Cycling Phase shifting Training theory

Phase shifting pt 3 – Excercise classification

One other thing from Bondarchuk I have been inspired by is his exercise classification because it resonates well with the idea of the systems pro­duced through these processes of self-organization that cannot be understood solely through an analysis of their components. Really, when it comes to training as much as we have seen that it was in war for General Clausewitz, it could be the stimulation of the smallest thing within the system that brings about precisely the change needed for that phase-shift. So while obviously never forgetting to train ”the whole” a method for also doing ”the less” seemed useful.

The now classic “invisible gorilla” test had volunteers watching a video and counting the passes between basketball players. Half of the volunteers then missed a woman in a gorilla suit slowly crossing the entire scene. When one develops “inattentional blindness,” as this effect is called, it becomes easy to miss details when one is not looking out for them. And this is not the only predicational bias we are exposed of: path-dependence is the phenomenon of how the possible decisions for the future is limited by the decisions we have made in the past or events that we have experienced, even though past circumstances may no longer be relevant.

“The light of reason is refracted in a manner quite different from that which is normal in academic speculation” is a beautiful quote from Clausewitz meaning that the innate ideas of seemingly self-evident truths, or pure logic, does not help in a complex environment where we need an appropriate responsiveness to the ever-fluctuating conditions that emerge. While we see a limitation in long-term predictions of a system we could instead replace this with a qualitative understanding of the same. Trying to identify its overall behavior, and using what you see but also staying observant to patterns and regularities in its dynamics and open to that these patterns might change. In short: have a plan to evaluate your plan.

In order to never miss to stimulate any part, regardless of attentional deficit, path-dependance or logical fallacies I find it beneficial to do all of Bondarchuks categories of exercises each training session. Those categories include the competitive exercise (”the whole”), Specific developmental exercises (parts of the whole), Specific preparatory exercises (not part of the competitive exercise, but using the same muscles) and lastly General preparatory exercises which would be all-purpose exercises for general coordination and recovery.

This holds me accountable for always including ”the specific” in my sessions, while also overloading certain parts that I guess to be more important for me, but still to touch on things that I – truth be told – would not think matter for my performance (but still might). Every three weeks I look at the collected data and the collection of thoughts and ideas I’ve pinned to paper during the last block of training, usually ending up making slight changes of my plan for the next one.

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

One could argue that the research seems conclusive that variation is a necessary component of effective training programs, and that this type of program while having a large variation within sessions has little between them. I would agree with the general statement but one should remember that the training input is always overlaid on the current bio-chemical state of the person doing the training, and as that the emotional state of that person is ever-changing there is always some, albeit little, variation taking place.

However: lack of variation have been strongly linked with training monotony, which in turn seems to increase the risk of overtraining syndromes, poor performance and banal infections. Obviously something to consider. Therefor I also very slightly shift the categorical emphasis throughout each training sessions within a block of training, so that while I always do a little of all categories every session, I also always do a little more of one. And thus provide a little more variation than the regular ”noise” from everyday life, but not too much to be too distracting when it comes to evaluation of it’s efficacy.

The take away is that you might not be able to predict why and when a new attractor might emerge, so do a little ”hit” on every part of the system you are targeting, relatively often and consistently over time. Dripping water pierces a stone; a saw made of rope cuts through wood.

Cycling Phase shifting Training theory

Phase shifting pt 2 – The fog of war

Let’s use my own cycling sprint training as an example of how phase-shifts can look like in performance: In January 2019 I had almost given up trying to record an average power over 800W for 10 seconds on rollers since failing to do so for months. Then all of a sudden I did it, and I to this day never again failed to do so. The next phase shift happened in October the same year bumping the stable state that performance varied around to 850W and a few months later, after seeing my performances fluctuate around the same stable state it once again shifted and since then I have never again seen less than 900 average watts when sprinting on the rollers.

(side-note: it’s crazy what low bodyweight and small frontal area/low drag does for speed. My training buddy does almost 400W higher average than me for this time-frame, and I would still more often than not beat him on 500m sprints… But some distance after that his supreme storage of kinetic energy shines through and he comfortably beats me)

The same things can been seen during this period when it comes to actual performance (speed) on the track where I went from 12.40 to 11.72 for a Flying 200m and >40 seconds to 38.02 for the 500m (on a slow, short and steep track as the Falun velodrome).

And this without structured wave-loading of either volume or intensity of training, which I was inspired to try from reading Anatoliy Bondarchuk. When I first read about the training regimes described by him, his method was very eye-opening (and surprising) to me. They certainly was not like the traditional ”Bompa”-style planning strategies that was the usual thing to see in academic literature (and that I no longer feel is a particularly useful tool). To simplify this it means that once a ’program’ or ’set of programs’ is prescribed, it is simply repeated over and over again without change, or much change, until an adaptation response is observed – hopefully leading to a phase shift in performance.

One must remember that the day-to-day measure of success here is not simply a question of load tolerance or survival (negative feedback), but rather one of enhancement and growth (positive feedback) over the medium to long-term, and to allow this to happen we should not necessarily take negative performance (one step back) to mean we are not paving the way for successful adaptation just around the corner (two steps forward).

Non-linearity and complexity in modern thought also expressed itself in the writings of General Carl von Clausewitz (1780–1831) who recognized the essentially dynamic and unpredictable nature of war. His major work, ”On war”, recognized the inherent limits of reason when grappling with dynamic and complex phenomenon.

”Success is not due simply to general causes. Particular factors can often be decisive – details only known to those who were on the spot […] while issues can be decided by chances and incidents so minute as to figure in histories simply as anecdotes.”

Non-linear phenomena, characterized by positive feedback loops and sensitivity to initial conditions, are precisely those that allow for such an amplification of “minute incidents”. Another way of stating this is to say that “local causes can have global effects”.

Cycling Phase shifting Training theory

Phase shifting pt 1 – Order and chaos

Mechanistic models constituted the first major scientific discourse and paved the way for the future development of science. With the core ideas being the Newtonian laws of motion, the notions of gravity and mass and the perception of time as an arrow the metaphor of the world as a machine took hold.

We lived in a stable clockwork universe just waiting to be described and understood in order to replace chaos and uncertainty with order and predictability. This drive for predictability and control manifested itself in a science which focused its attention on linear phenomena since those mathematical functions could be expressed and used in ways easy to understand and solve.

These linear models focused their attention to negative feedback, or homeostasis, where the product of a reaction leads to a decrease in that reaction. And while this is an essential condition for stability of a system, and thus well suited for dealing with engineering problems and machine design, it does a poor job of describing growth, self-organization and the non-linear relationships where the initial change to a parameter of a system results in an amplification of change elsewhere in the system.

Most sciences now holds the reverse to be true, that linear processes are the exception and not the rule and that nature is fundamentally non-linear.

”Whenever you look at very complicated systems in physics or in biology, you generally find that the basic components and the basic laws are quite simple; the complexity arises because you have a great many of these simple components interacting simultaneously. The complexity is actually in the organisation – the myriad possible ways that the components can interact.” (Stephen Wolfram)

This view is in direct opposition to reductionist approaches where the properties of the system are the mere aggregation of their constituent parts. Complex systems are a dynamic network of many agents acting and reacting to what other agents are doing. The competition and cooperation between those agents produces an overall behavior of the system, which can be said to be emergent. The emergent properties of complex systems are therefore properties that cannot be deduced from the properties of the individual parts. The system is larger than its parts.

And as complex adaptive systems include all living organisms including the social manifestations between them, it also include the adaptions to training. To me this explain why I have almost never seem adaptations to slowly go in one direction only, but to vary around a stable state which then suddenly might be shifted and become the new stable state that physical performance varies around.

The exploration of non-linear functions revealed the phenomena of bifurcations in dynamical systems. Bifurcations are when a small change made to a parameter of a system causes a sudden qualitative change in the systems long-run behavior.

”Systems reach points of bifurcation when their behavior and future pathways becomes unpredictable and new higher order structures may emerge” (John Urry)

For certain inputs the system will respond to all perturbations by settling back to an established steady state. And all of a sudden, when the system reaches a point of bifurcation the system will develop two alternative states that it will settle into depending on the perturbations applied to it. This can also be described as a phase-shift within the system, producing a new behavior, but one cannot tell what stimuli and to what part of the system that will cause such a shift.

In my experience, when it comes to adaptation to training, these shifts appear suddenly, and sometimes from what seems very random and unexpected. But they do not appear to be linear at all, and if anything to be the result of consistent small ”hits” to the various parts of system (in this context this would mean different stimuli to the trainee inside and outside of the training hall). And certainly seldom manifests themselves as slowly advancing from disorder to order, as in the mechanistic worldview that biology and psychology in large have moved past, but exercise science in general still succumb to.