Shownotes

Louis' background

03:55 -

• I was a keen cyclist, and what brought me to science was that I wanted to win the Tour de France. Therefore, I studied sports science.
• Unfortunately, I learnt two hard lessons: science did not have all the answers I was looking for, which is still the case today. The other is that I lacked talent.
• After graduation, I found myself in an Olympic training camp, but I was there as a cyclist rather than an athlete. I watched the junior cyclists compete alongside the national coach, and they were performing at a level far above what I could have achieved in my career.
• The 16-17 years old, athletes were outperforming me, and it could not be because they had done more training. (there had to be something else into play)
• It was a hard lesson for me, but it fueled my motivation to pursue applied sports science and help others.
• So, in the next few years, I worked with British Cycling to help support and prepare athletes for major Championships.
• At the same time, I was doing some academic studies. However, that was a tricky balance. I had an "on-off" relationship with British Cycling, so I did my PhD looking into endurance cycling.
• Then, I went back into academia as a lecturer. However, British Cycling asked to help them prepare for Beijing in 2008. And since then, my work in the field has been supporting other scientists rather than athletes. I still coach some athletes, but that is the situation I find myself in today.
• I have been a professor at Kent University and now at the University of Calgary. I also work with the scientists who work in the Institute of Sport. (provide support to provide physiological information for the British Olympic team)
• I have worked with other teams, such as speed skating teams and with various cyclists from all levels.
• I chose the academic career because there has been more emphasis on the academic part in the last years. When I moved to the University of Kent in 2008, I conducted some work in the school and conducted some research with some fantastic colleagues who are now prolific. 
• Therefore, I think that part of my work is visible.
• On the other hand, the work I do with the Institute of Sports scientists is a part-time thing that I do alongside my academic job.
• And that work is not visible. You can speak with physiologists that work with the British Cycling team or the Sailing or Triathlon team.
• However, that is something I cannot promote.

Training load - definition

09:50 -

• This topic can be a geeky topic with too much focus on the numbers. I will try to avoid that route as much as possible.
• Training ultimately comes down to making decisions, and the crucial part of those decisions is our emotions. The data analysis suggests we do something, but we did other things because the suggestion did not feel correct.
• Even though training load connects to logic and numbers, training is more complex than that.
• The training process allows measuring and quantifying how much training an athlete will do. Either the athlete is self-coached, or they have a coach. We work by prescribing a specific training quantity.
• Moreover, we want to track how much training an athlete has done to evaluate its effectiveness. I believe most people want to have a training program as close to the optimal as possible. (making training more effective)
• We need to compare it against other training methods and what athletes did in the past, look at the science, and see the best training practices of the best athletes in the world.
• The act of quantifying training is the concept of training load.
• Most people talk about the historical concept of the training load of Eric Banister. He suggested that it is possible to sum up the athlete's training amount and predict the impact on performance.
• He did many studies where he added more training to an athlete. He used an artificial number (TRIMP) to quantify that training in swimmers.
• He evaluated how much weight training athletes did by converting it to TRIMP and then did the same with the swim training and added everything.
• Therefore, he could say the exact amount of training an athlete has done. Then, he used the TRIMP model to predict changes in performance.
• He showed you could get surprising reasonable predictions by tracking the athlete's training.
• It was the start of this topic, and it has gone in many different directions.

Methods used to measure training load

13:37 -

• In the 70s, it was challenging to measure heart rate unless you were exercising in a lab. In the 90s, I could do novel research by putting a watch on someone's wrist and gathering heart rate from a race.
• People associate the TRIMP model with heart rate, but Banister only introduced it in the 90s.
• In the 70s, he only measured the distance swum, the intensity of training and the weight lifted by athletes.

Development of different training load concepts

14:50 -

• Some websites and software still calculate the TRIMP and report for you. They also manifest it in acute and chronic training loads.
• Then, there are various other things like TSS and predictive recovery times from your watches where they use the concept of presenting how hard you are training.
• Moreover, we may divide our training time into training zones. These are all methods to quantify how much training we are doing.
• Another metric is the normalised power score for cyclists, in which we find these concepts today.

What to do with training load

16:16 -

• We want to evaluate the efficacy of what the athlete is doing and what they did in the past. 
• When you write a training program, you have to consider the training load because you try to give an athlete the appropriate training dose.
• The program itself represents the training load. Once you have done it, you can look at the history and correlate it with the level the athlete is presenting.
• For example, you might be worried that athletes cannot recover from hard sessions or accumulate too much chronic load. You can also be worried about injury or illness, so we are interested in monitoring the athlete's training to control these variables.
• People are aware of this concept every time they prescribe a 10 km tempo run on Tuesday and an easy session on Wednesday because the training load on Tuesday is high. You do not want the athlete to get too tired by doing another hard session on Wednesday.
• Then, you can compare between training sessions, and when this gets more interesting. 
• Comparing a 10 km tempo run and an 8 km easy session is easy. One is longer and more intense than the other. 
• However, is a 5-min all-out harder than a 20-min all-out effort? Now, it is trickier because they are both all-out efforts. Even though the 5-min effort is shorter, you can compensate by going harder.

Validation of different training load concepts

19:39 -

• The surprising thing is that the training load has a scientific background.
• Many practitioners use training load in different ways using a broad range of different metrics.
• There was no validation procedure on training load concepts when we reviewed the literature.
• For an experienced coach or athlete, it does not matter because they have understood these concepts for a long time, and the scientific numbers for training load are usually wrong.
• In academia, we are catching up with what athletes and coaches have known for many years. 
• The problem is that people tend to make the same things over time rather than change and innovate. 
• If we look at things critically over time, we may find reasons to make changes and innovate.
• The challenge is to judge how hard a session is. Here you have the risk of falling into a circular argument. What you do is check heart rate, for example. However, heart rate is also a training metric, so we use a tool to control training that lacks validation for measuring how hard the training is.
• What we did was stripping training to a superficial level. After the training session, we judged how hard a session was by doing a performance test.
• If it is a demanding training session, your performance will drop significantly compared to an easy session.
• We looked at what performance tells us about each session and correlated it with the metrics. We found consistency with the metrics used to control the training when we started that exercise.
• The training metrics seem not to do the job properly, which is a cause for concern. However, an experienced coach would already know that some metrics provided incorrect data.
• For obvious comparisons, they work well. The less intuitive ones are the ones where it leads to misleading results. 
• If you ignore how you feel and focus on metrics, you could make the wrong decisions.

Effects of duration on performance

25:39 -

• This point was where I tried to avoid the number and keep it in concept.
• For example, if I do a cycling session where I constantly ramp up the intensity every three minutes, it will change the body's response to exercise. However, that response will not change instantaneously and will not increase linearly. When we reach a specific point, the stress increases exponentially.
• Once you cross the lactate threshold, the effective stress increases disproportionally. You can increase the intensity at low intensity and get a dose-response sensation. (almost linear response)
• After crossing that point, it will feel much more challenging if you increase the intensity slightly. Many of the training metrics we use to measure training load recognise this.
• And that is the permiss behind normalise power or TSS because they treat the high-intensity stuff we do as disproportionally stressful.
• We thought we handled that point well, but we started to look at the effective duration.
• Most people do not grasp the impact of duration in the most helpful way. However, experienced athletes know this, even though they cannot express this numerically.
• In summary, as we work harder, time seems to slow down. Sometimes, you can do an intense 10-30 second interval, and it feels that it takes forever. Whereas you could have a nice easy ride for 30 minutes or 1-hour, the time passes much faster.
• We need to structure time according to how hard the session is. (not every second is the same)
• For example, what is harder (5-min vs 20-min all-out effort)? It turns out it is a trick question. 
• We studied this with one of our PhD students, where we gave people this 5-min and the 20-min all-out effort, and then he measured the performance afterwards.
• Performance dropped regardless of the duration of the effort.
• It is counterintuitive because we suppose that the 20-min all-out test would be more demanding. However, as people can push more in the 5-min effort, they compensate for the shorter duration.
• We have to think more of the maximum effort we can make for a specific duration than the traditional method.
• The sessions offer the same stress concerning the training load. 
• However, we would not see that for any of the metrics. All of our metrics would tell us the 20-min was more challenging than the 5-min session.
• We are saying that a 5-min session where you go all-out could have the same training load as a 2-hour training session.
• Now, consider that we want to do 80 % of our maximum effort. The power outputs for the 5-min efforts will still be much higher than the 2-hour effort, but the cost of duration for maintaining a steady for a 2-hour session will be high.
• Training load started from the view of evaluating changes in performance. However, we might have to change that slightly. Even if the body's stress goes through a 5-min all-out effort, the adaptations that come from it might be different.
• So, we cannot swap a 2-hour session for a 5-min session, but we might understand better the challenges of each of those sessions and find more effective ways of doing them.
• We only mentioned continuous exercise, but it becomes even more complicated when we talk about intervals (time spent above a specific intensity or the time of recovery)
• People say that high-intensity training is better and more effective than endurance training. However, they say this when considering the same volume.
• If you have limitations on time, it is evident that high-intensity training will be better than continuous endurance training.
• However, you might not need to train that way. If you can train more time, you can train as effective as the athletes doing high-intensity.
• You can get the same fitness improvements by doing a different session. 
• We have to equate both training sessions appropriately. 

Measuring performance after a session

35:40 -

• We did five minutes between the training session and the performance test. 
• First, we had to do the scientific design, where we wanted to take some measurements at the end of the training session, and if we started the performance trial right after, we would not have time to take out all the measurements.
• Then, we had some concerns about motivation or pacing for a performance trial, so we wanted to give participants a moment to prepare themselves for a maximum effort.
• Their performance would have slightly declined if we had removed that recovery period.
• As you gave everyone the same recovery period, the impact of the recovery period is approximately the same.
• If we delayed it by 24 hours, we had another variable with recovery. And recovery would depend on the athlete's physiology, nutrition, physical activities, general stress, health, and sleep.
• However, that was the original approach Banister took. He did the performance trials to track performance after a specific period.
• We would love to get the evolution of someone's performance over different periods, but people do not want to do performance trials all the time.
• Therefore, we have to guess what that picture looks like, and looking at performance after 24 hours is almost asking a different question.
• Our goal focused on quantifying only one training session and leaving the method improvements on how to build training programs for the future.
• The effects on different sessions after 24 hours are some answers that practitioners already have, but science still has not provided any insight into this topic.
• After each session, we did the performance trials for a scientific purpose, as no athlete wants to do regular performance tests. (our goal is to predict the performance change

Future developments in training load

40:25 -

• The basis on which science progresses is that we put theories or hypotheses and test them with a scientific experiment. Science progresses by disproving those theories.
• We proved that the concept of training load today does not do what we thought it would. Therefore, we should discard this hypothesis.
• A pure scientist would stop talking about training load and develop a new concept. However, this approach is not practical and may be unnecessary.
• We will see if we can calculate the metrics better in the medium term and overcome their limitations. We want them to reflect better on how hard different training sessions are. If you compare two training sessions where you only change one thing, the metrics are straightforward.
• It is when both duration and intensity change that current training metrics suffer.
• The other question is seeing other parameters we can use alongside the existing metrics.

Total work as a training metric

43:15 -

• Imagine you want to trick the system by accumulating the total work done.
• People could not worry about getting fitter and would only go easy for extended periods. You would accumulate vast amounts of work, but they would not be that stressful. Therefore, you will not get fit from doing that.
• And that is the problem with the total work done. It awards excessively long training sessions at long intensities.
• If you train longer, you will naturally accumulate more training time, but you can also add some intensity blocks.
• However, if you would take out all the volume and keep the intensity blocks, would you have the same response to training? This method of looking into training load suggests that we might have some positives. (focus on quality for the length of time you are exercising, and not quality employing intensity)
• You can do long or short sessions, and it is not that duration does not matter, but we should not take for granted that longer is always better.
• It will take a while before we can make conclusions about these questions and get some consensus within the scientific community.
• With our study, we opened the box, and the people that will be leading the research will be the practitioners that have to deal with this every day.

Impact of different intensity domains

47:50 -

• At this phase, I am not interested in different intensity domains because I think they can distract you from the training process.
• You have to think about how hard someone is pushing and how long they are going for during an effort.
• All approaches can be successful as long as you match the proper intensity/duration ratio if we are correct. (you can get fit by combining all different sources of intensity domains)
• If you exercise in the moderate domain, you will need to exercise for an extended period. However, if you are in the severe domain, you will exercise for that long.
• The premise is that probably you can exercise at any intensity you desire, but you have to find a suitable duration.
• If you spend much time training at a moderate intensity, you will get different training adaptations than training in the severe domain or sprint training.
• If you do not do high-intensity intervals, you will not be as good at them as someone who only does those types of effort.
• When we watch races, we can see athletes testing themselves to see how they "can break" the competition. I believe in training specificity, and so, if I do many one-minute intervals, I will become good at those types of intervals.
• At this moment, science does not have an answer to these answers, as we understand that different types of athletes will react differently to different training sessions.
• If you have a "fast-twisted" athlete, you train them one way, and if you have a "slow-twisted" athlete, you train them in another way.
• The training load for both athletes might be the same, but the training plan could be completely different.

Final recommendations on training load

53:25 -

• If you like numbers, you can correct the numbers you are working with or change the numbers in your head.
• You have to think about how hard a session was to your maximum ability for the same duration.
• Therefore, athletes should work in terms of the percentage of their maximum power output for a specific duration.
• For a person that does not understand so well the numbers, you should tread them with some caution. The numbers help make decisions, but you should not base the decisions only on those numbers.
• The other factor to consider is emotion. You can score emotion with 0 being a neutral state, and positive numbers mean you feel positive and happy and negative numbers indicate the opposite.
• We found that emotion is surprisingly sensitive. It is not something that people associate with training sessions, but seeing how a person is feeling during a session indicates how hard a session is.
• This metric could be helpful for self-control in athletes or coaches that want to evaluate where an athlete is at a precise moment.
• When athletes fatigue, their emotional levels drop.

Future projects for Louis

56:42 -

• We have a similar paper on the same topic in the review process.
• In the future, we want to access how these metrics can be more practical by implementing corrections to them.
• The problem is that while I filiate with the Kent and Calgary Universities, I do not have my lab, so I cannot start tomorrow conducting these experiments.
• My dream would be to use AI and machine learning to optimise how people train. And to do it, we need to solve this question first by weighing a single session before extending it to a whole training program.
• The challenge with AI is that it will only model the data you put in. If the best training session is still not "discovered", AI will not find it.
• AI can only look at past data and evaluate how we could have trained better.

Additional markers to find the optimal training load

45:26 -

• We wanted to find parameters that we know coaches and athletes measure daily. We use lactate and HR because we can predict their values, and it is accessible for athletes.
• Moreover, we have subjective measurements (RPE). You can gather much data by rating how you feel while producing a specific power output.
• These subjective measurements can also help separate the points where you are overreaching. We also have 6-7 questions where you can see that when you go above your optimal training load, your mood will worsen, and your energy levels and motivation will drop.

How Louis has been helping scientists and practitioners

1:00:37 -

• Regularly, I work as a "critical friend". If you are helping the athletes by doing something, I help them access the potential risks and implications of that process. 
• While I am helping physiologists and scientists, it all comes down to working with people, addressing skills, psychology and even philosophy. I help with a broad range of topics.
• When we are training someone, we are influencing someone's behaviour. Although we start from a physiological basis, we move away from only that field when applying it to practice.
• However, there are specific topics like finding ways to increase further stress without overloading them.
• For example, a sailor needs to be fit, so we look at the type of fitness we want and how we can generate that fitness. (what sailors can do on land to help them improve their sailing performance)
• I also worked with an Olympic team that did some test events and had the race data of how hard the race was.
• Then, I helped them compare what they did in training as a gap analysis by addressing the differences between the race demands and the training demands.
• And even in an Olympic team, there were severe gaps in training.

Three pieces of advice to help athletes improve performance

1:03:41 -

• Training is about making decisions, so "planning is essential, but plans are useless". The value of a coach is to help you set out a plan, but your coach will not predict everything that will happen during a race. Therefore, at some point, you might have to change your plans.
• And that is where data comes in, where we try to recognise if you are on track according to your training plan. If that is not the case, you need to move away from it.
• The second part is general encouragement to keep learning. We are a long way from knowing everything, and each athlete changes according to where they find themselves in the development process.
• Another point is to test different ideas as an athlete. I was not innovative as I would train according to the training plan and persist, and I would not do anything else.
• Now, I am much more interested in doing other things in a way where it is safe to fail. (I do not risk the whole program)

Rapid-fire questions

1:06:09 -

What is your favourite book, blog or resource?

Endure: Mind, Body, and the Curiously Elastic Limits of Human Performance

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

Reading

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

There are so many legends in science, physiology, cycling and sports. But my three daughters are now beginning their careers. (one in sports science) The way they develop themselves in their fields inspires me the most.

LINKS AND RESOURCES:

• Louis profile on Twitter and Research Gate and his email : louis.passfield@ucalgary.ca
• Validity of the Training-Load Concept - Passfield et al. 2022 
• Prior exercise impairs subsequent performance in an intensity- and duration-dependent manner - Fullerton et al. 2021
• Cycling Performance and Training Load: Effects of Intensity and Duration - Kesisoglou et al. 2020
• Continuous Versus Intermittent Running: Acute Performance Decrement and Training Load - Kesisoglou et al. 2021
• Metabolic and performance‐related consequences of exercising at and slightly above MLSS - Iannetta et al. 2018
• Lactate threshold with Mark Burnley, PhD | EP#330
• VLaMax, Polarised training, Fatigue and Complexity with Mark Burnley, PhD | EP#331
• Critical Power and VO2 kinetics with Mark Burnley, PhD | EP#257
• Nitrate loading, marathons, and endurance sports science with prof. Andy Jones | EP#187