here in the start of work that you end up with a session that it's not doable because it's going too high in lactate accumulation and the athletes need to stop because of early fatigue so it's it's a bit of managing lactate accumulation and also the lactate recovery between your efforts

1:29:38  so that it's able to perform the entire session for that specific athlete so you need to tailor it to the metabolic profile of the athlete what do you think about remco's physiological values are able to do it tt and gc um i hope he will i hope he will because i'm a belgian citizen so i'm a bit biased here and i wish he can and i think he has still potential and i hope as a supporter of this rider that he can still improve and he was already quite close

1:30:16  i think he did a good job to be mindful of his own strengths uh to get the best out of his performance at the to the front i think he did very smart to the france and and get the most out of it in the situation he was in um i haven't done any calculation yet so that's something on my to-do list because of curiosity because i like to know that and uh we are currently working um on some calculations about olympic games efforts you might have seen that about grace brown's uh time trial efforts so we are now focusing a bit our um

1:30:54  our attention to the to the olympic games here to do similar type of of calculations and it's really interesting what i've shown also in my presentation that you can use the racing data to get an id it's maybe sometimes a rough estimation but you get at least a good idea and what our software allows is that when you come to a metabolic profile that it's um it's always a like a logic metabolic profile so it's impossible to arrive with a vo2 mag that is sky high and and and not com uh compatible with with

1:31:28  uh with the steady state effort for instance or the vlmx effort so it's always the data is always compatible with each other uh which is uh interesting and nice uh as an outcome from from the software so that's that's a work in progress i would say what's the highest feeling max number that sprinters may have in the tour to still survive in in the mountains i think that's a good question my colleague sebastian weber would be able to answer um so i'm i've personally no experience with this type of of

1:32:02  riders uh about i would i would say that we are um looking at numbers like a 0.90 uh 1.0 vlmx number but that can only be um tolerated if your vo2 max is also very high so don't forget that those um athletes those sprinters are still endurance athletes they're not pure sprinters they are endurance athletes with very high view to max numbers otherwise you don't survive you will not arrive in time on the climbing stages if you're not have those big fear to max number to balance out a little bit

1:32:42  um those high vlmx numbers so high view to mix helps to use more fats in your uh in your efforts but you know as well from today that vlmx high vlmx will will promote carbohydrate utilization and if you combine both it's it levels out a little bit so you need a high view to max to survive the mountains and the tour de france as a sprinter so that's a training priority um for any uh professional athlete and and starting

1:33:18  with such a low percentage time difference of three weeks of to the france racing especially when even stage time bonuses play a role or these very slight physiological differences critical since there's more example of theater mag that reflects potential but has not been proven in competition indeed uh he's already retired so that we we don't have proof of of uh of it uh unfortunately it made different decisions in his in his career um so i continue reading here fortunately the minor marginal gains of what we're going to do is what

1:33:52  makes a difference in a three-week event so could mature on the pool into the france uh and so that there's many questions here um hopefully you have um taken from my talk that physiology physiology is an important one to win the tour de france if you have a 50 v02 max then you're not able to do any uh stage in the tour de france so you have to have those minimal abilities from a physiological point of view and these are very high it's it's high level sports it's it's extremely high level it's extremely high

1:34:32  level and the bar has risen in my opinion what we have seen this year into the france has never been shown before in my opinion i hope i can support that with some calculations uh later on but uh it was an amazing tour de france uh what we have uh witnessed here uh but again it's not only physiology there is a lot of other things in stake uh as i've um mentioned in in my uh take home message if other riders can win it to the front uh yeah probably maybe depends of course about what they personally want to achieve in

1:35:06  their careers and in some athletes it will be very difficult i think because they don't have from nature their the makeup to to the the profile to win it to the france like matthew van der poole is very explosive which is not ideal to win the gc um but you never know if you remember lenz armstrong he was like a class rider in the beginning of his career but he turned up in in a gc contender at the end of his career um so yeah people can change people can can train towards a specific profile and and you

1:35:41  never know what's what's possible um it's very difficult to predict your training adaptation it's in my opinion very difficult to predict that so if you want to do that you should try and and see what it gives and and and monitor your process uh to finally decide if it's uh like a realistic uh project or not um would you consider training in the fat max as low intensity or is that too low for some athletes with moderate vlmx values interesting question and i would like to refer to more information that we have

1:36:18  on on on the website about this topic it depends on it depends in some athletes the the and now i'm referring to like hobby athletes recreational athletes with relatively low vlmx values they sometimes struggle to stay below fat max during their training sessions because their aerobic conditioning is too low if you compare the other side of the spectrum like the athletes we are discussing today like the very best professional riders in cycling then training lv at fat max is already a big effort and they're pushing 300 watts and even more and some athletes that's that's already pushing the paddles

1:37:00  so it really depends on the the metabolic profile of your athlete what it means that fat max power outputs and in science we don't have that nuance uh in general and we see that everything above below fat max is considered that low intensity or moderate intensity and everything above is like considered high intensity training but as a coach i think we should have more nuances in that interpretation and i think and look at the entire metabolic profile of the athlete to to make that judgment

1:37:42  a lot of questions coming off coming in the chats thank you for those great questions um what do you suppose is produce film x about i don't know i'm sorry uh maybe more in the 0.4 range than 0.3 range if you we see him we see him racing um what i've derived roughly i must admit roughly about this climbing effort uh in this year's tour then i would um estimate this view to max in the 95 region somewhere which allows you as a rider to have a bit higher vlmx that will not endanger your

1:38:32  carburetic utilization most of the of the stages so i think if you have a high view to max then you can have a high vlmx uh because you can compensate a little bit for that and and maybe yeah project car is it's it's uh what we have seen this year is so outstanding because of that typical profile but i don't have the calculations yet so i must uh a bit careful here um with commenting an interesting question from johkoman uh belgian coach about talent detection from which age can we

1:39:08  use inside tests there is no age limit to using inside tests of course it's more like a personal opinion when you think the inside software can give you an added value in your coaching approach i think it's more like a coaching decision here uh rather than than putting a specific age to this um

1:39:32  i think and and yeah it depends a bit on your idea about the land development um what your coaching opinion is about that and when you want to prioritize the physiological profile once you have that in mind i think that's a good age to start with inside testing but if you want to focus more on on developing skills for instance then you don't need the inside profile to to achieve that target the training target so i think it's more like an opinion and a coaching philosophy here than a fixed um age we can put

1:40:09  on on this it's our link to the address and subtract utilization paper i need to look it up it's already quite old publication so i don't have it in my mind so i need to look it up but i think we can manage uh igor to share the link uh once i have time to look it up i'm of course willing to share that paper

1:40:34  how fast can you switch plmx in terms of values so that's referring to um the timing of training adaptations it's it's really uh i can't give any again i can't give any uh general feedback on this because it's really depending on the athlete you see athletes sometimes adapting very fast to changes in vlmx uh especially the athletes with a lot of five switch driver they are very prone to adaptations the lmx numbers to increase it because their their muscles are equipped to to develop it on the opposite if you have at least with a lot of type one fibers and you want

1:41:16  to increase it then i wish you good luck because it's a struggle to get to get there it takes a lot of time and efforts for minimal training adaptation so it depends really on the physiological makeup of your athletes what you can expect as training adaptations and how fast it can be seen in in your you know test results

1:41:42  comment from james moses thank you for sharing seeing that future max training should be emphasized in the nervous cycle and vlmx reduction later again i can't i can't say uh based on scientific information you can use that id in your coaching approach and that's fine there are many ways to arrive at a certain physiology physiological profile i don't think there's a one way that's uh that fits to all needs of the old situations so um again um you should uh and that's what coaching is it's it's uh

1:42:17  tailored on the athlete and measuring uh at regular times is uh in my opinion helpful to manage the process you know is there any correlation with oxygen saturation of the lmx i'm not sure if i have that question well but plmx is a measure of glycolytic energy which by definition is not using oxygen so i'm not sure if that answer your questions

1:42:46  are any recent scientific studies that will show the amount of time one can hold maximal lactate steady state intensity it depends there are some some research uh not in maximum lactate steady state but in functional threshold power ftp and that's that's a different debate if that's a good representation of maximal x stage stage state and my personal opinion is no and there's good science to support that opinion uh there's at least good information uh on that training intensity that it's a good thing that it's a good thing that it's a good thing that it's a good thing that it's

1:43:20  the the the um i'm sorry the training level of your athlete so you see in low level athletes not able to uh support that intensity for a long time and in higher level athletes they can support it longer even it's like sort of threshold metabolic steady state intensity indeed it's not this a fixed endurance time for that intensity uh so i think i went through all the questions here uh hopefully um i've answered them sufficiently for you and i would like to thank you for watching the webinar to

1:43:56  stay here uh with many people still after more than one hour and a half so you have all good endurance to follow uh presentation and the questions and i wish you the best for the next of the day thank you for for watching see you soon