Categories
Practical application Training theory

When life was less narrow (you probably felt better)

With age, most people tend to drift into narrower and narrower tracks. Not just in training, but generally: political views become more fixed, taste in music and literature stabilizes, clothes become more predictable. Social circles narrow, and movement tends to do the same thing as we become “cyclists”, or “someone who lifts”, or “someone who runs”, or “someone who does yoga”.

Which is, to be clear, completely normal, and probably healthy to some extent. Identity is useful, habits reduce friction and specialization solves problems. There is something admirable in the ambition to explore how good at something very specific one can become in life.

Still, I think many people recognize something when they look back at periods where they genuinely felt their best, that those were times when they did many different things and moved in many different ways.

The idea that variation is connected to health is not exactly foreign to us. Scientists already see variation as a sign that systems are functioning well. Heart rate variability is widely used as a marker of a flexible, adaptive system. Nervous systems seem healthier when they can adapt to different demands instead of producing the exact same response regardless of what situation they are exposed to. Healthy ecosystems tend to contain diversity and redundancy.

Systems with options tend to tolerate change better, which makes it slightly strange that most of us organize our own lives only in the opposite direction, especially later in life when adaptability may matter most.

When working with developing athletes, a common mistake is having a short-term perspective. This often manifests as early sports specialization, defined as intentional and focused participation in a single sport that restricts opportunities for engagement in other sports and activities. While this can work surprisingly well in the short term, such rapid improvement, while acutely gratifying, is often detrimental to long-term development.

Such early specialization is linked to higher overuse-injury risk, while the evidence for later elite success is mixed. It is also a poor way to evaluate long‑term potential, because it is heavily biased toward relatively older and early‑maturing players whose superior speed, strength, and size reflect biological timing more than durable skill advantages.

Research on long-term athlete development shows that, in most sports, athletes who spend their early years sampling many sports tend to stay healthier, avoid overuse injuries while being at least as likely, often more likely, to reach elite senior levels.

Exposure to different sports and movement patterns create a deep reservoir of motor intelligence, and by the time they finally face the demands of elite specialization they have a robust system capable of absorbing the stress. Those who specialize early might have looked better at age 12 or 14, but by age 18 they had often hit a plateau, lost motivation or succumbed to overuse injuries. Most modern youth development models now actively argue against early specialization.

Repeated exposure to similar types of performance problems in one sport allows movements to become more precise, efficient, and predictable within that domain. In other words, true expertise in adult sport depends on repeated, increasingly difficult and specific exposure.

But if you move further along the timeline again, something interesting seems to happen. Many of the same qualities that seem beneficial early in development begin to reappear later in life.

When reading about how to protect your body and mind against aging it is always some specific activity that is pointed to as what would be the silver bullet: balance training, muscle mass, crossword puzzles, aerobic exercise, or similar. But what if the protective effect comes not from one thing, but exposure to things outside of what you are already good at? Not the activity itself, but its newness?

Research on healthy aging and cognitive reserve increasingly points toward novelty, variation and broad engagement as associated with better cognitive outcomes. Not just physical activity itself, but exposure to different types of movement, environments, learning situations and social interactions.

Placed next to each other, these ideas begin to resemble less like three separate discussions and more different phases of the same pattern.

Early in life, broad variation seems to create systems that are more adaptable and capable of long-term development. This allows for narrowing the focus during the peak performance years, where the goal can shift from broad adaptability toward precision, efficiency and mastery of a single field of performance.

There is a specific period in life, often during late adolescence and early adulthood, where specialization is deeply rewarding. Exploring one’s own potential and seeing how good one can actually be is something that, if you have laid a good foundation for it, is an important school of body awareness in the same way that it is deeply rewarding to improve oneself in other activities or within a profession.

And then later, once maximizing performance is no longer the primary goal, many of the same qualities that once supported early development begin to appear valuable again: variation, novelty, broader movement repertoires and exposure to different types of demands.

One difficult question, of course, is knowing when specialization loose its edge. The answer is likely not chronological.

Different sports (and different forms of expertise generally) place very different demands on the body and mind, which makes for peak performance to emerge at very different ages. Gymnastics is the historic poster child for early athletic peaks, but action sports like skateboarding and snowboarding follow an even more extreme developmental trajectory. On the other end of the spectrum we have precision sports like horseback riding and archery, or endurance disciplines like ultra-running where elite athletes often are way over their forties.

For some athletes the narrow focus may remain deeply meaningful for decades. For others, the costs begin appearing much earlier.

Sometimes the body reaches a ceiling: recurring injuries, motivational flatness, increasing anxiety around performance, or simply the feeling that too much of life has become dependent on one narrow capacity continuing to function. For others it is the demands of relationships, children, work, aging or curiosity that add up.

Life phaseWhat seems beneficialWhat many people actually do
Youth / Early lifeBroad variation, many movement problems, explorationEarly specialization
Peak performance yearsIncreasingly narrow and specific demandsContinued specialization
Later lifeReintroducing variation, novelty and broader demandsNarrow identity becomes permanent

While the research on your sports development so clearly points to that early specialization does not benefit long term performance, we still do more and more of it.

Modern sports, as many parts of modern society, is filled with cognitive dissonance. We are citing research about the benefits of variation in the morning, then spend the rest of our day to build a system of selection that demands hyper-specialization before puberty. The structure we have constructed demand an enormous amount of courage from trainers (and parents) daring to be “inefficient” enough to break the pattern, and let children be generalists. We could certainly do better.

But what I really want to discuss is that most people never make the final transition back. While it might be so that the intensity of the activity of choice lessens, the runner keeps running only, the lifter keeps lifting only, the academic keeps reading only one type of literature. The social circle narrows. Inputs stabilize.

But narrow systems also tend to become fragile. Not necessarily weak, but increasingly optimized for a limited range of demands. The experienced weightlifter may still move beautifully inside the squat pattern, and the seasoned yogi may display extraordinary flexibility within familiar positions, while both struggle when exposed to movement problems outside those highly adapted environments. When we adapt to become exceptionally good at one thing, we often forget that we also gradually lose familiarity with demands outside of those demands.

For the young exploring new areas in life is easy, as identity is open, then, later on, transferring into specialization is also relatively easy, because performance demands it. But then, when life requires returning to exploration, the transition back to variance is difficult because specialization is so seductive: it provides a sense of competence and a low-friction life.

The brain loves the path of least resistance. Identity reduces uncertainty, and habits reduce cognitive load. Novelty is threatening because it expose incompetency. Social belonging reinforces sameness, and sameness feels good.

When I teach courses in training theory, I often ask the group of coaches a deceptively simple question: who should take the greater risks in training, the person who train in order to support a larger life, or the elite athlete for who the training has become the center of life itself. Most instinctively answer that the elite athlete should take bigger risks, but isn’t it so that it is them who have more to lose? As their self-image is built upon their capacity to perform, the loss of one single capacity could greatly affect their whole identity.

Psychologically, having multiple, active, and authentic roles is linked to better well-being to some stressors compared with a single, highly dominant identity. Diverse, active roles tend to buffer people against some forms of stress and trauma, while a narrow, highly central identity can make setbacks in that domain feel devastating. Well-being seems highest when people have several meaningful roles that are reasonably balanced and can be enacted with a sense of authenticity. When self-image is strong even small disruptions to that self-image matter more. Injury hurts more. Psychological setbacks hurt more.

So while there is strong evidence for specialization in order to explore just how good at something we can become, there is also strong evidence to reintroduce variation when the time is right.

Different activities challenge different capacities: coordination, balance, timing, force production, spatial awareness, rhythm, endurance. Moving through water, on ice, across uneven terrain or under different rules continuously forces the brain and body to stay elastic rather than simply repeating one highly optimized solution.

Novelty, learning and broad engagement seem to stimulate neuroplasticity more effectively than repeatedly performing one narrow task in the exact same way.

Not only sprinting, long-distance running or explosive power work repeated in isolation, but exposure to all of them may distribute stress across a broader range of tissues and energetic systems, reducing some of the chronic low-grade inflammation increasingly associated with cognitive fog and age-related decline.

If this pattern is correct, then the practical implications become surprisingly simple.

Variation → specialization → variation.

In a very simple recommendation, it might look something like this:

PhaseIf you train 3 days/week
Youth / Early life3 different sports
Peak specializationThe same sport all 3 days
Later life3 different sports again

Perhaps one environment containing broad variation built into it is enough, especially for those who don’t have the time, energy or openness to constantly seek out entirely new activities.

I suspect this is part of why functional fitness or CrossFit or similar systems work so well for many adults. Strength, endurance, coordination, speed, balance and motor learning are all challenged repeatedly, structured into the environment itself rather than dependent on constant reinvention.

CrossFit was early to include age categories into their competitions, and many older athletes appear to retain broad physical capacities to a surprising degree despite training substantially less than younger competitors. When adapted appropriately to allow for enough recovery, it might turn out that such systems built around “a little of many things done often” may turn out to fit aging humans, in our hectic modern time unusually well.

And perhaps there is also something important in the social structure surrounding such environments. Not only training together, but spending time together outside the training itself.

There is a Swedish saying, “slipping on a banana peel”, where something unexpectedly opens a new path or changing direction, well, in order to be able to “slip on banana peels” you still need to put yourself in as many opportunities to do so as possible. One broad community, as good as it is, should not replace all others.

We could apply the same logic to reading, friendships, work, environments, travel, creativity, conversation. In the long run, in order to have a long run at all, we do not need a perfect version of ourselves. We need a messy, varied collection of them to keep our identities from fossilizing. Being repeatedly exposed to people living differently, thinking differently and organizing their lives differently than we do ourselves might be an important factor to open up yet new ways of thinking.

The specialist is a marvel of optimization, but they are also a system with little margin for error. The science of specific adaptation of imposed demands (SAID principle) explains their success, but the science of systemic fragility explains their frequent breakdown. True mastery might not be about staying in the narrow track forever, but about knowing when to step out of it to keep the system from becoming brittle with age.

References

Youth Sport, Specialization and Long-Term Development
  • Barth M, Güllich A, Macnamara BN, Hambrick DZ. Predictors of junior versus senior elite performance are opposite: A systematic review and meta-analysis of participation patterns. Sports Medicine. 2022. DOI: 10.1007/s40279-021-01625-4 (ArtSci Labs)
  • Güllich A, Macnamara BN, Hambrick DZ. What makes a champion? Early multidisciplinary practice, not early specialization, predicts world-class performance. Perspectives on Psychological Science. 2021. DOI: 10.1177/1745691620974772 (Sage Journals)
  • LaPrade RF, Agel J, Baker J, et al. AOSSM early sport specialization consensus statement. Orthopaedic Journal of Sports Medicine. 2016. DOI: 10.1177/2325967116644241 (Mayo Clinic)
  • Brenner JS. Sports specialization and intensive training in young athletes. Pediatrics. 2016. DOI: 10.1542/peds.2016-2148
  • Moesch K, Elbe A, Hauge M, Wikman J. Late specialization: the key to success in centimeters, grams, or seconds (cgs) sports. Scandinavian Journal of Medicine & Science in Sports. 2011. DOI: 10.1111/j.1600-0838.2010.01280.x
Exercise, BDNF and Neuroplasticity
  • de Sousa Fernandes MS, Ordônio TF, Santos G, et al. Effects of physical exercise on neuroplasticity and brain function: A systematic review in human and animal studies. Neural Plasticity. 2020. DOI: 10.1155/2020/8856621
  • Müller P, Duderstadt Y, Lessmann V, Müller NG. Lactate and BDNF: Key mediators of exercise-induced neuroplasticity? Journal of Clinical Medicine. 2020. DOI: 10.3390/jcm9051136
  • Miranda M, Morici JF, Zanoni MB, Bekinschtein P. Brain-derived neurotrophic factor: A key molecule for memory in the healthy and the pathological brain. Frontiers in Cellular Neuroscience. 2019. DOI: 10.3389/fncel.2019.00363
Cognitive Reserve, Lifelong Engagement and Aging
Categories
Training theory

When the problem is no longer the problem

One of the forgotten questions in training is not what exercise to choose, nor how much load to prescribe, but when to change the challenge.

Far too often this decision is left to a pre-set chronology of a few weeks (or days or months), or hard-coded into some systematic, linear training plan. Far less often do we ask whether the athlete’s response to a stimulus has actually changed. If adaptation does not unfold smoothly, but instead reorganizes in phase transitions, that are specific to each individual, then the timing of that change becomes a more important consideration than we might like to admit.

But what to look for when deciding such response-based adaptations… New all-time highs in performance? Sudden loss of performance? Or something more elusive, like a shift in the typical level around which performance fluctuates?

What we observe from session to session are only momentary expressions of how we react to stimulus. Some days the numbers will be higher, some days lower, but most of the time they move within a certain range. When that range itself begins to shift, something more fundamental may have changed.

If human adaptation tends to fluctuate around one level before shifting to another, then single performances tell us very little. Doing something once is an anomaly, not a baseline. Expecting an anomaly to repeat on command is to overestimate the state of the system in front of you.

We would be better off not trying to detect a single personal best, a single peak, or even a trend line that assumes smooth improvement, but what we should be looking for is when the typical state of the system changes, when “normal highs and lows” move to a new level, in short, we need to distinguish between normal fluctuation and genuine change.

This does not require vast datasets or advanced statistical software, but it does require that we look at performance across time, rather than in isolation, and that we think carefully about what we are really measuring, and what it can teach us.

Systems change over time, and the simplest way to think about them is in terms of their state, the set of quantities that determines how the system will respond to change.

Imagine a tank filled with water from which you can open a valve at the bottom and let water flow out. The opening of the valve is a variable: if you turn it to a position, it will display the same degree of opening as the last time you turned it to the same position.

But the level of water in the tank is a state: the effect of opening the valve depends on how full the tank already is. If the level is high, the pressure is greater and the flow behaves differently than if the level is low. So in a sense a state is a variable with a memory, its behavior is not only determined by it’s variables, but also by what it was before that input was applied.

In nature, changes of state are often abrupt rather than gradual. Stable patterns wobble, lose coherence, and hit what scientists call phase transitions, bifurcation points, or simply tipping points. In those moments the system reorganizes into a new pattern of functioning, which may contain a different set of options.

Boiling water is the familiar case. You can heat it steadily and nothing seems to happen. Then, at 100°C, everything changes at once and new possibilities open up: you can now sterilize, steam, cook foods, extract compounds that stay locked away below boiling… The phase change didn’t just give you hotter water, it gave you new possibilities of moving forward.

Humans are part of nature, and behave the same way: long stretches of nothing, followed by sudden reorganizations. Each transition could be a place where the athlete would benefit to be challenged differently, because new possibilities have opened up.

Think of a river flowing down a valley. The river’s level and flow pattern represent the river’s baseline state. The top of the sandbanks are the highs and lows. Over short times, waves rise and fall with rain or drought, and these changes are normal ups and downs.

But a small shift in the channel, something like a fallen tree, or a new sediment bar, or some abnormal change in the weather system that affects a rock formation somewhere, can redirect the entire flow. The river looks much the same, of course, and the surface waves still rise and fall, but behind the scenes, the main current is following a new route.

On the other hand, in aging systems, rigidity and loss of variability are common. The “channel” becomes entrenched and narrow, which is good for some tasks, but bad for adaptability: a single entrenched path means vulnerability when conditions change.

So the detection of both baseline shifts, and the loss of variation seems important, but neither is completely visible by looking at single sessions only. A single good or bad day can mislead. It’s only across several sessions that you start to see whether the system is actually at a different level, or simply fluctuating around the same one.

There are statistical ways of doing this. In fields like finance, engineering, medicine change-point detection models are used to identify when the typical pattern of a time series has shifted enough that yesterday’s baseline no longer applies, and when that happens it’s a strong signal to change treatment, recalibrate the machine, revise the model, or shift the strategy altogether.

But these methods are far too complicated to use for the strength coach. They rely on advanced statistics that even trained mathematicians spend time getting right, and they’re designed for systems where you can collect thousands of observations under controlled conditions. Our data are sparse, messy, and full of context you can’t easily quantify.

So what to do? I have a few suggestions that are good enough for our purposes and cover the situations we coaches usually face.

Obviously before we do calculations, we need data to do them on. The data, for our purposes, needs to be ordered in time, but doesn’t need to be complicated. Actually it’s better if it’s not, as complicated things tend to not get done regularly. Also, for gym work, testing one-rep maxes tends to be physically and mentally demanding, so instead of doing that I would advice doing something that corresponds well with that max performance. Speed of movement at some load tend to work well, as do testing of isometric maximum force.

For speed measurements:
Pick a consistent load (a weight that you deem to be roughly at 70–80% 1RM), and then track velocity over time, or track the load that produces 0.5 m/s. I would most often go for the first option, as finding what load that can be moved at a certain speed requires more lifts.

For force measurements:
Isometric testing allows you to measure force at very specific joint positions. That means you can choose positions that are highly relevant to the sport or movement you care about, but as a general rule, as testing at longer muscle lengths tends to correlate better with dynamic strength, you should, in order to gauge progress in dynamic movements in the training program (as squats, deadlifts etc) often opt do your testing in deeper positions rather than shallower ones (regardless of how your sport looks).

In practice, the two types of tests complement each other:
Isometric tests give you a stable, low-fatigue anchor of maximal force at a position. Velocity tests give you a moving picture of how force is expressed in a movement you are already likely to use in the regular training.

If you work with a closed sport – running, cycling, weightlifting, CrossFit – it’s often possible to collect meaningful data directly from practice. Especially cyclists, with the widespread use of power-meters, often already collect maximal efforts at different thresholds as part of their normal training.

Mathematically this very sport-specific data can be treated similarly once ordered in time, using much the same models to identify shifts in trends. This methodological similarity can fool you to use it in the same way, when there are substantial differences in what you can learn from them, how they should be analyzed and interpreted.

Research consistently shows that relationships between physical training and sports performance are context-dependent. Increases in strength and power in the gym do often, but not always, translate into performance at the field. Conversely, sports performance can improve without similar improvements in metrics tracked in the gym.

Data from the field shows how all the things that make up performance (physical and chemical capacity, technical ability and psychological factors) intertwine into one thing, whereas data from the gym shows you about how one factor might develop, in order to support a whole.

But while tracking data for these not-the-same-but-related signals is tracking two things, they have in their relation lots of information to provide us when it comes to training program design. If both trend upward over time, confidence in what we do in the respective areas of training obviously improves. But if they diverge that can be informative too, and might enable us to sharpen our decisions in the training we perform.

So far we have talked about principles, such as that the personal best we set is not on their own a description of an athletes state, that the data we collect should be simple enough to be collected over time, that we need to consider carefully what it really can tell us, and that statistical tools can help us to make judgments on when the same stimuli might not shake the athlete in the same way as before.

Some days are faster, some slower, and a simple rolling average reduces this volatility by grouping together the data in windows of, let’s say the last five sessions. Very easy to compute, but also means the trend-line can jump abruptly when a particularly strong or weak session drops out, even if the current performance has not meaningfully shifted.

Simple moving average with a 5 session window

We can see this from one example with bar-speed data of the back squat loaded to 100kg, collected during regular strength training.

The short-term noise in the graph is certainly dampened, but the curve still shows relatively sharp turns. In several places, the average shifts more abruptly than one would suspect the underlying performance state would suggest.

An exponential moving average behaves slightly differently. Instead of discarding older data, it gradually reduces their influence. With the same data as above, the EMA produces a smoother representation of performance, while avoiding sharp shifts in the average.

If biological adaptation rarely shows itself as perfectly smooth, linear increments, but rather appears to remain fluctuating around a mean for a period before shifting to fluctuate around another mean, then a method that filter out daily variability, while still balancing responsiveness to change becomes important.

Conceptually the difference between the two methods is that the rolling average helps us see the recent past more clearly, while the exponential moving average helps us see the present, while still retaining some influence from the past.

For a coach this has practical consequences as training decisions are often based on recent adaptation, not on performance from several weeks ago. A method, like EMA, that balances stability with responsiveness might therefore be more useful to us.

It is worth noting that even this seemingly simple method requires choices, such as what smoothing factor (the weight attributed to more recent results) to use in an EMA, or what size of window in a simple rolling average, and that these choices influence what is shown, and in turn how we might interpret the results.

Rather than just smoothing data, like a moving average does, methods of formal change detection are used to mathematically identify a shift in the underlying mean in a time series of data. For a coach that would mean a method to identify whether what we are seeing is just normal fluctuation, or real change.

Quite advanced statistical methods for change detection exist that can be powerful when large, high-quality datasets are available, but CUSUM modeling is a more simple way of doing this. Instead of smoothing performance, CUSUM accumulates small deviations from a reference level. If performance is consistently a little higher, or lower than usual, the cumulative sum rises or falls. As random fluctuations tend to cancel out, this method picks up sustained changes.

In the coaching environment, where data are sparse and noisy, CUSUM offers a practical middle ground and gives you a relatively advanced method for change detection that is still simple enough to implement without the use of advanced statistical software, as it can be implemented in a more coach-friendly program, like Microsoft Excel.

CUSUM works by accumulating small deviations from a reference level. Instead of looking at each session in isolation, it keeps a running total of how much performance has been above or below what is considered normal. To do this, we first define a reference value, a baseline, which is an average of the first N sessions in the current phase. Then for each session we calculate how far the result is from that reference. In practice two CUSUM lines are usually used, one that tracks upwards shifts, and one that tracks downward shifts.

The method requires one parameter (h) which is the decision threshold, meaning how large the cumulative sum must become before we treat it as a signal of a phase shift. The parameter k is not necessary, but smart for noisy data as ours, as it offers a way to adjust the sensitivity of the method.

CUSUM_pos = MAX(0, previous + (value − reference − k))
CUSUM_neg = MIN(0, previous + (value − reference + k))

If performance fluctuates around the reference level, the cumulative values tend to revert toward zero. If performance consistently deviates in one direction, the cumulative value grows until it crosses the threshold, at which point a phase shift is signaled. A new baseline can then be calculated, and the process is repeated.

When the positive cumulative sum drops below zero, it resets to zero. Similarly, the negative cumulative sum resets toward zero when deviations no longer persist. This prevents isolated sessions from generating lasting signals and ensures that only sustained changes are highlighted.

Once we have identified where sustained shifts in performance occur, we can now represent the data as a series of phases rather than as a continuous trend. Piecewise modeling then allows us to describe what those phases (their respective baseline) look like, by fitting separate segments to periods where performance behaves differently.

When I have taken the time to do this and shown it to the athlete, the response has usually been immediate recognition and acknowledgment that their experience of the training aligns with what they now are able to see.

While detecting (genuine) change is mostly what we coaches need for our decision process, this visual approach makes the training and adaptation very clear to the athlete, and this shared understanding can strengthen buy-in, and helps with long-term motivation for both the athlete and the coach.

When real change occurs, and a new behavior has evolved, not in a psychological sense, but in the sense that the same stimuli now would deviate around a different mean. It is therefore possible that what previously challenged the athlete will no longer push in quite the same way.

When this happens, then, may be an appropriate time to reconsider how we challenge the athlete, not because the previous training was ineffective, but because it may already have done what it could. Detecting these shifts, and interpreting them carefully, is therefore a central but often undervalued part of training design.

Worth noting is that detecting too little variation between sessions can be important as well. A system that is exposed only to a narrow range of demands may appear stable, but stability can be fragile. A river that rarely changes its course can be disrupted by even modest shifts in rainfall, simply because it has not needed to adjust its behavior. In training, a similar lack of variation may lead to a reduced capacity to respond when demands do change, and life tends to throw us curveballs once in a while. It’s good if we can handle those without injury.

Methods such as CUSUM analysis and piecewise modeling make these phase shifts appear clearly, but while they appear more exact they still rely on parameters (thresholds, sensitivity values) that must be set by the coach’s judgment. And is it not so that an experienced coach looking at a well-constructed EMA often will be able to see the same shifts in trend without needing the somewhat heavier statistical machinery needed for even a CUSUM analysis?

That said, there is still value in learning and occasionally applying the more advanced methods. Working through CUSUM or piecewise analyses can train the eye, helping the coach to develop a better sense of what different kinds of change look like in data, and how sensitive different models are to variation. This experience can sharpen interpretation, even when returning to the simpler tools of everyday use to decide on how to structure and set up complementary training in the gym.

Over time, performance in the things we choose to measure in the gym will slow. We cannot change up how we do testing too much, if we do we lose the long perspective and our built up experience of how an athlete performs exactly that movement while the season and life itself changes around them, and with every new exercise there will be a time of learning until the athlete reliably can perform the test. Plateaus in test scores, even occasional set backs, are to be expected, and are not a failure of the system but just how adaptation tends to unfold.

Such plateaus in the gym might actually not be a problem. What we do there is usually not the end goal. It’s almost always complementary, and its purpose being to support performance on the field of play, or for the ordinary trainee to support competence and resilience in daily life. If progress in the gym slows, while sport-specific performance keeps improving, or, for the established athlete, remain at a level that is satisfactory, there is no reason for alarm. The full picture may be reorganizing in ways that are not visible through the simple tests we track in the gym.

How often do I not hear that motivation to keep doing strength work drops because “my squat or deadlift does not improve anymore”, and that therefore that person will “start doing other things, maybe run more”. But if one stops training their strength, those numbers that did not increase will instead tend to decline, and with them then other things, things that was important for this person might become harder, or even impossible?

So stagnation of improvements in a complementary lift does not necessarily signal stagnation in the athlete, and may simply mean that the complementary tool has reached a point of inability to reveal development.

This is why measuring and applying the same analytical methods and models on both domains can be useful, with this we can interpret stagnation in one context differently depending on what happens in the other exactly because they display different things: one is trying to capture the whole, one isolates only a part. This perspective can allow us to remain calm, and reduce the temptation to chase personal bests in the gym at any price. It helps us to ask the more relevant question: is the athlete becoming better at what actually matters?

The task of the coach then becomes simple, but also difficult: not merely to follow the calendar. When doing this we should measure and test gathering data, but also try to not overcomplicate the issue with methods that tempt us with a false sense of certainty.

Because, in the end, the model does not remove the need for interpretation, and in most coaching environments, a clearly ordered dataset, a sensible smoothing method, and a practiced eye will take you most of the way.

Excel file and data used in the article:

Categories
Reading Borges Training theory

Reading Borges part 2: Repetition without repetition

It’s true that we should not make an exercise too hard because when something is too hard, we don’t learn much, and even more importantly we won’t enjoy the process and soon enough quit coming back (who wants to feel shitty all the time?).

Skills are often treated as things you have. Stored motor programs, memorized techniques, procedural knowledge that becomes stable and automatic through repetition. Perfect practice, for perfect results.

But what if skills are things you do? Emergent solutions generated in real time, under constraints that are always shifting: fatigue, attention, timing, environment, emotional state. Remove error entirely and you remove the signal the system needs to reorganize.

So it’s also true that when we make things too easy, we don’t learn much, lose interest, and stop coming back all the same.

Most coaches recognize both failures immediately. The harder task is knowing, in practice, when a movement that looks good has stopped demanding anything from the athlete.

Motor learning as a formal scientific field emerged in the early–mid 20th century (1920s–1960s), evolving out of psychology, physiology, and early human performance research. It did not begin with athletes moving through chaotic environment, instead it was set up in laboratories. Early researchers worked with tasks that were easy to measure: pressing keys, tracking lights, tapping rhythms. Closed, predictable actions where every deviation was obvious made it natural to think that the nervous system would strive to reduce error and stabilize performance.

Coaches absorbed these metaphors immediately. Perfect practice, perfect repetition, perfect technique. Clean up the deviation. Freeze the ideal and repeat it until it sticks.

In the 1960s, Nikolai Bernstein, who was largely ignored in the West at the time, observed something that didn’t fit the narrative at all: skilled performers never move the same way twice. This allowed the body to adapt to changing conditions, loads, surfaces, fatigue, timing.

What Bernstein suggested, quietly but radically, was that the nervous system doesn’t solve movement by executing a stored program. It solves it by coordinating itself each time. Repetition without repetition.

It would take decades for this insight to be absorbed. Through the 1980s and 1990s, dynamic systems theory, coordination dynamics, and ecological psychology began to challenge the old metaphors.

In 1939 Borges published his short story Pierre Menard, Author of the Quixote. In it he is telling us about a french poet who embarks on the absurd project of writing Cervantes’ novel Don Quixote again. Not, like in fan-fiction, a modern reboot of it (in which one would place the characters in modern situations) – but an actual recomposing of it.

At first, he considers the obvious route: to reproduce the book perfectly, perhaps he must become Cervantes: learn Spanish, return to Catholicism, fight against the Moor or Turk, forget the history of Europe from 1602 until now. Recreate the original causes and hope the same effect will follow. He quickly abandons this plan, as, thinking on it, he deems it impossible and, more importantly, uninteresting. Instead he decides to write Don Quixote as himself. A twentieth-century man, with knowledge from another world. The syntax, the words written, will end up the same, but their meaning, as it does not emerge from the text alone, but from the conditions under which it is produced will be something completely different.

The short story suggests that repetition only works because conditions are never identical. This is Bernstein’s “repetition without repetition,” long before the term existed. That learning does not come from reproducing the same solution, but from repeatedly adapting to slightly different situations while aiming at something recognizably “the same.”

A series of exercises in which the sensimotor experience is as similar as possible to a sporting movement is called whole practice. The alternative is parts practice, where one or more parts of the movement is practiced, rather than all of it.

When it comes to complementary training, which is the training you do in order to support better actions in the field of sports, exercises is, regardless if whole or part, is highly simplified versions of sporting movement.

The more similar an exercise is in sensorimotor terms, the greater its potential help from it to improve at the field of sports. This is why whole practice is always preferable. Sometimes, however, it is difficult to ensure progression with whole practice.

When learning movement there must be room for self-organization of the motor patterns forming this movement. Without your body being able to self-organize it would not be able to react to the demands of the environment quickly enough (describe the amount of time it takes for the brain to send signal to the muscle), and regardless, such top-down control, would only ensure performance of very specific movements in a very set environments.

When the athletes skill in a movement is low, more top-down control is necessary, and therefore the cognitive demand is higher. Too much cognitive demand in a situation, or exercise, and we are more likely to fail.

Building “motor programs” is more a matter of eliminating movement patterns that work only sometimes, than learning a single solution that works every time. The variation (noise) in the movement is what helps to learn what could be left to peripheral self-organization and what will have to be done top-down.

If the athlete is to unskilled in an exercise the noise will be so great that he or she cannot learn much from the performance of it, and progress will halt because each performance of the exercises cannot be linked together, and learned from.

In such cases, regardless of the superiority of whole practice, complexity needs to be controlled and we need to break the challenge down into manageable challenges. So the aim for complementary training is to designing exercises that are “as whole as possible”.

In a way, it’s not only the “signal” (successfully performed movement) that causes an increase of learned skill, but also the amount of “noise” (variability of performed movement).

“Open sports” (like basketball, football, mountain biking, etc) involve unpredictable, changing environments requiring constant adaptation, while “closed sports” (like gymnastics, weight lifting, swimming, CrossFit, etc) happen in stable, predictable settings with self-paced, consistent movements.

Strength training for open sports is so unlike the challenges on the field that expectations of a large effect from technical similarity are low. Better for these sports would be to focus more on structural change in the gym, like building muscles, tendons, and the capacity to tolerate force, rather than trying to add overload to sport-specific solutions.

But still, whether we challenge coordination or the ability to maintain stability against load (strength) there has to be sufficient challenge. Load, speed, time pressure, instability, or fatigue all create challenge, and in that sense they can all be thought of as intensity.

We can think of intensity as the amount of cognitive effort in demand. Time stress and load, as well as chaotic environments and mental pressure all play a role in how much cognitive effort is demanded during any given practice, and how well we can perform it. Seen this way, all training becomes skill training to some degree.

Whether the exercise is labeled “coordination” or “strength” the athlete is always negotiating constraints, managing errors, and organizing movement under pressure.

The distinction still matters because it changes what kind of error is informative, and where that error must be generated, but regardless of whether we train for strength or coordination, in open sports or closed sports, well-designed practice still always live in a corridor of not too hard, but never too easy.

What the scientific experiments show, across different paradigms, is not an optimal amount of error, but an optimal relationship to it. Learning improves when error persists without overwhelming the system, when it is clearly tied to the athlete’s own actions, and when it continues to demand reorganization rather than repetition. When those conditions are absent, practice may look good while learning is stalling.

Science can describe the boundaries perfectly well if fed enough data, but much of what happens in a exercise is not easy to measure, and the data will never be complete. And what is easily measured still means different things in different contexts.

This is where Borges becomes unexpectedly practical.

Borges’ poet does not learn anything by copying Cervantes letter by letter. Only when he writes the same text under different historical, linguistic, and intellectual constraints does the act become meaningful. The difference is not visible on the page, but it is decisive in the process that produced it. The same distinction applies to training.

Context is something that is hard to quantify into calculations. The coach who is present and attentive and has the experience to pick up on more things than even himself could tell what they are can build exercises that are “as whole as possible”.

A task is too easy not when it looks simple, but when it no longer forces the athlete to adapt. This is no easy judgment to make, but if we look carefully there are several signs of this.

One is premature stability. Technique settles quickly and remains unchanged across repetitions and sessions. Error diminishes early and does not return. In laboratory terms, the task has fallen below the learner’s challenge point. In practice, it means the athlete is executing a solution they already own. The movement may be clean, but it is informationally poor.

Another sign is the absence of exploration. Repetitions look the same not because the athlete is skilled, but because nothing in the task demands adjustment. Timing, rhythm, and sequencing repeat themselves without visible searching. The athlete can maintain conversation, attention drifts, and nothing in the environment threatens success. Here, the system is not stabilizing a coordination; it is merely repeating one.

A third indicator is error without consequence. Missed timing, poor force direction, or inefficient positions do not meaningfully affect the outcome. The movement “works” even when it should not. In such cases the nervous system has little reason to reorganize, because the signal carried by error is too weak. The practice is forgiving in a way competition rarely is.

Finally, there is emotional flatness. Learning tasks tend to produce small oscillations in attention and affect: mild frustration, renewed focus, occasional relief and sense of accomplishment. When practice is too easy, these disappear. The athlete is neither challenged nor threatened, and nothing is at stake. This is not a motivational issue, but an informational one.

None of these signs require measurement devices, they are judgments made in real time, by looking carefully and with intent at what changes and what does not.

Worth noting, even if a little of a side track, is that this requires the coach to have clear criteria for what they would expect when they give out an exercise. If those criteria are not already established before the exercise is performed, then how could possibly you make a judgment on too what degree the athlete fulfills the purpose of the movement?

There is a growing conversation about saving time by having AI generate training programs, with the coaches then to “personalize” them on the floor. But does this not risk exactly this requirement for clear, pre-established criteria? If the purpose is unclear to the coach then evaluating whether it was met becomes guesswork rather than coaching. Intention is not only required from the athlete, but from the coach as well.

But, to get back on track:

When a task is identified as too easy, the solution is not to abandon it, but to change the conditions under which the same goal is pursued. The challenge can be increased by designing it as more whole practice, or the movement can remain intact while the challenge is altered, done with tighter time constraints, or performed with less visual information. Music can be turned up, familiar placement in the practice room can be changed, and fatigue, asymmetry, altered starting positions, or tighter success criteria can all raise the cognitive and coordinative demands without fragmenting the skill.

This preserves what the science insists on and what Borges illustrates: repetition only educates when it is not repetition in the literal sense. Learning emerges from encountering the same problem under conditions that are similar enough to recognize, yet different enough to require adjustment.

A coach does not need to chase either perfect movement nor complexity for its own sake. Their task is to keep practice from becoming a perfect copy of itself. That would be where learning stops.

Categories
Reading Borges Training theory

Reading Borges part 1: No one actually wants a forest

Most training plans assume that tomorrow will function more or less like today. The same athlete with the same capacities. Just add a little more load, or do a little more of the same, and the response will be progress.

But anyone who has coached for more than a season knows how fragile that assumption is. A bad night of sleep, a small ache, a missed lift, a lost game, a loss of confidence and suddenly the plan that worked so well no longer fits the person standing in front of you.

At that moment, the problem isn’t effort or discipline. It’s that the map you were following no longer matches the terrain. I didn’t find a language for that moment in training textbooks. I found it in the short fiction of Jorge Luis Borges.

Borges writes about uncertainty, infinity, chance and time, all systems that can’t be fully mapped. This is a useful counterweight to the linear habits coaching often falls back on. His work refuses neat explanations, and that refusal can shake loose old ways of thinking or, just as usefully, strengthen them if they still hold.

While Borges is not a theorist of learning, he may be the best writer we have on what it feels like to push a system beyond its current limits, to look ahead without knowing how things will work out, and isn’t that what it feels like to learn?

Historically, both coaching practice and cognitive science have leaned toward control narratives. If you can break a skill into parts, sequence them correctly, and repeat them enough times, improvement should follow. That logic is tidy, attractive, and reassuring, especially in environments that crave measurable outcomes.

If you listen to how people talk about learning, you’ll notice a strange pattern: progress is often imagined like a graph in a powerpoint diagram: a line moving steadily upward, with a dip here and there for tasteful realism. Put in good work, repeat the correct pattern, follow the program, and the skill will “stick”.

Pedagogy absorbed the assumptions of industrial thinking: standardize the input, get standardized outputs. Psychology focused on error reduction: eliminate variability, reinforce the desired behavior. Sports coaching embraced the notion of an “ideal technique” and set out to sculpt athletes into approximations of biomechanical models.

It comes as no surprise, then, that exercise science absorbed these assumptions as well. Most planning of training assumed a top-down approach where adaptation could be predicted so reliably that you could plan backwards from a desired future capacity. Clear phases, defined objectives, load progressions that marched forward with the confidence of a train timetable.

The application of such models is highly structured and provides clear definitions at each stage. The idea is that peak performance arrives in a controlled way as the phases are neatly stacked on top of each other, maximizing the chance of hitting performance goals while minimizing the risk of overtraining.

But this requires a strict commitment to finishing each phase before starting the next, which introduces obvious problems. What happens if the athlete doesn’t respond to training the way we thought? What happens with injuries or illness? Do we keep building? Do we go back? And if we go back, where to? To the point where we got held up? Or do we account for the capacity we may have lost during sick leave?

A runner struggling after an illness isn’t just “behind schedule”, their whole rhythm of training shifts, and the neat phases we planned suddenly feel like papers caught by the wind.

But these are disturbing questions, that simply did not fit the dominant metaphors of the time: machines, programs, spreadsheets, blueprints. Machinery doesn’t like wobble. Athletes however, they wobble. All the time.

The Garden of Forking Paths - Jose Luis Borges - The Geecologist

In 1941 Borges published his short story The Garden of Forking Paths. In it he drops you in the middle of things. The first two pages are missing. Already, you’re off-balance. On the surface it looks like a spy story at the end of the first world war. A man on the run, pressed for time, trying to send a message to his German allies before being captured.

The narrator, Yu Tsun, tells us what happened after his cover was blown and he had only hours to act. Halfway through, the story changes tempo completely. The urgency dissolves, and instead of action, we are led into a quiet conversation about theories of time, labyrinths, and a strange book written by Yu Tsun’s ancestor, a book that was never meant to make sense in a linear way.

When the story returns to action, it does so abruptly. A murder takes place. The message is delivered, and the mission succeeds. And yet, it doesn’t feel right. The story leaves you with the sense that you’ve missed something.

At this point the reader has a choice: shrug and move on, or go back and read again. Those who do read again, with appropriated knowledge from the first pass, suddenly see how lines in the story that at the first reading appeared to be gibberish now makes sense. The story you thought was a spy plot is now something else entirely: a story about choices, consequences, and possibilities and that all possible futures exist, at the same time.

And read it again, with the knowledge about that, and yet another thread emerges, one that suggests the opposite of multiple possibilities, that whatever actions characters would have taken the outcome may have been fixed all along. There is a sudden insight, one that could not be made during the first few readings of the story, that the idea that all possible futures are realized at once is grand, but it doesn’t change much for us. Even if it was so, we never see those other worlds, and the only reality we can know is the one we live.

Borges leaves you without a map, and without the possibility of one. The only thing you are allowed to experience is the path you are on, now.

Isn’t this what practice feels like from the inside? Not a line in a power point, but branching paths. Each repetition changes what future repetitions are possible, and closes others. No privileged route, no secret shortcut, only the ongoing process of constantly selecting, adjusting, and navigating.

Notice. Choose. Move forward.

Even though the field of physiology already in the 1960s and 1970s moved on to more complex explanatory models for adaptation, shifting from homeostasis (“maintain a fixed baseline”) to allostasis (“constantly reorganize to meet changing demands”), training planning stayed rigid.

Pedagogy moved from linear, information-processing models toward ecological, relational, and systems-based explanations. Exercise science, even today, still leans heavily on Hans Selye’s theories of stress from the 1930s.

Coaching practice however had noticed the shift, and today there are considerable gaps between science and best practice, how training principles and training methods actually are applied. Today the term “ecological” gets thrown around also in our field.

But our tools remain built for sets, reps, percentages. You can’t put something vague into a spreadsheet. The times had no wiggle-room, so the planning stayed linear even after the understanding shifted.

“Ecology” sounds appealing enough, but no one actually wants a forest. They want a map, clear lines, predictable outcomes.

The real challenge isn’t being convinced, in theory, that the world isn’t linear. The challenge is acting non-linear. Partly because linear thinking is what most courses and training literature teach us, but also because the language of clear, predictable consequences is baked into the world, not just in training, but everywhere we look.

Can we use Borges here, not as a criticism, but as a kind of metaphor for how one can think in a different way, or at least approach such thinking?

To borrow Borges’s imagery: when we coach, it’s less about trying to guide people along the “correct” path through their labyrinth, because such a path might not exists, and even if it did, we wouldn’t be able to see it.

Our job as coaches isn’t to simplify complexity but to help the athlete stay with it without becoming overwhelmed, and then, when the moment is right, raise the demands. Regression isn’t failure, but reorganization (that may or may not be favorable in the long term). Standstill, on broader scale, is a neccesary prelude to the branching of possible next steps, and as such nothing to fear but to live with.

In a forest, progress isn’t something you march towards. It’s something that grows around you.

Still, all too often, when coaches, or any other theoretician shines the light on “what others do” or “what this theory says”, they stop after pointing at what might be a problem with that practice or theory. The internet is full of commentary and remarkably short on usable advice. To turn theory into practice, we need to go all the way: the real process, real situations. What would I actually do here? Get some real skin in the game, not just watch from the sidelines.

Contrary to the common saying: it doesn’t matter how big a toolbox you have, how many cues, drills, or clever progressions you’ve collected, if you haven’t also trained your coaches eye to see how situations differ. Case examples force you to look, to compare, to discriminate, to ask “why this here?” They keep you from assuming sameness where there is variation.

The snatch is used in sports because it develops superior, full-body athleticism by building explosive power, speed, strength, coordination, and mobility, crucial for activities like sprinting, jumping, throwing, and hitting, while also enhancing core stability and injury prevention through its complex, high-velocity, full-body movement pattern. 

It is both one of the simplest movements and one of the most complex. On paper, it’s just one instruction: lift a barbell from the ground with straight arms and catch it overhead, also with straight arms. But the moment you try it, you discover it’s also a very long, continuous sequence, moving the bar the greatest distance it can possibly travel, from the floor to full overhead lockout, while you drop under it, and then stand it up.

Each position in the snatch has to allow you to put force into the bar in a useful direction. If you add speed in the wrong direction, your strength becomes a problem rather than helpful. The faster the bar is moving off-line the harder it becomes to bring it back and save the lift.

Each position, then, is a kind of branching point. Your ability to find that position and control it shapes what paths remain available to you next. A sound position opens up possibilities, a poor one collapses them. Those possibilities aren’t knowable in advance, you discover them by getting there.

We need to plan and prescribe training, to give it direction and fit it into our lives. We usually do this by stipulating sets and reps and the weight to be lifted. That works, up to a point. But it says very little about how the weight is moved. To address that, we need more than volume and load. We need a language, a framework, that lets us prioritize and strengthen positions within the lift.

That’s why we, when we coach this lift, should look for the first position that breaks down, rather than trying to fix whatever goes wrong later in the lift. Those later errors are usually just the visible consequences of an earlier misalignment. Until the root position is addressed, the downstream problems aren’t really “fixable”. They’re symptoms of a branching that already happened.

Branching positions of the snatch. From left to right: starting position, bar at knee, power position, catch position

Having identified at what branching point in the snatch begins to break down, the position where our ability to organize internal and external force forces us out of position, we design drills toward strengthening the transition from the last position the athlete can still control to the first one they cannot. That is this athlete’s true edge of skill.

External demands (heavier load, faster bar speed), internal limits (strength, mobility, coordination), and the athlete’s psychological state (confidence, hesitation, fear of missing, arousal level) all shift where that edge shows up.

What this process gives us is not a way to perfect technique, but a way to locate where technique is currently possible. Progress, then, is less about chasing an ideal version of the snatch and more about widening the corridor of stable options the athlete can navigate. Coaching becomes the work of helping the athlete explore more of it without being overwhelmed.

My process is then:

1. Identify the first branching point where the athlete loses control of the bar’s direction. Look for loss of balance, posture, or force orientation.

2. Design practice that strengthens that specific position. This is often made unnecessarily complicated. You rarely need exotic drills or movements unrelated to the task. My approach is almost always some variation of:

  1. Finding and holding the position – lowering into it deliberately and stabilizing it.
  2. Starting the lift from that position – reducing everything except the transition we care about.
  3. Starting from the preceding position – adding just enough context to challenge the transition.
  4. Performing fuller versions of the lift – but limiting complexity by slowing the approach into the compromised position, adding pauses, or otherwise damping the speed of error.

3. Evaluate progress continually, remembering that stability at one load (or, remembering the influence from the psychological state of the athlete, even a specific day!) doesn’t guarantee stability at the next. As soon as external demands change, the capacity to control key positions of the lift may again be insufficient, and the work of strengthen that ability begins again.

Could the same argument be made without involving Borges at all? Probably. But engaging with stories like this trains us to notice the moment where systematic explanation runs out and living systems begin. Exercise science alone, for all its contributions, still struggles to describe that territory.

Research and studies is very important, of course, but also fiction, biographies, essays. Not because they explain reality better, but because they resist simplifying it. They train you to notice context, to hold more than one perspective at once, and to see differences where you might otherwise assume sameness.

What this awareness allows is something practical. The branching positions of the snatch are not metaphors, but places in the movement where futures actually diverge. Designing practice around them is a way of working with the system as it is, not as the spreadsheet wishes it to be.

Still, it would be a mistake to read this as an argument against variation or full-movement practice. Slowing the lift down, isolating transitions, or emphasizing specific positions can reduce complexity enough for the athlete to regain control where it was lost. But reducing a movement also reduces its errors. Error, as long as it isn’t catastrophic, is simply variation.

Variation is protective. There isn’t much learning in a “perfect” lift. So the goal is to reduce complexity only to the point where learning becomes possible again, but not so far that learning disappears with it.

Categories
Coaching philosophy Education for grown-ups Rants

Teaching without ends

”The teacher must be capable of being more teachable than the apprentices”

Martin Heidegger

What separates successful athletes from merely athletes is the ability to execute fast and intense movements.

However, the attempt to forcefully perform a movement will create tension in muscles other than those needed for the movement, resisting the movement rather than supporting it. If you tell people to focus on engaging a muscle, it makes them think, which slows down movement. You can’t be thinking about your “traps”, “glutes” or “lats” when you need to move fast.

Relaxing helps to avoid giving force to the movement, instead letting the force come from the momentum of a turn of a foot or the hip, from a step or a stance, from the precision of the directness of the movement.

Moreover, relaxing is not only about the physical effort. It is also a matter of attitude, both in the moment and in the approach to training. Practicing and performing requires a quiet mind: a mind that is empty of expectations, ideas, and presuppositions. A mind that just does it.

How could one understand what it means to relax in a particular movement until one mastered that movement and, in a way, has become that movement, when at the same time mastery of the movement in itself involves already being relaxed. How can we teach and explain something that seems to require an experience of that thing in order to understand it?

It seems impossible to teach such subjective abilities through only direct instructions of how particular movements are performed. Rather it seems that coaching should be as much about showing the method of practicing, as giving direct instructions, and to instill faith in those methods.

This requires expertise, knowledge and facts, but also courage, empathy and understanding, and sometimes I think coaches spend a little too much time developing the first of these qualities, and a little too little time on the others.

One of my favorite pastimes is watching coaches who balance all these qualities when they teach, watching them expertly swing in tune with a group of students and guide them to new learnings about themselves and others. Something similar to the conducted attunement of an orchestra, where there is harmony between different instruments that can both be recognized as part of the same melody, as well as distinctly different from each other. 

Watching that makes me all warm inside.

I once got reprimanded by my seniors for saying in an opening speech for a course that I was about to teach that I was “a coach just like them, only possibly with more experience of teaching”, and that I invited open discussions that coming weekend, in order to create a better course.

This apparently, by my seniors standards, gave a bad impression of my organization. I was to be clear that I was to teach, to instruct, and the attendees would take in my knowledge. There had to be a clear hierarchy, for the pupils to take me as seriously.

I do not agree with them.

When it comes to parenthood, something that is often stressed is the importance of consistency with decisions and consequences. It is said to cause confusion when parents change their mind, and that this will harm the process of learning and hinder the conformation to the social sanctions that govern our practices.

Personally I think that what is really detrimental to this process of learning is when the parent does not change their mind when confronted by sound arguments.

The art of coaching is no different in this respect. Arguments are something to be taken seriously and compromises are often both possible and necessary.

As a coach or teacher, you can rely on the power you have by virtue of your office. It can be the right to distribute tasks, decide what is wrong or right, promote or demote, punish or reward. But there is also another type of power, a more informal one, which is based on being the one with the most experience or the greatest wisdom.

Submission is never the most developmental approach in any context or relationship. If you want to see commitment and development over time, there are many indications that it is wiser to lean more on the informal power than the formal one.

“The community stagnates without the impulse of the individual. The impulse dies away without the sympathy of the community.”

William James

In our time, there is often a call for strong leaders who are clear and know the art of simplification, but what we need is primarily something else: Leaders who stop managing, manipulating and making fools of their followers or pupils.

The coach, much like his pupil, must have an open mind to oppose his natural reaction to get stuck in rigid models that might not apply to this situation. He must resist his tendency to look for sets of rules, for an explanation, a formal notion or something else that does not capture all the complexity of a concept such as “learning”.

But all this is fine and dandy – yeah yeah – “as a coach you need to keep your eyes open, adapt to situations and try not to be Hitler”? Isn’t this just another way of saying “it depends”? And as with all arguments that advance to this, necessary but insufficient point we need now to proceed to what it actually depends upon, or what we can do to make better decisions here and now.

So I am going to make two practical suggestions on how further the chances to be that good coach, the one with the “open eyes”.

“Knowledge consists of knowing that a tomato is a fruit, and wisdom consists of not putting it in a fruit salad”

Miles Kington

1. Describe before explaining

While athletes might be lacking in scientific knowledge, they tend to know a fair bit about their sports, and their practice of them. Discussions with them on these matters easily extend both into how to use the skills you have been working on in live action, and to sharpen the drills for improving them.

Ask the apparent questions in order to see what is already in front of your eyes: When do athletes struggle in racing or during competition?

At this point rid yourself of all the physiological models you have learned and describe those situations without explaining why they happen. That will momentarily rid you of preconceptions, and illuminate the path forward.

Use the language of the sport which is familiar to the athlete. You will move into a territory of training where your athletes have knowledge to add to yours. This will lead to relevant discussions on how to tweak the drills you will choose for them.

2. Learn a new skill

Us coaches do a lot of hard things like standing in front of a lot of people talking, directing and making decisions. But isn’t it often enough also the case that we no longer challenge ourselves with new skills while at the same time ask our athletes to do just that?

At this point in time we are often so far removed from learning new motor skills ourselves that we lose out on this aspect when we try to motivate people and encourage them when they learn such new skills that we ask them to do.

Perhaps we could be even better coaches if we would keep up to date with that feeling of how frustrating it is to be bad at something. How it is to damn well know how to do something, but still not be able to show it.

It is frustrating to fail. It requires finding positives in parts when the whole is a mess. Remembering this could be useful.

When asked for help or coaching we all too often show the final product, instead of meeting them where they are now. Instead of coming up with drills simple enough to provide a possibility for relaxation we show off.

Doing so can be more than a little demoralizing, and maybe we would recognize this better if we found ourselves on the other side of these situations regardless of how senior we are.

“A teacher who can show good, or indeed astounding results while he is teaching, is still not on that account a good teacher, for it may be that, while his pupils are under his immediate influence, he raises them to a level which is not natural to them, without developing their own capacities for work at this level, so that they immediately decline again once the teacher leaves the schoolroom.”

Ludwig Wittgenstein

Let’s take a practical example of bad coaching, where the coach specifically did not follow the advice above. The result was alienation of the athlete, with the risk of the athlete walking away from the challenge or even quit the sport.

The sport of this particular athlete was cycling, and to give you some background I could tell you about the short summers and long winters in Sweden, meaning a large chunk of the yearly training has to be done indoors.

When cycling on a spinning bike or a bike steadily mounted in a machine to provide resistance, the riders only have to focus on producing power, whereas normally they also have to control the direction and stability.

One of my neighbors asked me if I could show him how to ride a bike on rollers, you know, the kind of rollers that you just set a regular bike on. The bike moves freely, meaning it could easily fall off the rollers if you make the wrong movements.

Cycling on rollers might provide less physiological overload, because of their larger demands for creating stability. Peak force and power output are lower than on an ergometer, but the need for balance while producing it makes this training quite similar to actual cycling. I have seen far more transfer of improvements to real cycling because of this.

The internet is littered with videos of failed attempts while riding rollers . This is not strange at all, because in the beginning it’s a little bit like trying to run on ice.

One has to be relaxed, but as we have noted one does not relax just because one is being told to do so. This video I found on random is a very reasonable first attempt.

Anyway, I filmed myself riding in my living room and sent the video “for inspiration”.

How do you think he felt when he watched this? How much could he value whatever large steps forward he took on his first sessions, when he put them relative to this rather than where he started from?

Experts in all fields appear fluid and natural but in reality they have made conscious efforts to shape the way they perform. Simply having the same knowledge of how to perform exercise is not what makes great coaches great.

  • “The philosophy of dissonant children”, https://www.researchgate.net/publication/230167370_The_philosophy_of_dissonant_children_Stanley_cavell’s_wittgensteinian_philosophical_therapies_as_an_educational_conversation
  • “On Heidegger on Education and Questioning”, https://www.researchgate.net/publication/311857931_On_Heidegger_on_Education_and_Questioning
  • “Quiet Minding and Investing in Loss”, https://www.academia.edu/43704333/Quiet_Minding_and_Investing_in_Loss_An_Essay_on_Chu_Hsi_Kierkegaard_and_Indirect_Pedagogy_in_Chinese_Martial_Arts
  • “Vi behöver en annan sorts ledare”, https://sverigesradio.se/avsnitt/att-vara-ledare-ar-inte-att-alltid-ha-ratt
Categories
Coaching philosophy Practical application Problem solving Rants

Commitment is an act, not a word.

“Only in failure, in the greatness of a catastrophe, can you know someone.”

E.M. Cioran

Picture some middle-aged dude with the habit of going down to the local wrestling club, always challenging the newcomers in the kids class to matches of greco-roman wrestling. He’s crushing them! Ripping them up! Throwing their little bodies in the air, slamming them back down on the floor, trash talking… He is 183-0 against them. He is the MAN.

Well, if Alexander Karelin, widely considered to be the greatest Greco-Roman wrestler of all time, would go down to the same club to wrestle the same kids he too would be 183-0 against those kids. If this was all that we had to go on to decide which is the better wrestler of our dude and the “The crane from Siberia”, apart from reverting into aesthetics, how would we ever know.

And how could our middle-aged friend ever truly know how good of a wrestler he is until he dares to challenge himself enough to fail, and therefore see where his limitations are?

Uncertainty is scary, but when you accept that uncertainty of things, the flip-side of that is that now you can go anywhere. If you accept the dangers of the Savanna, for example, you don’t have to stay crammed inside of that armored car on the road watching things from a distance.

But just like any experience that is quite special, it comes with a cost. And the cost of this type of existence is anxiety, dread, and all the rest of the feelings that come with plunging into the unknown.

For some to seek out, and stay, at these borders of what is comfortable comes completely natural.

For instance I remember meeting Dragos Stanica for the first and unfortunately only time in my life when I was teaching a Course for Eleiko in Brazil a few years back, while the Brazilian nationals in olympic weightlifting was held at the same venue.

Dragos, a former weightlifter, who represented Romania in the 1988 Games in Seoul, South Korea, now lives on the outskirts of Rio de Janeiro from where he has his base, serving as the national coach for Brazilian weightlifting.

One of the nights, after the final day of competition, me and my colleague got Dragos by our table and when we got him started talking we never wanted it to end. That man had so many great stories from his life to tell, and it seemed all we had to do to enjoy them was to keep getting him (and us) beer.

He told us about his life, from his upbringing in a poor Romania, how he got to be a successful weightlifter, got recruited by a circus traveling the world, to stories on how he became the physical trainer for most of the Brazilian UFC superstars, and it just kept going, all the way into how he now lived permanently in a Brazilian favela, helping kids to learn to overcome their environment with his little weightlifting club as his teaching tool.

Of all the stories he told, the one I most often think back upon is the story of him starting weightlifting. He was 13 years old when he first ventured into a weightlifting club located in a basement.

“The lightest barbell they had was permanently loaded with 50 kilos, and I barely weighed more than that”, he said, “they showed me other lifters snatching it, and I wanted to do the same, but I failed miserably of course”.

He went on to give a picturesque description of how he came back, week after week, month after month, always failing to snatch the barbell from the floor over his head. It all seemed completely futile of course, but it became an obsession to him.

“And then one day I snatched it. I was very surprised” and he took another sip of the Brazilian beer, looking as happy as he must have been in that basement on that day so many years ago.

”If to describe a misery were as easy to live through it!”

E.M. Cioran

But most people are not like Dragos, not even if they are elite athletes. Faced with the possibility of failure, many might rather walk away from the challenge completely if not helped by someone to stand firm in a sudden storm of emotions.

For infants, all signals from the body or the world around them are causes of panic and result in screaming because they have not yet learned to put them into words.

With the help of its surroundings, it then trains itself to interpret both it and itself, and many things are then no longer perceived as threatening. This allows the child to move on and make wiser decisions. The screams are exchanged for productive responses.

But that presupposes that it has not been trained to shout when it is just hungry or experiencing something else normal.

That, in turn, requires the help of responsible adults.

Anxiety is an integral part of performing in sport for a majority of athletes, regardless of what level they perform. Being able to manage that anxiety can really help to produce a better performance. Under pressure, some athletes can produce a “peak performance” where they actually perform better, but the risk to be overcome with nerves is also always present.

This, in my mind, is one of the most important tasks of the coach: to help and guide their athletes to dare to challenge themselves, to dare to stay in these uncertain situations despite the flush of emotions that may overcome them. This is hardly done by pretending that those emotions aren’t real.

Many times I have seen trainers reassure their athletes when affirmation more likely was what they needed from them. One situation comes to mind, in the warming-up area for the European Regionals of CrossFit in Madrid. I was there coaching team CrossFit Nordic in their pursuit to put them on the podium of the competition.

Arriving with the team to the warmup-up area to get ready for our first event, I saw this Swedish athlete who I knew, running and looking unhappy on one of the non-motorized treadmills. Knowing that the first individual event wasn’t until all of the team events finished up, I walked up to her and asked what she was doing there and where her coach was.

“I don’t think I can compete in the next event, I don’t think I am good enough” was her reply, and you could see in her eyes that she felt both scared and lonely.

After some time her trainer appeared, and I overheard his answers to her expressing her doubts of herself as “Come on, you’re great, you’ll do fine, stay strong!” and I watched her try to smile and to look strong.

This athlete quit individual competition after this Regionals, which was the athletes first.

Maybe this would not have happened if the coach, instead of trying to sweep the feelings of doubt under the rug, would have affirmed those feelings, helped to put some words on them, asked if she has felt like this before, if so what she did, and how that felt.

To tell her that it must be hard, but nevertheless normal to feel this way.

Anxiety is a state comprising both physical and psychological symptoms due to feeling apprehensive in relation to a perceived threat. Each individual may experience anxiety slightly differently and it also may differ from situation to situation. For example, one Olympic weightlifter I worked with couldn’t get themselves onto the platform without feeling like passing out, while many CrossFit athletes would be physically sick waiting in line for their heats, or cyclists frequently abandoning longer and tedious races, not because of tactical reasons, but overcome with feelings of doubt.

It is natural when experiencing anxiety to want to get rid of the feelings because they are unpleasant, therefore people can seek solutions to avoid feeling like that.

If the anxiety becomes extreme an athlete may even get to the point where the only way to not feel like that is to stop competing or even quit the sport. This is a solution, as it might put a stop to these strong unwanted feelings, but the athlete might by doing so lose what’s most important to them (their sport).

A better option would be to accept anxiety, embrace it and learn ways of living with it.

Using only reason and empiricism to do this will for some always fail, for these methods can not explain reality with certainty. Then, to be able to cope with this uncertainty, one must accept that the aversions causing these feelings are real and that they are felt in this way, rational or not.

Letting them be real, then look around to see the things, in the same situation, that are experienced as positive. While some things are outside of our control, uncertain and in many ways terrifying, some things are always not.

Continually doing so the floods of emotions experienced in these situations will be decreasing with time. The wolves that hunted you become dogs, in time they might even bring you your slippers.

– But I believe what you are experiencing is a feeling.
– It’s a horrible feeling.
– I can see it’s unpleasant.
– But like all feelings, it will surely pass.

From the movie “The Party” (2017), Directed by Sally Potter

This should not only be in the competitive setting. It has to start in the training hall, where one should not “win all workouts”. I am a huge believer in not pursuing perfection, for perfection is impossible to catch.

I have in previous posts argued that long periods of basic training has drawbacks when it comes to effectiveness and planning, producing unwanted adaptations, such as significant decreases in power and speed abilities, and taking up a lot of the training time available.

But these are not the only pitfalls of excessive periods of basic training.

First, the high intensity movements used in competition give the body fewer options to cope than using pre-tensioning strategies available through the stiffness of the muscles tendons. The lower intensity of basic training allows for, and it usually is done to strengthen the muscles contractile tissue.

But with less demands on the tendons, we risk that they become inefficient and come game time, when the luxury of inefficiency is not available leading to injuries (which put a stop to everything).

Second, getting back to my main point: if training looks too much like competition it becomes unbearable, or at least it does not provide enough variation to provide the means for improvements. But on the flipside, if it looks too little like competition it has no way of helping the athlete to cope, “learning the language of”, the uncertainty of competition.

Instead of more is more-approaches, where more necessarily means further from the demands found in competition, I once again propose a different not more-strategy.

Continuously challenging the individual participant by progressively increasing task difficulty during practice enhances motor learning and optimizes performance, while also helping the athlete to safely develop strategies to counter the frustration of being exposed to the slight possibility of failing.

“Failing to plan, is planning to fail”, and while this is good advice, as a coach you need to remember that the experience on the competition floor often is a very different experience despite all the training that precedes it, which often gives rise to emotions not able to plan for.

The way of being a better coach then turns out to be pretty similar in the training hall and on the field of competition: to take one’s nose out of the plan and look at the situation at hand.

  1. See possible improvements for each athlete and manipulate exercise in order for these improvements to arise.
  2. Do not reassure. This discounts the athlete’s fears, makes him doubt himself even more and reinforces the anxious behavior that got your attention. Avoid acting on your first impulse to counter them by reason. Instead: listen and confirm that feelings of anxiety, fear, doubt are normal.
  3. Do not say what an athlete should not do or cannot do (Such a list would be virtually endless and quite useless). Focus on communicating what he or she can or should do.

Experts in all fields appear fluid and natural but in reality they have made conscious efforts to shape the way they perform. Simply having the same knowledge of how to perform exercise is not what makes great coaches great.

If so many people know how to do a barbell clean and the basics of how to coach it, why are some so good at developing lifters and others are not?

Science is great for predicting the average response in a certain situation, and while this is a good starting point that is all it is. The great coach also realizes that they are working with humans, with all the unpredictability and erratic behavior that might follow from that.

Categories
Coaching philosophy Exercise selection Rants Training theory

Fail again. Fail better.

“The definition of insanity is doing the same thing over and over again and expecting a different result”

Because Einstein said it, it’s got to be true?

Well, first of all there is no substantive evidence that Einstein wrote or spoke the statement above. The linkage to the genius whose hair was always uncombed, clothing always disheveled, and who never wore socks occurred long after his death. It is one of many completely unsupported quotes attributed to him.

When one looks for the very influential statements’ real origins it seems like it originated in one of the twelve-step communities. Twelve-step programs are mutual aid organizations for the purpose of recovery from substance addictions, behavioral addictions and compulsions. Being communities who greatly value anonymity adds to the difficulty to identify a specific author to the saying.

Regardless of who first said what, the idea that one can try something and instantly see if it resulted in anything useful or not, is something that we mostly take for granted. From this we, usually without thinking much about it, similarly take for granted that if something did produce positive effects it would do so again if we kept doing it. 

When doing so we fail to see that not all change and not all strains within a system are visible on it’s outside or by the parameters we measure it by.

Further it can make us rush on to try new things too soon. To give up when we would need to be patient and let the things we do bring about the change they could, given some time.

Systems can be analyzed in terms of the changes of their states over time. A state is an attempt to characterize, or define, a system by a certain set of variables. When a system changes its state its variables also change as a response to its environment and a completely different behavior might emerge.

This change is called linear if it is directly proportional to time, the system’s current state, or changes in the environment. They are called nonlinear if it is not proportional to either of them. In a nonlinear system very small changes might sometimes give rise to great changes of the system, and vice-versa.

Complex systems are typically non-linear, changing at different rates depending on their states and their environment. They have stable states, called attractor states. These are states that are preferred, and govern system behavior to stay the same even if perturbed. They could also be unstable, at which the systems can be disrupted by a small perturbation.

Examples of complex systems are the ecosystem, the weather, forests, organisms, the human brain, infrastructure, social and economic organizations (like cities) and ultimately the entire universe.

When these attractors are in such unstable states, exposure to what might look like the same environment, or such tiny changes of it that they can hardly be seen, could quickly completely change the entire systems behavior.

This type of change, which characterizes much of nature, is often abrupt and discontinuous. Systems experience periods of turbulence as attractors destabilize and create the potential for phase transitions (sometimes called bifurcations or tipping points). During these transitions, systems reorganize into new patterns of functioning.

A familiar example is the transition from liquid water into gas when boiling water. Under gradually increasing heat, the water remains liquid until the tipping point of 100°C is met and the sudden transition toward the gaseous phase takes place.

If one wanted to boil water but gave up when nothing happened after a minute or two, one would be prematurely looking for other ways to get things cooking.

Samuel Beckett, winner of the Nobel Prize in Literature, and most famous for his play Waiting for Godot. A play that was famously described by Irish critic Vivian Mercier as in which “nothing happens, twice”.

Two dysfunctional men encounter others along the road as they wait forever and in vain for the arrival of someone named Godot. They fill their idle hours with a series of mundane acts and trivial conversations as the world of the play operates on nothingness.

Surely the author of such a play could offer a counterpoint to the dominating “definition of insanity”? Something more useful to handle the everyday struggle of nothingness without prematurely abandoning or giving up on one’s efforts?

Sure enough, In 1983 Beckett offered a different perspective in his work Worstward Ho:

“All of old. Nothing else ever. Ever tried. Ever failed. No matter. Try again. Fail again. Fail better.”

What Beckett is telling us is that no matter how good the attempt, all actions inevitably fail to be perfect, then one must make another attempt and another, and the effort is in the attempt – not in the product.

In a non-linear world one could be considered mad if one would think that doing the same thing over and over again could not produce a different result. For both the person and the environment where the action is carried out is always different, if only so subtly.

Possibly the hardest thing to do as a trainer is to back off. To realize that while you are very important in some parts of the process of learning, most of the time must be spent simply doing.

I have a friend who is a very accomplished trainer, and who have few superiors when it comes to designing exercises. His skillful eyes see not only unsatisfactory movement outcomes, but also at what point initial flaws that might be causing them arose. On top of that he has great understanding for manipulation of the exercise to open up for better movement patterns, as well as being skilled in communication.

We often teach together and his imagination and sharp eyes never seize to impress me. Then things go wrong. He’ll have the athlete do the exercise a few times, or maybe a week, watching closely. If he sees better outcomes, he goes on to take on the next pattern to be sharpened.

Change takes time.

Much like parents often end up trying to fulfill their dreams through their children, teachers often get too involved in the process. Over-coaching and pushing too quickly can be just detrimental to the development of new and efficient attractor states as the opposite.

In other words, it simply happens. The coach, the midwife of all those new skills, is simply momentarily assisting in the process, but not making it happen.

Practicing and performing require a quiet mind: a mind that is empty of expectations, ideas, and presuppositions, that is open to what happens in the presence of every aspect of a movement.

To be a masters trainer, on top of all your technical wisdom, you need to be patient.

  1. To see possible improvements and manipulate exercise in order for these improvements to arise.
  2. To communicate so that the student understands what constitutes a good rep versus a less good rep.
  3. Stepping away and letting the student find his or her way of increasing the frequency of good reps, until it is something done without thinking. The failed reps in the process is what eventually lets the good reps just happen. (very hard, and often forgotten)
  4. Staying cool and detached yet a little bit longer, remembering that just because some good reps are being done, it does not mean that they just happen, just yet. (requires the patience worthy of Buddha himself)

Coaches momentarily assisting the process I said… But sometimes that moment is long. One week? Four weeks? Months?

It is impossible to tell how long it takes for a new attractor state to emerge, but in my experience it varies not only between individuals, but also with time for the same person. All we have is to stay rooted in the present and to evaluate the fluctuations of the athletes results.

When an attractor is getting more stable there will be less fluctuations in performance. In order to see this we cannot vary the exercises and workouts too much.

A master coach who did take this to great lengths was Anatoliy Bondarchuk. A former Olympian himself, he turned to coaching after his career and is widely regarded as the most accomplished hammer throws coach of all times. He developed what can best be described as completely response-based programs. His method largely consisted of repeating the same session over and over again, with no wave loading of training variables and abilities, and no changes in strategic or qualitative elements.

Will there be no variance in such a system? Surely there will be, for in a complex world both the person and the environment is always slightly different.

Plotting the response to similar sessions or exercises over time one can clearly see the phase transitions of our athletes.

A program with little variation allows you to see the states of the system over time. When data and form seems stable, then we can also assume that the attractor states are stable. When this happens, but not before, we should be increasing task difficulty in order to force adaptations via yet more phase changes.

One note of warning though – one might be tempted to think that we now know how this athlete responds to training, and would be able to predict the time to adaptation or phase transitions for the athlete. But when a system changes its state, a different behavior will have emerged.

While we now know our process of exercise selection and communication likely functions well for this athlete, we can’t ever relax and be the lazy coach.

“For the young the days go fast and the years go slow; for the old the days go slow and the years go fast.”

Anna Quindlen

Regardless of what specific method one adheres to, for there are many possibly great ones, one thing I see more from the experienced coaches is that they are likely to let things take their time and by doing so allowing for more possible growth of their athletes.

Categories
Coaching philosophy Cycling Exercise selection The map or the territory Training theory

The map or the territory pt 3

Simplicity is the ultimate sophistication.

Leonardo da Vinci

In the first article of this series I explored the risks of assuming that there is something fundamental beneath the surface, which must first be optimized in order to increase performance later on. In the second article I challenged the need to continually increase physical training load, suggesting to focus instead on adaptation of task difficulty to where our athletes are exactly now. 

In this last article of the series we will continue to explore methods to stay in the present, and how the use of our language can help but also overthrow our attention to what is really going on and hinder the transfer of the exercises we prescribe.

As we have seen, the promise of the ideal is repeated over and over again but never fulfilled. When technology was invented to measure oxygen consumption, blood lactate concentrations and force it gave rise to new models for training. Now the recent ability to sequence DNA is looking to change the way we measure and prescribe training.

While this way of looking at the internal processes of the body certainly has merits to many sciences, it is still not able to add much to the decision process constructing training programs. Just like with the preceding reductionist approaches comes the same possible pitfalls. 

We could also measure the length of fascicles, concentrations or flux of chemicals, energy storage or the efficiency of the electron transport chain and… Well, it’s likely to be a mess to bring all those parts together in a general capacity. The whole is not the sum of its parts, despite how magnified they may be.

The aspects of things that are most important to us are hidden not because of their depth, but because of their simplicity and familiarity.

The philosopher Ludwig Wittgenstein once described the situation as it is as if a man is standing in a room facing a wall on which are painted a number of dummy doors. Wanting to get out, he would fumblingly try to open them, vainly trying them all, one after the other, over and over again. But, of course, it is quite useless. All the time, although he doesn’t realize it, there is a real door in the wall behind his back, and all he has to do is to turn around and open it.

Having explanatory models of how it all works, seems to be helping us to take the right actions. But the problem with the concept creation is that it assumes that by creating concepts, we can lay down in advance what it is we are thinking about. In plain English, there is really not much evidence supporting the theoretical concepts of phase potentiation, but we have a hard time to see this since it is all we know.

To help our man get out of the room all we have to do is make him look in a different direction. To do this we should turn things around, away from the safety of dogma, and look at what is hidden in plain sight.When do our athletes struggle in racing or during competition? Describe those situations without explaining why they happen.

This brings us to the topic of terminology, on how to best communicate with the people we coach.

Concept language is used to describe words or constructs that bundle a lot of actions and interactions under a simple word. To transmit less detail and more fundamental aspects of information faster and easier, mainly by experts of a defined field.

Complementary training, meaning all training carried out away from the field of the game, with the intention of helping successful execution of skills in the game itself (or a more functional life for that matter).

Coaches, specifically us who provide help with complementary training, are usually using the concept language of our field, as opposed to the language of the game itself. We use constructs that are natural in the gym, like “strength”, “strength endurance” and “speed”. We speak a language of “intensity”, “volume”, “sets” and “reps” with the athletes that we train.

When athletes are new to complementary training they usually struggle. They have a hard time to understand our lingo and to perform the training we prescribe with it. When we invite athletes into this world, filled with new mysteries to solve, they will eventually get better and better at speaking our language and doing our type of training.

But this was never the end goal.

It is not enough to show how clever we are by showing how obscure everything is

J.L. Austin

There is some evidence that memories are stored in the same brain regions as they are perceived. This means that not only what you mean when you phrase your coaching cues matter, but also how the athlete interprets them and in what context the training is carried out for their subsequent retrieval.

The way language seems to provide a gateway into athletes’ motor cortex is quite stunning. Studies show that when participants hear verbs like lick, pick and kick it activates the respective brain regions of the tongue, arms or legs.

By using language so different from the field of play, we might accidentally be creating a rift between the athletes training and the application of it. By using our concepts instead of mapping into the common language that is better understood by our trainees we are limiting the transferability of the training they do .

Sports is a practical matter. It is not about words, but rather about actions. Action language, on the contrary from concept language, is the language used to describe only relevant details in a clear, concise and objective way, transferring details without judgement, often with a more direct purpose. It tells what to do in a specific situation of a game.

When we start with what we see, rather than from physiological constructs, we are more likely to be able to create terminology that ties the action language of the sport and concepts of exercise science together. Then we can utilize this terminology in a coaching process that is individualized without becoming abstract.

The athletes will perform their exercises more purposeful and they will intuitively know how to use the skills they are strengthening. And, although they might not be well versed in your world, they often are very knowledgeable of their sport. They know themselves and they will be able to help improve those exercises in a constructive way.

In this the third series we will show how one could implement the proposed methods by using cycling sprinters as the example.

A muscle fiber generates tension through cross-bridges of actin and myosin. Under tension, the muscle can be made to lengthen, shorten, or remain the same. Muscles also have elastic properties where energy can be stored to increase force, but only for a very short time. When a muscle is not tense it is “slack”. To produce movement, that slack has to be removed by pretensioning.

At high speed and high power the demands for contraction velocity, pretensioning and efficiency of storage, and return of energy are greatly increased. As a result there is little positive transfer between different types of muscle contraction. In cycling most muscle actions are shortening contractions.

Cyclists produce higher peak pedal power and rate of force development on a stable cycle, commonly referenced to as an ergometer (like a watt bike, a spinning bike or a trainer) than when riding in a velodrome.

When sprinting on the ergometer, the riders only have to focus on producing maximum power, whereas on a bicycle they also have to control the direction and stability whilst trying to produce maximal power. Also, one of the biggest factor to overcome during cycling in aerodynamic drag which is not easily simulated in a gym.

Because of different demands there is an altered riding position observable as difference in hip, knee and ankle angles.

With the principle of specificity in mind there would seem to be arguments for the the track cyclist to train on the track, or to find other ways to challenge stability if that is not possible.

Torque-pedaling rate and power-pedaling rate relationships for laboratory and field tests, estimating “optimal cadence” in Elite track sprint cyclists (Gardner et al, 2005)

Cadence, or pedaling rate, is an important factor influencing the economy of motion, power output and the development of fatigue during cycling. In track sprinting the use of fixed gearing makes this a very important consideration at race day, but also to guide training. The inability to select the best gear for specific situations during a race, forces a decision on which gear would be overall most suitable for a rider in all situations. Some factors influencing this are the type of race, the opponent and the rider himself.

Bigger gears give the opportunity for higher maximum speed with less fatigue. If one is able to get up to speed and then to effectively spin it around, that is. With higher inertia comes higher demands of force.

There has been considerable research in what is called optimal cadence, the cadence where peak power is achieved. Given the importance of contraction velocity and efficiency in high speed and high power movement it is thought to provide important insight in the selection of pedaling rate, and therefore appropriate gearing.

Optimal cadence is highly correlated with the amount of fast-twitch muscle fibers, and in a sport where the ability to push bigger gears are so rewarded as it is in track cycling, there is likely not much drawback in continually training to increase their proportion. Given the low risk of gaining mass when doing large volumes of training, there is little reason for the road sprint cyclist to think differently.

As with other constructs there is a catch to letting peak power testing dictate training decisions. Those tests are almost always carried out with very little pre fatigue and from a stand still or low cadence. Following periods of exertion cadence at peak power has been shown to change. Higher velocity provides less time for cross bridges to form, and therefore the demands for the speed of contraction increases. The demands of the athlete shift with each situation and each athlete.

You can’t make an omelette without breaking some eggs…?

In a small country like Sweden, with a limited talent pool even in our national sports (football, ice hockey, skiing), we need to adapt our coaching to improve each person in front of us, rather than the other way around.

One would need to look at the specific situations each athlete struggles with to best construct exercises to increase their capacity in those situations.

Sven Westergren is the current Master national champion in Match sprinting. Match sprinting is the discipline where two opponents go head to head for 3 laps, or 750 meters. He is big and strong and able to push bigger gears than his smaller opponents. They however have the upper hand when it comes to quick bursts of acceleration from lower speed.

Tactics comes down to controlling the pace. If Sven is able to keep the base speed high enough to prevent aggressive “jumps” from his opponents they tire quickly, and have little to do when he eventually accelerates to top speed. In order to strengthen his ability to do so, exercises for acceleration and maximum speed can be constructed to involve a build-up beforehand.

With little access to the only Velodrome in Sweden, which is located more than 2 hours drive from where we live, and knowing that the transfer of skill development from ergometers to the track might be low, we do most of our training during winter season on resisted rollers. This is not ideal, but better than other options.

Rollers might provide less physiological overload, because their larger demands for creating stability. Peak force and power are lower than on an ergometer, but quite similar to the track, and we have seen more transfer of improvements on to the track because of this.

We should use our coaches’ eyes when we construct exercises for our athletes, but if we can formulate them with language well understood by our athletes, we are improving both their transferability and the chance for better feedback. A clear goal for our exercises also allows for better judging if the exercise was successfully executed and functional.

A possible way to create a helpful terminology would be to first define a game model based on the broad actions taken in their sport.

For track cyclists we could construct such a model by going through each broad component carried out in a race. A very simple example would be to specify the possible actions to master as the start, the acceleration, maximal speed and speed endurance.

For each of these areas we can assign suitable actions, which would be a good starting point in order to create a more individual and usable “dialect” of a general sports language. Actions however do take place within the boundaries of space and time. If we sat down in a car and all everything that was told to us was to “drive” the action would seem less connected to its environment than if we were also given instructions on how fast and in which direction.

Similarly our cues will also benefit from the inclusion of direction and distance.

Christoffer Eriksson is the Nordic Champion in Keirin. Keirin is an event similar to the match sprint but features between three and seven riders competing in a sprint race of 3 laps after having followed in the slipstream of a pacing motorbike for 3 laps. The motorbike gradually increases in speed before peeling off and letting the sprinters battle it out.  The event is fierce, fast and unpredictable, with many split-second decisions about when to hold and when to attack that have to be made under fatigue.

Christoffer has lower top speed than many of his opponents, but on the flipside he is perceptive and he does not tire easily. In competition he cannot just muscle himself to wins but instead has to see how the match unfolds. He wins by finding the opportunity to get a gap early, or to follow the strongest riders when they do so. Using his strength to not get boxed in, and accelerate to fill gaps is an important quality for him.

One exercise to practice this ability could be to build, then simulate staying on a wheel, relaxing to get some distance in order to use the slipstream to get enough speed to go past on the outside. We could call this exercise “hit, fly, hit”.

In order to build the language for this we should consider the actions involved in it. Most important is the verb that should be the main descriptions of the action to take. I’ve often used the word “push”, as it is pushing the pedal away we would like the athlete to do. But considering that pushing is something that could be done slow I prefer “punch”, which I think would be a perfectly fine option. You can push slowly, but you can’t imagine punching slowly.

Knowing about the very specific encoding of memory storage, I would like to use a word less associated with the upper body. I would propose using “stomp”, which would seem as a similar action as punching, but for the lower body, where power is most important for cycling.

When describing the exercise, I would use something like “Build up to speed and and then stomp as hard as you can to go faster, closing the distance to a breakaway rider. Then stay as smooth and effortless but without losing cadence, and then again stomp hard to accelerate past”.

In order to sharpen the action cue I prefer to shorten it to a minimum. Keep the action, direction and distance, and end up with “stomp fast forward”, and after the “fly part” again tell Christoffer to “stomp hard past”.

The exercise will be tied to race tactics, and we would be able to get a nice feedback loop going in order to improve future exercise according to the needs and skill level of the rider.

The skeptic could point out that the examples given in this series of articles appear to be quite simple. That all I do is to observe my athletes, and when I think I’ve seen what needs to be improved upon, I have them do that very thing. Yes, with some variation, and sure, carefully considering communication and possible improvements of the exercises – it all appears to be so simple.

They would certainly be right. Even though I would argue that doing the simple thing well, is not easy. Let’s also describe how one could use the same methods to develop something less like what is performed in the sport itself.

When an exercise is very specific, by definition it has a low degree of overload. If we would like to lift the middle of a rug from the floor, we would do best to direct most of our lifting to that point exactly. If we want to maximize how high we could get it, we would also benefit from at the same time lifting at the edges.

In elite sports, you rarely win with the distance of a landslide. More often with the small margins visible in the loser’s sigh. The athlete also needs the marginal gains found in general overload.

You have to appreciate the impact that variation and change has on how an athlete reacts to training across the board

Derek Evely

The upper body is involved at a remarkable extent when cycling hard compared to when cycling less hard. The degree of negative relation between upper body asymmetry and maximum cycling power production is quite exceptional.

This should not come as a surprise – in high intensity movement the opposing forces are so great that muscle fibers have to stay close to their optimum length, and as the feet are attached to the pedals, there is less flexibility of positions in the lower body. One can imagine how much this must challenge the trunk and the pelvis when force is applied into the pedals. Studies also indicate that compromised coordinative patterns for the ankle joint correlates with loss of power.

For the cyclist who wishes to win in a sprint this would seem to make an argument for

  • Upper body training (Pullups and Dips?)
  • Hip strengthening (Hip thrusts seem to be popular)
  • Core training (oh, those circuits that burn so good)
  • Ankle strengthening (Calf Raises, for more of that sweet burning sensation!).

While there is nothing wrong with these exercises, I would treat such isolation as things we do at the end of the session, after we’ve done everything else.

In movement, force produced by muscles moves through the body. Patterns between muscles occur with the changing demands of force in order to develop synergies. The whole body efficiently forms a unit capable of more force production than any of its muscles in isolation.

Again, with the principle of specificity in mind, there seems to be an argument for multi-joint compound movements in the gym to maximize transferability of increases of strength.

The need for variation is fulfilled already if we make sure that there is a large extent of overload.

“The human race shouldn’t have all its eggs in one basket, or on one planet. Let’s hope we can avoid dropping the basket until we have spread the load.”

Stephen Hawking

In bicycle sprinting you need to subdue very heavy resistance, especially in starts and acceleration. Further, these efforts must not make you so tired that you can continue to turn around those heavy gears the distance required to complete the race. Being strong for the sprinter is very specific.

In some of its disciplines, like in the match sprint and Keirin, a modernization of tactics has raised the need for top speed over acceleration. This has forced the riders into an arms race for the capacity to push bigger and bigger gears.

In earlier posts we have explored the balance between specificity and overload in the gym setting, and isolated the following basic rules

  1. Keep movement somewhat similar in movement patterns and stimuli
  2. Overload as much as possible while satisfying rule #1. Large load means larger neural adaptation and higher percentage of muscle fibers being recruited.
  3. And do not let the main movement mechanics break down or change during the set

I argued for single leg movements for developing maximal leg strength for sports played on one leg (cycling, team sports, track and field, racket sports, etc) and double leg movements for those that have movements performed symmetrically (powerlifting, weightlifting, CrossFit, etc).

Possibly we could tweak this even further.

Before we go on to explore this I’d like to point out that I do not propose to exclude single joint general movement, despite having less obvious benefit. In fact I have all of my athletes do such movements, like pull-ups and dips, but they do it late in the session, after the more contextual work is done.

The way our muscles in the lower body are structured allows for a unique role in the transformation of rotation in the knee joint into the production of high force. Biarticular muscles are muscles that cross two joints rather than just one, such as the hamstrings which cross both the hip and the knee. Rectus Femoris in our quadriceps and gastrocnemius in our calves also have this property.

These bi-articular characteristics allow for extending the joints one by one in a sequence called the proximal-to-distal sequence more commonly referenced as triple extension. Extension of these joints one by one allows at least one of them to have a favorable translation relationship throughout the full extension.

This sequence allows for the possibility of more net force production, but in order to function properly the extensions should be completed in a certain order.

An ankle collapsing during the pedal push does not translate into movement of the pedal, but still cost energy. To prevent this leakage of force efficient cycling pedaling depends upon the ability to keep the ankle locked into position.

If the push downwards is done with a highly extended or flexed ankle the extension movement becomes rapidly less efficient. It would seem that cycling therefore cannot fully use the benefits of the triple extension.

During the sprint, ankle joint power decreases more rapidly than power at other lower limb joints, while hip extensors and knee flexors sustain their power for a longer time at higher rate.

The hip extensors are also the strongest muscle group in all velocities, followed by knee extensors and hip flexors. The weakest muscle group are the ankle flexors.

This seems to further support that there are differences in the efficiency of the pushing sequence with fast cycling, possibly at least partly as a result of not being able to execute the triple extension in the most efficient sequence.

Road cycling too involve recurrent demand for high force output, with little possibilities for perfect execution of the the proximal-to-distal sequence

New inventions in technology to measure performance in endurance training changes the way training is conducted and planned. The way things work in the strength world is no different. Traditionally the measurement was the weight on the bar, but lately bar speed, or power, has been popularized as a way to monitor performance.

More contextual always means less optimal for overload, meaning that athletes will always have lower numbers to show for their efforts. The systemized way of using such constructs could potentially bias us to high performance in these constructs, rather than to look for more contextual performance increases.

It will also subconsciously nudge us toward movements with the highest efficiency, regardless if we do not have these options for movement execution on the field. This is often defended with references to higher neural stimuli of these exercises. High effort in more contextual movements will also have equally high neural stimuli, despite lower measurements, as an effect of their lower mechanical efficiency.

Very seldom do we train strength in the gym with our joints in such non-optimal positions. Since muscles do change their optimal length and other properties with exposure, this is the whole point of strength training, and given that the coordination of chains of muscle is no less trainable – maybe we should?

The standing start is no different from seated pedaling. If the knee joint and hip joint creates force by opening up, the ankle must stay fixated in order to translate this force from above into the pedal. If it does not there is a leakage of force.

As we found in an earlier article the split squat is a fine example of an exercise capable of generating a lot of force. Even more so with the added stability of the hands. We can see that the ability to transfer force through the ankle is one limiting factor in the video of the standing start above.

Possibly we could try to combine a dynamic high force output from the hips and the knee joints with a static high force demand of the ankle?

As cadence increases, the time we have to create force shorten.

Disregarding exactly what the optimal pedaling rate for high power sprinting is, it is definitely high enough to not allow for inefficiency. For us to develop efficiency to perform unloaded high intensity movements, we should practice pre-tensioning with the use of co-contracting muscles alone.

This could be done with high power ballistics movements, such as jumps, especially from static positions with the least possible help from pre-loading and counter movements. I see few drawbacks doing some of them from mechanically challenged positions similar to what you would find in bicycling.

The splinter in your eye is the best magnifying-glass.

Theodor W. Adorno

The main reason we still lean so much on these perfect systems of explanation for decision making is that they provide the false safety of the ideal. Numbers are clear and concise, actual situations are messy. But in that mess there is also information that is lost when quantified.

A magnifying glass quantifies and enlarges an image, but the spectator cannot truly construe meaning from what is magnified. Only when we get a “splinter in our eye” we are forced to stop to regard the things that do not fit in. The flaw in vision, becomes a way of seeing better.

To say something about particular situations risks exposing our ignorance. Our challenge then, becomes not to hide from our possible ignorance, but to embrace that risk.

Categories
CrossFit Exercise selection Skill training Strength training The map or the territory Training theory

The map or the territory pt 2

In the realm of sports science what can be thought of as classical periodization was originally discussed by Russian scientist Leo Matveyev and further expanded upon by Stone and Bompa. Periodization is a logical method of organizing training into sequential phases and cyclical time periods in order to increase the potential for achieving specific performance goals. All while minimizing the potential for overtraining.

Phase Potentiation is the strategic sequencing of programming phases to increase the potential of subsequent phases and to increase long term adaptive potential. Theoretically, using this concept, peak performance occurs in a controlled way as the phases are stacked on top of each other.

When examining the success of classical periodization concepts they fail to convince of their superiority over more concurrent approaches to the planning of training.

Not only are these long detailed and rigid plans vulnerable to unplanned periods of non-training – what do we do when the athlete gets ill? – but also that we just miss our mark, either on the resources available for training, or the speed of progress we ended up with. As we are working under either of the two false assumptions that averaged group-based trends accurately reflect likely individual responses, or that the individual response can be extrapolated to work for a group – our plan will only provide a false sense of security.

These methods with long cycles of mostly general work are also quite time consuming. For most sports disciplines, the packed competition schedule makes it difficult for coaches to adopt them, as there is simply not enough time during the season to improve poor form.

However, the most important drawback is their very low rates of effectiveness. When scientists have looked at the amount of athletes who are achieving the season’s best result at the seasons most important events, like World championships and Olympic games, the results are disheartening. Seldom if ever more than 1/4th of the athletes manage to deliver their top results for that season.

The theoretical and speculative “delayed training effect” concept assumes that training basic capacities at earlier phases of the training plan has positive effects on actual performance long after they are taken out of the training programs, replaced by more sport specific exercises. They also produce unwanted adaptations, such as significant decreases in power and speed abilities. Coaches might ask themselves whether basic training is a real basis for competitive performance, or whether it is a loss of precious time to athletes.

To be fair, basic training is not only done for peak performance but also for the sake of injury prevention. There is also plenty of evidence suggesting that what is likely responsible for a large proportion of non-contact, soft-tissue injuries is not training load as such, but rather excessive and rapid increases of them.

It is likely that the positive adaptations in muscles and tendons provided by longer periods of basic training may also be obtained by typical strength and power exercises. Exercises which can be implemented with little to no negative effects during the course of the season.

The stakes of unsuccessful performance at key competitions are high, with evidence suggesting that more severe psychological consequences are a distinct possibility. Failure to meet performance expectations include anxiety, interpersonal hypersensitivity and coach-athlete relationships falling apart.

“Speed is the most precious thing in swimming. It is what it is all about. I do not understand why you would spend weeks and months not training speed, then hoping it will come back when you taper and race. I believe you must always be within one second of your personal best time at all times of the year. That you must train for speed all year round. That your sprinters must sprint often and race regularly throughout the year.”

Gennadi Touretski

In the 90s the “Speed through Endurance” philosophy that reigned supreme in Australian swimming was challenged by the Russian coach Gennadi Touretski. This “more is more” philosophy was to work hard to first develop an aerobic base for 10 to 16 weeks (or even longer!), then to significantly reduce training volume close to the competition. The idea was that the more you swim, the more efficient you become and the more efficient you are the faster you can swim.

Touretski, the coach of one of the sports all time greats, Alexander Popov, was recruited to rejuvenate Australian swimming after a poor Olympic result and he did so by removing the (imaginary) certainty of linear adaptations provided by a base training phase.

He warned to assume speed will return once it is lost, and was wise doing so. The “delayed training effect” is not completely supported either by science or practice and its use as a tool to improve actual results are very unpredictable. There is simply not much basis to sustain the idea that the body is ordered into basic and specific capacities and that the overloading of a given basic capacity will suddenly “supercompensate” later in the training cycle.

When you have a capacity, you can certainly lose it (and haven’t we all experienced that). But that risk is way lower than the hope for you to gain a completely new capacity at a later point in time. For that reason he included speed training at all times of the training program, throughout all of the year.

“I think coaches do too many drills. Drills do not improve technique. They teach the basic movements of the stroke. To improve technique you must work with the individual swimmer, over a range of speeds, from slow to race speed and give them constant feedback about their technique, talk to them about how it feels and help them to develop their own technique. Every swimmer is different – every technique is different.”

Gennadi Touretski

Instead of general drills he believed that technique is a personal thing, and that training prescription should not be about doing a lot of general drills. Rather it should be about optimizing the technical efficiency of the stroke of the individual swimmer. Start with what you see, and practice what you see is needed for that particular athlete.

He would walk with his swimmers continuously throughout the session, ask them to swim initially at a slow speed, then have them progressively increase speed until he would notice a technique inefficiency. He would then describe rather than explain what happened and then figure out a cue to address the inefficiency he had seen.

There is plenty of evidence to support that increasing the physical load of training in the form of exercise intensity, volume or duration can be successful in order to enhance training adaptations.

When looking for the optimal adaptation found at the upper limit of tolerance, we expose ourselves to very small safety-margins of error. The presence of deep uncertainties linked to working with human beings challenges decision making by questioning the robustness of all purportedly optimal solutions. Knowledge about historical adaptation yields little to no information about how our “optimal” solution performs if the future surprises us, and they do not guide us to solutions that might work well if the predicted future does not come to pass.

Physical load can only be increased so much, and often this “progressively do more, do harder”-philosophy eventually pushes athletes into injury. And regardless of the progress made before this, injuries put and end to all progress.

Traditional methods for decision making require agreement about the current and future conditions and only then to analyze our decision options.

In a paper published by the World Bank on developing new processes for decision making under deep uncertainty, the research group suggested that alternative methodologies can help in managing uncertainty. These methods start the other way around by stress-testing options under a wide range of plausible conditions. All without requiring us to agree on which conditions are more or less likely, and against a set of objectives.

In the context of sports performance the traditional methodology would be to construct a training plan by starting out estimating the future capacity, form and other factors. For example to predict how much a specific squat cycle would increase squat numbers, and how much that in turn would affect sport performance in specific numbers. Only after these predictions are made we would evaluate the possible upside and downside under these assumptions.

This is problematic on two levels. First, many important assumptions are buried in models, rather than in front of decision makers and therefore vulnerable to bias. Second, many factors are difficult, if not impossible, to predict and risk to cause a gridlock in the decision process. 

As an alternative, we could identify the plan that is robust, working well across all the scenarios by “stress-testing” our options under a wide range of plausible conditions. All without requiring us to decide or agree upon which conditions are more or less likely.

This means to imagine different outcomes from many possible methods. Squat numbers increasing by 15kg, 10kg, 5kg, staying the same or even regressing. Which methods end up with the highest satisfaction and lowest regret under all possible outcomes, including high or low transfer to sport performance?

When faced with the possibility of multiple outcomes we will end up choosing “no-regret” or “low-regret” decisions. Decisions on reduced time horizons that have high utility no matter what the future brings. They will be more reversible and flexible, and have larger safety-margins.

In order to learn a skill, like the strict muscle-up as shown in the video above for example, do we really have to increase the physical training load? Or could we limit explanation and predictions in order to concentrate on when our athletes struggle now in the skill.

Continuously challenging the individual participant by progressively increasing task difficulty during long-term motor practice enhances motor learning and optimizes performance. Such progressive long-term adaptation to individual skill level not only enhances learning, but does so without necessarily increasing either the volume or the intensity of training.

Simplicity is key both for scalability and to see what is actually driving the trend without the distraction of too many variables. Managing a program of only slight changes and frequent evaluations allows for it to be data driven (as trend analysis is time-sensitive and time-powered).

All of this seems to suggest to use different, not more and often but little-approaches rather than to speculate on theoretical basic capacities, then build a base and to expect linear adaptations.

The old “more is more” approach is still very much ingrained in our way of thinking and planning. That is quite obvious when one looks at and listen to coaches who would subscribe to these theories of learning, but often still feel obliged to offer a progression of physical overload throughout their athletes cycles. Change is quite hard.

Is this the perfect progression to learn or strengthen a skill? Certainly not!

If anything should be clear by now it is that there will always be cases that are different from all other cases. Every method has its place. 

I can also picture you thinking that, well, “those examples you have given are too easy. Sure, in strength sports you can get away with performing the specific skill, not something more basic or different, but simply overloaded at the level that the athlete is, but what about other sports not practiced with a barbell or a set of rings?”. Well, stay tuned for more examples of practical implementations of these principles in part 3.

I’ll leave you with the words of the great Touretski, who may have passed on last year, but whose actions and words hopefully will live on for long.

Dare to be different. Doing the same thing as everyone else is a doomed strategy and a flawed philosophy.

Categories
CrossFit Exercise selection The map or the territory Training theory Weightlifting

The map or the territory pt 1

“In early life I thought of studying economics, but had found it too difficult!”

Max Planck

In order to optimize performance, training theory has followed it’s fellow scientific endeavors looking deeper and deeper into details of their fields of study in a search for more detailed models of the world. These models are thought to provide more insight into underlying factors of performance. By uncovering them we can then design more meaningful training interventions. This manifests itself in metaphors like “the man as a machine”.

Similar to what Sigmund Freud did in psychology, when he presented the idea that thoughts and emotions outside of our awareness continue to exert an influence on our behavior. Even though we are unconscious of these underlying influences, physiology too has focused on hidden thresholds and reduced causal models of explanation for performance. The hope is to create better and more stable athletes built “from the ground up” and upon more basic conditions for performance than what can be seen with the eye alone.

While this project certainly has merits, it can also obscure the vision from what is “hidden in plain sight”. When searching for what is within and by looking deeper behind what is apparent, you will lose sight of how a scientific area is connected to other scientific areas: how things “just work” in the common world. When one has dug a deep enough hole, he can no longer see over the edge.

Complex biological systems (nature, humans…) are characterized by the fact that they consist of lots of interconnected dependencies in the different parts of its whole. A system constantly exposed to both sensitivity and noise, and a system of constant change.

It’s also quite easy to get stuck in a loop of trying to uncover more and more of these underlying factors, rather than to carry on with whatever knowledge we already have at the moment.

Better than using a detailed map to navigate an ever-changing landscape, like a glacier, would be to routinely triangulate your position and endure living with the degree of inaccuracy and uncertainty that comes with not knowing exactly where you are. Even though the belief in the perfect map gives a sense of security, it is a false feeling that risks leaving us blind to what is actually happening.

Simply observing what we have in front of us is often hard to do.

In order to be able to compare efforts and athletes we usually take the leap from qualitative observation to quantitative data collection, and by doing so removing them further away from the context where they were observed. How do you quantify “fast” or “slow” or “hard” or “easy” without delimiting them by turning them into numbers? Numbers fit so much better in spreadsheets for statistical analysis.

Not only are we by doing so removing the effort out of its context, we are also risking to try to affect these new numbers rather than the situation they emerged in.

You don’t want your planes to get shot down by enemy fighters, so you armor them. More armor makes a plane heavier and heavier planes are less maneuverable. They also use more fuel. Armoring planes too much is a problem; armoring planes not enough is also a problem.

During the second world war the American army was studying the planes returning from battle and kept reinforcing the areas of the planes that had the highest number of bullet holes. However, more and more planes were lost despite their added protection.

This continued until the statistician Abraham Wald noted that the military only considered the aircraft that had survived their missions. Since they didn’t, or couldn’t, look at the specific battle situations where shots were fired, they failed to see the planes now rendered unavailable from assessment. Wald instead asked: where are there no bullet holes at all?

As aiming at moving planes is not that easy, especially in those times, he figured that the damage would have been spread quite equally all over the plane. Since this did not adhere to the observations, he was fairly sure he knew where the missing bullets were: on the missing planes.

The reason planes were coming back with fewer hits to the engine is that planes that got hit in the engine weren’t coming back. The armor, he said, shouldn’t go where the bullet holes are, but quite the opposite, where the bullet holes aren’t.

At the end they managed to logically figure out a way of protecting their planes. But all of this would have been quite clear if they had not only looked at the data, but also kept an eye on the actual action.

“Mathematics is the source of a wicked intellect that, while making man the lord of the earth, also makes him the slave of the machine.”

Robert Musil

The technology to measure oxygen consumption first arose in the early 1920’s. Using that ability Hill and Lupton found that there appeared to be a maximum limit to oxygen consumption, when despite increases in speed, their VO2 consumption did not also increase any more.

After this most studies in exercise science have been evaluated on the resulting change in VO2max rather than actual performance (such as ability to stay with a breakout, handling of different sections of a race, movement form or even something simple as average speed over a distance). VO2max is less variable and more tolerant to changing conditions. It also happens to fit well into columns of spreadsheets.

As outcomes are increasingly measured by a specific construct, they start to shape the outcomes themselves. Researching training interventions using this or that variable as the standard of success, will slowly shift the training interventions to strengthen just that variable rather than something else. They become self-reinforcing as you will always find more of what you are looking for, and less of what you don’t. Even though that variable might have a very poor transfer on actual sports performance (or health for that matter).

Whenever a new parameter is discovered or introduced, a large degree of emphasis is put on that parameter in the research.

Several new ways of taking measurements of biological processes have had similar impact. With the ability to portably test lactate, research was centered on ways to improve lactate threshold. With the ability to measure force, other variables came into the limelight, such as Functional threshold power or Critical power.

If we all agreed on what math problem we were trying to solve, then we can sit down together and say, hey let’s calculate! But sport and life is messy. We might not agree on what we’re trying to optimize and we also have a lot of uncertainty about what the consequences of our actions will be. 

Even with access to great data, not everything’s an optimization problem. Ultimately it is crucial that we understand the limits of the technology we leveraged to help us to navigate our complex world and the values that often invisibly determine how we use it.

“For years we have seen study after study attempting to compartmentalize intensity domains based on an assumption that there is some physiological decompensation point. However we reach no clear consensus on this. First it was MLSS. Then VO2 kinetics. Then FTP and CP, but none are conclusive. Perhaps we are looking for something that isn’t there.”

Dr. Jeroen Swart

We are starting to see why Max Planck, awarded the Nobel Prize, once said that he saw economics as a harder discipline than his own field of theoretical physics: due to the inherent need for subjective judgments. Dealing with humans, is dealing with unpredictability. This could certainly be said about exercise science too.

We often think of these measurable physiological variables as clear cut, defined markers. We use them to train at different thresholds and to classify our training as such. We assume that the transition is clear and that these parameters represent some sort of boundary line, and that improving them leads to better performance.

All of the above mentioned concepts can be helpful, and used to organize and guide training but we need to understand that they do not by themselves represent increased performance. That they do not represent a clearly defined transition. Physiology is complex and messy.

There is no sport of highest VO2max, Critical Power or peak wattage. We should not be so in love with a measurement so that we forget to look at how an athlete handles specific situations of their sports.

”I’ve seen things you people wouldn’t believe. Attack ships on fire off the shoulder of Orion. I watched C-beams glitter in the dark near the Tannhäuser Gate. All those moments will be lost in time, like tears in rain.”

Roy Batty, “Blade Runner”

When you put a pot of liquid water on the stove it is in a steady state. All of the collective molecules exist in liquid form. As soon as you begin applying heat and pressure the state begins to change. At any given point in time we are unable to predict which molecules will make the transition. They exist at the edge of chaos. Provide enough heat and pressure and over time and they will eventually turn into a gas.

Complex systems, such as humans, have interesting properties. Strong interactions between their parts, feedback, emergence, self-organisation, adaptation, growth, change. None of these are a simple linear process. Large interventions in a variable does not necessarily have a large effect on the expected variable of interest. Similarly, a small intervention can have large and unexpected outcomes. Just like a “perfect storm” – a combination of circumstances drastically aggravates the event.

At first this unpredictability is hard to reconcile with. But maybe it’s not necessary to know exactly how a specific performance in such a system emerges?

Continuing with the “perfect storm” analogy, it might be important to provide individuals with periodic interventions that are delivered under varying “atmospheric” (i.e., psychological or life states) conditions. This means providing repeated opportunities to practice this self-organization under realistic conditions.

Consider “Chinese water torture” – a drop of water continuously hitting the same spot on your head for a long time would not bother you at all, but eventually it would change your behavior completely (driving you mad, so don’t use the analogy literally with your athletes).

“We must do away with all explanation, and description alone must take its place [..] The problems are solved, not by giving new information, but by arranging what we have always known“

Ludwig Wittgenstein

Start with what you see. When do athletes struggle in racing or during competition? Describe those situations without explaining why they happen. Separate these situations in the training program and practice them with some variation.

The level of difficulty and overload should not be too high. This might push the system into interpreting the situation as something altogether different from the game-day skill. But not so little that the athlete can complete every repetition with a 100% accuracy (how could a system operating perfectly be pushed into change?).

To practice “what you see the need for” has a few advantages over to base training prescription on hidden underlying qualities

  • By doing so you will measure its success by exactly the outcome which you want to improve. This prevents you from getting lured in a separate direction by confusing some other variable with performance on the field. Every improvement will have a large transfer from training to performance, making small increases in capacity highly valuable.

  • You will move into a territory of training which your athletes are familiar with. This helps communication between the two of you. Communication should not be under-valued. When coaches speak the language of science only, how can athletes be expected to understand the drills they are given? You are more likely to get success telling your athlete to “sprint out of that corner as if you would like to get a gap on your opponent” rather than something along the lines of what percentage of VO2 or speed to hit.

    It will also help you to get relevant discussions on how to tweak the drills. Although athletes might be lacking in scientific knowledge, they tend to know a fair bit about their sports, and these discussions easily extend into how to use the skills you have been working on when discussing tactics.

The downside is of course that you will have to be open with the fact that all you can offer is educated and well-founded guesses. That there is no magic pill. That all the certainty there is to find is that continually doing the things you wish to improve at over time, with some variance and with some overload is what might increase your capacity (mostly by ways of a sudden phase-transition).

If I could have gotten one dollar every time someone asked me for an assistance exercise for a problem – let’s take the execution of the weightlifting movement of the snatch for instance – and seen the disappointment in their eyes when my first choice of exercise was to do exercises not completely different from with is done in that movement. I’d rather pick an exercise to emphasize or correct the point of the lift where I felt the problematic outcome initially did arise.

This places a lot of demand on the coaches communication skills in order to get the buy-in from the athlete. A buy-in which you could have gotten by dangling a mathematical carrot on a stick in front of the athlete. It will also in my experience bring about more compliance and less injuries when you get the athletes involved in the actual process.

I started working with this young and gifted athlete from Portugal a few years back. He had made the transition from Volleyball into CrossFit where he now had some success, qualifying and performing well at the 2018 Regionals. He also struggled with some of the integral movements of the sport, such as the weightlifting movements – most noticeably the snatch.

He was catching most of his Snatches in front of him, forcing him out of balance. Unfortunately we live at quite some distance and cannot do better than to have close contact over the internet. After a lot of questions and answers and sending videos back and forth we agreed that he had trouble already at the starting position, struggling to find initial balance against the floor. This in turn leads to his position being too upright when the bar passes the knee. His joints then are not properly set up to allow him to hit what in weightlifting is often referred to as the Power position. 

Without going into too much detail, the Power position allows for rapid extension of the knee and hip along with plantar flexion, in a sequence called the proximal-to-distal sequence, where extension on the joints one by one allows at least one joint to have a favorable translation relationship throughout the full extension. The failure to hit this position can force the barbells necessary vertical movement slightly forward, getting the lifter into all kinds of problems catching it.

Over the coming period we did quite a lot of

  • Snatches from power position, with clear instructions on what would constitute a “good rep”, having him to learn and discover on how to generate force from that position. If he could not move from this position without a slight “swinging motion” or if he had to jump forward in the catch he would know that he did not find his Power position properly.
  • Snatch deadlifts, playing with and learning how balance felt. (Balance is tough, as it is really the absence of feeling. Athletes sometimes tend to seek out more distinctive tension, something they feel, as you would find when you are more on your heels or on your toes)
  • From knee to power position and from floor to power position.
  • Full snatches involving the feeling for positions he learned by the above exercises.

Slower, faster… Mixing it up with some fatigue and eventually hitting the positions and moving between them became more second nature for him. 

Not once did we do any movement that was fundamentally different from the movement that he struggled with, hoping to increase some “underlying quality” possibly holding him back. Surely, we still trained those underlying qualities, if they existed, by overloading and stressing the movement that involved them. With the added benefit of a more direct transfer and possibly better understanding and feedback of his process.

We also did not measure the performance of the assistance exercises, more than if they successfully challenged the positions where we thought we saw a lack of efficiency and balance. They were always viewed in the light of the performance of the full snatch.

João has gotten more proficient with this movement: here he is, at the end of a 30 minute workout, hitting a 110kg Snatch, rowing 500m in 1 minute and 40 seconds (something not done without breathing hard), then hitting another 110kg snatch just after coming off the rower something that he could not do in isolation before.

Is this the best way to conduct training? Certainly not always! There will always be cases that are different from all other cases. Every method has its place. 

It is a simple process helping you not to get completely lost in the “data” jungle, or if you are, to find your way back onto the field, where the actual athletes live.

Stay tuned for more examples of practical implementations of these principles in part 2.