Shownotes

Stephan Van Der Zwaard's background

03:19 -

• I am Stephan Van Der Zwaard. I work as an assistant professor at the Vrije Universiteit Amsterdam. I am also working as a data scientist at Leiden Institute of Advanced Computer Science.
• When I was 16/17 years old, I visited one of the performance testing sessions of the Jumbo Visma speed skating team. (the club of Jac Orie)
• I saw all these incredible performances, and I want to know how they could go so fast. That is why I studied Human Movement Sciences and pursued a PhD in it as well.
• I wanted to explain how we can explain differences in performances by creating a physiological profile. (Measuring the parameters, including skeletal muscle determinants) The goal was to figure out what distinguishes a good endurance athlete and a good sprinter. Now, we mainly focus on the endurance part. That is what I dive into in my academic career.
• Later, I entered more on the data science part because I figured out there was so much complexity and interactions between all these physiological determinants. Now, I am forging a bridge between the two fields and applying data science to learn more about physiology.
• I do it through academia and by being a consultant for some teams and federations. We contacted many national teams. (e.g., cycling, speed skating, basketball players, volleyball players)
• What we do is analyse all the data they collect. Teams and players monitor throughout the season and understand how training correlates to their performance or injuries.

Overall determinants of endurance performance

06:21 -

• In the past, the whole body determinants of performance were maximum oxygen uptake, lactate threshold, gross efficiency, and economy. The lactate threshold combined with the VO2max explained what performance levels athletes could obtain during a specific event.
• These three indicators are the most crucial. There are others like medical determinants.
• In terms of limits of VO2max, rowers tend to have the highest absolute VO2max values. We are talking of 7/7.5 L/min. If we look at relative values, cross country skiers, cyclists tend to achieve high values between 80 to 90 mL/kg-min.

VO2max of runners

08:14 -

• Runners tend to achieve marks in the high 70s mL/kg-min. If you compare all the values in the fields, they might not be lower than in other sports. But it is more common to see higher values in other sports than running.
• I would not say this relates to training. Runners accumulate many kilometres every week. Therefore, the distribution of values and economy could explain these differences.
• However, VO2max alone will not evaluate the ability of an athlete. The combination of VO2max, fractional utilisation of VO2max and running economy is what matters.
• There are not many athletes that excel at those three parameters. It is challenging to achieve a high VO2max, high lactate threshold and high running economy.
• There is a study on the multiple Tour winner. That study showed that we could have high efficiency at a high VO2max and elevated lactate threshold at the same time.

Skeletal muscle determinants of endurance performance

11:25 -

• We analysed the public literature and looked at all articles related to endurance performance. We focused not only on skeletal muscle determinants but also whole-body determinants.
• We ended with 290 different articles and crunched them down to 54. Of all those articles, we looked at the relationship between skeletal parameters and performance parameters.
• First, fibre type is a crucial determinant of performance. The impacts fibre type has on VO2max, lactate threshold, and economy are large. Therefore, it is fundamental we can explain the reasons why this is the case.
• A typical endurance athlete has 70 to 80 % of type I fibres, mostly in the vascular muscles.
• In the 90s, the percentages presented were even higher.

Impact of type I muscle fibres on endurance performance

13:12 -

• Type I muscle fibres are more oxidative.
• Concerning efficiency, if you look at the movement velocities for cycling/running, they are also more efficient.
• Therefore, a higher percentage of type I muscle fibres correlates with a higher VO2max, lactate threshold and economy in endurance athletes.

Muscle fibre cross-sectional area

13:55 -

• That is an unusual parameter because you might want to have larger fibres. (you can produce more power)
• If you have larger fibres combined with slow type I fibres, you can sustain higher workloads for longer. Theoretically, this gives you a higher steady-state pace.
• However, if you look at the data, we find negative correlations between fibre cross-sectional area, endurance performance and lactate threshold. It means that a higher cross-sectional area impairs endurance performance.
• One of my supervisors did many studies on animals. He looked at the cross-sectional area of different species. (frogs, humans, mice, rabbits) They saw animals with a higher cross-sectional area could produce a lot of power. Nevertheless, they had lower oxidative capacity. The animals with lower areas had higher oxidative capacity.
• If you draw this correlation, it is hyperbole and strictly related.
• Now, if you are an athlete, do you have to deal with it? (you go for larger oxidative capacity or higher muscle fibre size)
• As an endurance athlete, you want to focus more on oxidative capacity. But you could try to have a slightly higher cross-sectional area with the same oxidative capacity. It helps to produce more steady-state power.
• It is intriguing to see how this correlation can help you and how athletes can achieve this.

Strength Training for endurance athletes

16:59 -

• The neurological adaptations are favourable, aside from the increase in cross-sectional area.
• The cross-sectional area may increase for endurance athletes doing strength training. However, this is a balance between this and how much endurance training you do.
• Some reports in the literature show higher cross-sectional area type I fibres in professional cyclists.
• There is some room for improvement here. It also depends on the oxygen supply.
• You have sizeable cross-sectional fibres, where the oxygen needs to go in. It means you have a large diffusion region. That is not perfect, as you want to provide all the areas with oxygen.
• You can also look at the other side of the spectrum. What if I increase my oxygen supply? You achieve this by having more capillaries, and then the diffusion distance is not a problem.
• On top of that, you also have myoglobin (what transports oxygen within the muscle fibre). It helps to get oxygen to the mitochondria that need oxygen to create energy. These two factors combined are what allows someone to have larger muscles fibres. (while not affecting the oxygen capacity negatively)
• We did a study in 2018 where you observed this. Cyclists that could be above the curve (with the higher cross-sectional area) had higher capillary density. It also supports this theoretical argumentation of why this works.
• The outcomes on endurance performance of cross-sectional area were only short or moderate. If you look at muscle capillary density, the effects are large. (which you would expect)
• If you look at capillary density, you could have three or four capillaries per fibre. But if you look at endurance athletes, they will have five to eight.
• We measured Olympic track cyclists 9+ capillaries around the fibre. As you can imagine, this is very beneficial.
• For myoglobin, there is not much literature on it. (at least looking at these relationships) It is something to study more in the future. The effects on endurance performance are mostly moderate. But this is only by looking at a couple of studies.

Mitochondrial oxidative capacity

21:41 -

• There are many mitochondrial markers you can access. We evaluate enzyme activity (e.g., citrate syntheses, citrate CIC, oxidase). You can also look at the actual respiration of the muscle fibre there. It is through permeable fibres.
• We saw these correlate strongly with VO2max. If you take a muscle biopsy sample and extrapolate the activity for the whole body, the actual VO2max was 90 % of the theoretical one.
• It is what we tend to see in literature. The limitations of VO2max supply are in oxygen supply. However, the room for improvement is not high. (only 10 %)

Physiological cross-sectional area

24:37 -

• We measure it with a non-invasive method (MRI or ultrasounds). It is the cross-sectional area of the entire muscle.
• People are born with different muscle fibres. The consensus today is that you cannot change that much.
• We see similar correlations as the ones for fibre cross-sectional area. (negative correlation between this and VO2max)
• The oxidative capacity has a strong impact on the lactate threshold and VO2max. For endurance performance, the effects are moderate. It is a bit lower than expected, but it interacts with the other parameters.
• We also have to look at how all of them correlate with each other.
• If you had a high oxidative capacity, a small physiological cross-sectional area and a high capillary density, you would have a high VO2max. (only by looking at skeletal muscle determinants)
• Endurance athletes have more glycogen in their muscles, and they burn this glycogen faster as well. It is helpful for long-duration events.

Effects of training on the skeletal muscle determinants of performance

28:32-

• Higher training volume increases VO2max. If you look "under the hood", your calcium pathway goes up. Therefore, you make a lot of contractions, increasing PCG-1alpha, and this leads to mitochondrial biogenesis. That is why it improves the VO2max.
• With higher volume, stroke volume increases with low-intensity training. In the past, researchers analysed the training volume athletes had and the improvement of cardiac volume. And there was a strong correlation there.
• Doing this type of training gives you these peripheral and central adaptations.
• You can also do higher-intensity training. This might be more effective than doing moderate continuous sessions.
• With higher-intensity training, you can improve more or, with less time, produce the same result. The reason for the improvements has to do with increased SDH activity and capillary density.
• By making the muscle to be in lower energy status, it forces mitochondrial biogenesis.
• However, there is literature stating that high-intensity training might have an upper limit. The first studies were on recreational athletes seeing that after 14 HIT sessions, you could see some improvement in the mitochondrial enzyme activity. But if you look at the respiration, it was lower. It means you lose some of the effectiveness of this.
• Even though you have more biogenesis, it is not as productive. The debate now looks to explain why too much high-intensity becomes effective.
• We should put high-intensity sessions in our training regime, as this improves the oxygen supply. There is a study which analysed four groups. (two groups that trained at low-intensity and the others at a high intensity). Low-intensity meant training below four mmol of lactate concentration. Two groups had a hypoxic stimulus at low or high-intensity sessions. They trained slow or above 3000 meters of altitude.
• The research found that myoglobin levels would only go up when doing high-intensity training combined with hypoxia.
• When you train in a hypoxic environment, it is more demanding to get oxygen. Therefore, you are making the exercise with hypoxia even more stressful. From the oxygen supply, that is something to look into when training.
• However, keep in mind that you do not want the impairment of the mitochondrial oxidative capacity. It is a balance, and that is the reason polarised training is so well-looked. (Training most of the time below the first lactate threshold and 15-20 % above four mmol lactate concentration)
• These adaptations athletes got to do with the intensity part.
• The moderate-intensity training part is more related to the stroke volume and mitochondrial biogenesis. It has to do with repetitive movements with prolonged exercise bouts.

Blow flow resistance training and myoglobin levels

35:52 -

• I have not seen studies addressing this topic yet. You can imagine that instead of reducing oxygen in the air, you can reduce blood flow and produce a similar environment.
• In that sense, you can expect the oxygen blood pressure to go down.
• Of course, many other things are going on. As the blood flow lowers, you do not remove waste products as well. Therefore, it can be a more strenuous stimulus in that sense.
• I am not sure, but it is something worthy to look at in the future.

The effects of training in the heavy domain (between LTI and LTII)

38:02 -

• We are talking about threshold training. Of course, everything leads to improvements when you start training.
• But what is more effective? The polarised training I was referring to before does not include much time in this zone. And it gives better adaptations. (better improvements in the whole body determinants of endurance performance)
• A meta-analysis showed that threshold training has a lower impact on performance compared with polarised training.
• However, there is not much literature yet on the subject. Some studies will come out shortly. I am intrigued by how polarised training affects these skeletal muscle determinants.

The role of threshold training for endurance athletes

40:14 -

• The goal of threshold training is more focused on race-specific performance. But looking at intensity distribution, if you do most of your sessions in that zone, it will not be as beneficial as shifting to the extremes. Nevertheless, I think there is a place for these sessions.
• We should not see the subject as "black and white". The question is how much you want of it.
• Therefore, I would only focus on it before the competition period.

How different high-intensity sessions impact endurance performance

41:34 -

• Sprint interval training is in the extreme domain. It is crucial, and we see that it improves VO2max.
• In the same line of capillary density, if you had the hypoxic stimulus to these repeated sprints, there is a benefit to doing it. So, performing sprint interval training in hypoxia improves VO2max slightly more and facilitate adaptations.
• You have to consider that recovering from these sessions take more time. And maybe, that is one strength of the polarised training. If you do these high-intensity bouts, followed by low-intensity blocks, it helps to get the adaptations.
• We did a study on sprint training in hockey players. They did a combination of groups of these sprints in hypoxia. We saw that the biggest improvements in oxidative capacity came from the sprints in the hypoxia group. (already after two weeks)
• Therefore, the adaptations are fast to occur. They improved by 35 %. It is not a short improvement, especially looking at hockey players.
• However, you have to keep in mind that these improvements go away also very fast. We have to consider the timing when applying these protocols.

Additional points on the study

44:40 -

• A study looked at polarised training also in terms of rate of perceived exertion (RPE). They looked at it four weeks before testing. It was not an endurance group, as they were a speed skating group. However, 1500 m efforts also require a lot of endurance background.
• The study found that training with an RPE of (2-3) was beneficial and improved power. Training with an RPE of (4-5) associated with the threshold zone correlated negatively with power output. With an RPE of 7, we started to have benefits again.
• It is intriguing to see this RPE correlation might be beneficial for short events. (as this correlates already for longer events)
• Of course, we have to look at the individual component as this was only one study.

Data science in endurance sports

47:30 -

• What we typically look for is to analyse past data of training. For example, we log the training sessions meticulously and evaluate how that correlate to performance.
• We collaborated with the Dutch volleyball federation, and we worked with the male team. We had an entire season looking at all the sessions they did. (e.g., analyse jumping heights, number of jumps)
• Therefore, we could evaluate all the impacts of this and compare that to injuries. With this protocol, we could understand how much load leads to problems.
• We created a model looking at all these parameters, and we can make questions like these. Does it matter how high you jump? Does it matter how often you do strength training? How long are the training sessions?
• We are capturing the data in all these different aspects. And we try to predict the model with the target of accessing injuries.
• We understand that jumping is crucial for the athletes, but we are also providing thresholds for coaches. For example, we have a player with 150 days of training and x days of injury. With this information, we can model for this player what the limits are.
• We have an athlete that does a lot of strength training, and we already know that there is a limit on how much backload he can manage before he gets injured. We can say what amount of weight he can deal with injury risk-free.
• By providing this value, we can plan future training and understand what we need to do to avoid injury or overcome improve this limit.
• We do a similar analysis in basketball, cycling or speed skating. We have many sensors and devices that help us to take out data. However, the value is on how we treat data.
• Analysis of how internal vs external parameters correlate is crucial for understanding performance improvements.

Data science applied to endurance sports like cycling or speed skating

51:11 -

• There is some work in progress to apply it to endurance sports. In cycling, we can measure a lot of things with different devices. We use unsupervised machine learning to try to find correlations. With all the data, we look at all the relations in the dataset for very similar people. By doing this, we can see that there are several types of cyclists. We did a cross-analysis of different cycling modalities.
• We found that track sprinters are different from other cyclists. as we can imagine. They are much bulkier and mesomorph. Team pursuit and road cyclists were similar to each other.
• We can use these clusters to analyse their performance and to find different ways of training them. We want to use the physique and physiology of these people to be more specific with training.
• The application of data science in endurance sports has only started now. (it is in its infancy)
• We work with well-controlled hypotheses driven by the experience. However, applying data science is different. You look back to the data and apply new knowledge or get new insights.
• As this is a shift in the way we work, it takes time for people to adopt it. There is also much to do in image analysis. In Antwerp, they are doing much work on sprinting towards the finish line. The researchers are trying to understand how the trains form and dissolve with camera analysis. It is another different way you can apply data science.
• There are so many ways and applications in this field, so I feel there is much more to come.
• The crucial part is you want to have people working in the domain. (knowing the problems that exist in the field) And people working on data science. By combining the two and working as a team, we can solve different questions with new tools.

General tips for endurance athletes to improve their performance

55:52 -

• One fundamental point is to monitor your progress and keep track of what you do. You should not only analyse the speed of your runs, swims or cycling bouts. But also how hard you perceive those bouts.
• With only one metric of RPE, we can take a lot of information about the workout itself.
• If you record data, you can then go back and analyse that data and use new tools to understand what worked or not.
• Concerning physiology, you should focus on oxygen supply capacity to improve overall performance. To improve it, you should do high-intensity training. You could do it in hypoxia. (in altitude camps). Nevertheless, do not forget that you need to balance it and not overdo it.
• Along similar lines, I would suggest varying your workouts. The goal is to achieve a polarised training distribution, but also to motivate yourself. You aim to look at what sessions you like to do.

General questions

58:06 -

What is one thing within coaching or training you are now learning/curious about or fascinated by and why?

I am curious about the hyperbolic curve of muscle typology. In nature, or you go to the explosive sprint side with fast twist fibre. Or you go to the oxidative capacity and the endurance side. It means you cannot combine both. Nevertheless, there are some athletes that find a way to do it. And I am very curious to understand how. In previous papers, we saw myoglobin and capillarisation are crucial, but there are more things to look at. And there will be some papers addressing those issues.

Rapid fire questions

59:15 -

What is your favourite book, blog or resource?

Faster: The Obsession, Science and Luck Behind the World's Fastest Cyclists

What is an important habit that benefited athletically, professionally or personally?

Tracking my workouts and my well-being allowed me for looking back and understand things that I did. It is a habit I still do every day, with only two minutes of work.

Who is someone you have looked up to or who has inspired you?

That is Jac Orie. The reason is because of the way he approaches science and puts it into practice. He is keen on proper data collection. It is something I admire and try to apply in my work field.

LINKS AND RESOURCES:

• Stephan's Twitter, Research Gate and website
• Under the Hood: Skeletal Muscle Determinants of Endurance Performance - van der Zwaard et al. 2021
• All "Science and Physiology" episodes on That Triathlon Show