Thursday, February 4, 2016

Rocky VI: Fitness v. Fatigue

“That which does not kill us makes us stronger”
Friedrich Nietzsche

So, being in the middle of an Ironman taper for the past couple of weeks seriously got me thinking about the role of fatigue in the training process. Dropping a significant amount of load over the past couple of weeks has me feeling like Superman, running my 200’s almost 5s faster than what I do in a normal training week, swimming times that I haven’t seen in a long while and feeling an unfamiliar pep throughout the day.

These sensations got me seriously asking the question, what if I was to throw down a training block right now? What sort of quantity/quality could I accomplish? Of course, it’s purely speculative, but I do know that I have energy and motivation for training that has been missing over the last couple of months while I have been pitching my tent in the valley of fatigue.

I guess all of this extra energy devoted to firing a few more neurons brought me full circle, back to that undying question: When it comes to fatigue, how much is too much?

Any athlete who has taken the time to browse through the popular literature on triathlon training will be familiar with the following figure:

The figure is a graphic display of Hans Selye’s General Adaptation Syndrome, which, when it comes down to it, is the very crux of the whole training process. You apply a stress that is beyond the athletes normal day to day level, the athlete gets fatigued, the body recognizes the fatigue and, while the athlete is recovering, supercompensates beyond the initial fitness level so that if the stimulus is encountered again it will be ready for it.

Now, most athletes are at least aware of this process on some level (though a great many fail to apply the recovery portion in their training). However, without putting some numbers on the x and y axes, this theoretical construct stays firmly in the realm of training theory. If we really want to put this concept into practice, we need the answer to some very fundamental questions:

When it comes to endurance training (numerically);-

• How much fatigue do we want to accrue before resting and recovering?

• How long can we maintain a given training load, with improving fitness, before we need to ‘up the ante’

• How long should we rest to ensure that our body supercompensates to the highest possible fitness level before an important event?

• How long can we maintain this fitness level before we have to ‘get back to work’?

A number of researchers, beginning with Banister (1975) have ‘done the math’ on the preceding questions and have come up with the following mathematical model to answer them:

For the mathematically inclined (for those not inclined, feel free to skip to the next paragraph – the important stuff):

pt = Performance at any given time
p0 = Initial performance level
T1 = Rate of decay of fitness
T2 = Rate of decay of fatigue
k1 = Amplitude of fitness decay
k2 = Amplitude of fatigue decay
ws = Daily ‘dose’ of training.

While the math deals with some pretty abstract stuff, when we express the model graphically, throwing in some ‘real world’ numbers, the implications are pretty clear. The following model, using the above formula with real world data acquired from distance runners was created and tested by Morton et al. (1990)

On this chart, the x axis represents the number of training days and the y axis represents fitness gained and fatigue accrued.

This chart represents the physiological response to a uniform training load of 100 TRIMPS/day. In our terms, this would equate to about 2.5hrs of easy-steady training per day. This load is a constant from day 0-120, i.e. 2.5hrs each day, every day.
The implications are clear:
As anyone who has swam competitively and experienced the early season return to ‘2-a-days’ can attest, just like Rocky Balboa in Rocky IV, you are going to take a beating in the opening rounds, as fatigue (Drago) dominates fitness (Rocky). For the first week or so, Drago has a slight upper hand but you are still primed and ready for a good fight. Then, as the fight goes on, Drago begins to dominate the early rounds big time. There may be times during the opening month that the accrued training will make it very tough to keep motivation up. You will be tired and at points will want to quit/change your plan, but as Rocky says:
“Going that one more round when you don’t think you can is what makes all the difference in your life”.
So, you stay the course and like all Hollywood endings, somewhere around Day 50, you start to get the upper hand and providing Drago isn’t too steroid supercharged (i.e. your training load is not so ambitious that you fail to adapt and get sick), you start to win and then at Day 120, you jump on the Russian PA system and in one fell swoop you end the cold war by stating the immortal words:
“If I can change, and you can change, everybody can change!”
OK, I’ve taken the metaphor too far :-)
Back to the important stuff, a couple of things to remember:
1. At least in this case, fitness didn’t trump fatigue until ~50 days of constant loading. How many of us bail or change the program (either up the ante prematurely or insert premature recovery) before giving the program a chance to work?

2. Fitness continued to improve to a standard training load for ~4 months before approaching the asymptote, i.e. max fitness gains for a given workload/level of fatigue. At this point, it would be necessary to increase the stimulus to ensure further fitness gains.

3. One may suggest that the greatest fitness “bang for your buck” would be to structure training around 60 days cycles, i.e. loading cycles that take the athlete to the tangent to the curve, i.e. ~60 days in, when fitness begins to exhibit a tendency toward diminishing returns.

These three conclusions provide a good deal of validation towards the efficacy of the ‘basic week’ structure and serve to place periodization in it’s appropriate perspective.

Another question that the model can help to answer regards the taper, i.e. what is the optimal time period to reduce training load prior to competition? And what performance improvement can be expected?

In other words, what happens to performance if we cease (or reduce) the training stimulus at a given point? The chart below shows what happens if we taper training 60 days in.

The model shows that by tapering load 60 days in, the athlete can expect performances equal to what would previously have taken 120 days of continuous training to achieve. In addition, it shows that the optimal performance will occur, in this case, 23 days after the beginning of the taper (on day 83) when the athlete experiences the greatest gap between fitness and fatigue.

Of course, there is a cost to ditching training load. This cost is paid with diminished fitness (see below).

In the case of this model, the athlete can expect to lose ~33% fitness over the course of the taper period. However, they also lose 85% of the accrued fatigue (due to the different rates of decay between fitness and fatigue). So, in the grand scheme of things, when performance is the name of the game, it’s a good deal. However, it is important to note that this drop in fitness essentially takes the athlete back to the fitness level that they were at 50 days ago. In other words, over the course of this training cycle, the athlete only gets to ‘keep’ 10 days of the fitness that they accumulated to carry over into the next cycle because they took 60 steps forward, but 50 steps back. For this reason, one needs to seriously consider the # of A races (races that they taper for) that they place in their season (or during the course of their athletic development). 3 x A-Races essentially means 150 days of lost training just getting back to their peak seasonal fitness.

So, you may say, all of this is very interesting, but how universal are the training responses to this training model?

You may be surprised by just how robust the training model is. It has been applied to and shown to be valid for a number of sports ranging from strength sports (Hammer Throwing) to endurance sports (swimming, cycling and running).

It has also been used with athletes of a wide ability range from elite swimmers (Mujika et al, 1995) to novice cyclists (Busso et al., 1991).
In all of these studies, the fitness acquisition and decay rates have been surprisingly similar. The fatigue constants on the other hand have differed, primarily in accordance with the athletes fitness. Somewhat unsurprisingly, higher level athletes who undertake greater loads require more time to shed the associated fatigue.
These fatigue constants have ranged from mean values of 2 days for untrained men undergoing 4x60min cycling sessions/wk (Busso, 1991) to 13 days for moderately fit cyclists undergoing 5 days/wk of interval training (Busso, 1997), to 19 days for elite swimmers training 45-50km/wk (Mujika et al. 1995)
The constants used in the above charts (Tf=15 days) are therefore within the range of moderately trained individuals and should provide a good starting point in predicting performance response within that group. On the other hand, if you’re a couch potato or your busting out 50km+ per week in the pool, you may need to ‘tweak’ the charts accordingly, which brings us to the next point….
While a model that predicts a large sample of athlete’s performances is good, a model that predicts your athletic performances is even better. To this end, wko+ offers athletes a tool that enables them to come up with their own performance model that best predicts peak performance. It uses similar concepts to those above, a Chronic Training Load number (fitness constant), an Acute Training Load number (fatigue constant) and a Training Stress Balance (performance prediction number) to enable athletes to model their own training response.

Of course, like most tools, it must be properly calibrated to be accurate. In this sense, it is important that the athlete sets an appropriate Acute Training Load (fatigue constant) in accordance with performance markers from their own training. If this is done properly, wko+ offers athletes a fantastic individualized snapshot into their fitness, fatigue and form at any point during the training season and enables them to make intelligent decisions as to:

What is an appropriate long term training load for me?
What races are worth shedding fitness for?
When should I change up my training plan?
How long should I taper ?
Etc.
It is only with this kind of strategic information that an athlete can really hope to win the long term battle between fitness and fatigue.
Train smart.
AC

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