Entry 5: Rest and Recovery Part 1, Managing Fatigue

Whether it be from PE class growing up or listening to motivational speakers, many of my readers will likely be familiar with the cliché phrase “no pain, no gain”.  While there is certainly a great deal of wisdom in this adage, exercise science would suggest that “pain” (or in endurance parlance – fatigue) is a necessary but insufficient condition to performance “gains” in endurance sports.  The general consensus amongst coaches and sports scientists today is that the human body has an amazing ability to adapt when pushed beyond its physical limits, granted that one does not overly stretch those limits and the body has sufficient time to recover.  This adaptation process is known as supercompensation, whereby when the body experiences microtrauma from an outside stimulus (e.g. exercise), it makes itself more resilient to that stimulus during the process of repairing itself.  As an interesting anecdote, the primary reason why certain athletes have (shamefully) utilized banned substances such as anabolic steroids and testosterone to make illicit gains was not because these compounds made them stronger, but rather allowed their bodies to recover faster between bouts of exercise.  Unethical practices aside, my n=1 experience from my own training process suggests that managing fatigue may be as important as the actual workouts themselves, having made the all-too common mistake of pushing my body beyond the point that was productive. TLDR: no pain + recovery, no gain.   

Training Plan Implications

With all this in mind, the training plan I have outlined in previous posts takes into careful consideration the importance of recovery via three specific elements regarded as best practice by many coaches: 

• Rest Days: Every training week includes one day completely off from any form of exercise.  This typically takes place on Mondays after the weekend’s longer / tougher sessions and is designed to allow sufficient time to regroup for another week in the trenches. 
• Recovery Weeks: At a macro level, my season is structured into four-week mesocycles comprising of three weeks of increasing training load, followed by one week of recovery, which usually entails a ~50% reduction in volume.  Like individual rest days, recovery weeks are key to allowing bodily adaptations to occur after a difficult mesocycle. 
• Race Taper: In the final weeks / month leading up to a race, it is generally considered best practice to execute what is known as a “taper” protocol by drastically reducing one’s training volume while maintaining intensity.  While this does reduce overall fitness, it also has the effect of reducing residual fatigue at a much faster rate, helping to ensure fresh legs for race day. 

Measuring Fatigue – Coggan PMC Model:

For those of you who would like to dive down the rabbit hole, the general recovery practices outlined above are informed by a diligent monitoring process of certain metrics.  Utilizing the training metrics outlined in my previous post in conjunction with fitness tracking technology and software (to be addressed in a subsequent post), it is possible to quantify and therefore manage one’s accumulated fatigue.  The most well-known and commonly used methodology is the performance management chart or “PMC” model developed by Dr. Andrew Coggan, which hinges upon an alphabet soup of four metrics: 

• TSS: At its core, the PMC calculates a training stress score (“TSS”) for every workout based on the intensity of the session relative to one’s lactate threshold and the duration of the session, specifically:

As seen above, the TSS of a session rises as one increases the intensity and/or duration of a workout.  To provide some examples, spending 1 hour at an intensity equal to threshold yields a TSS of 100%*100*1 hour = 100.  Likewise, spending 2 hours at an intensity equivalent to 75% of threshold yields a TSS of 75%*100*2 hours = 150. 

• CTL (Fitness): It goes without saying that as an athlete becomes stronger, he or she is able to go harder and/or longer during training sessions, which is reflected in the data via higher TSS numbers on any given day.  This is most often summarized in a metric known as chronic training load (“CTL”), which is one’s weighted average daily TSS over the past 42 days with the most recent days being more heavily weighted.  For the math geeks out there, the formula for CTL looks like this:

Here, CTL_y represents yesterday’s CTL and TSS represents current training stress score.

• ATL (Fatigue): In a similar manner, TSS can also be used to approximate the amount of fatigue one has generated in the short term, also known as acute training load (“ATL”).  This is calculated in the same way as CTL except weighted over the past 7 days:

Given the difference in weighted average days (42 vs 7), trends in CTL generally tend to lag behind those of ATL. 

• TSB (Form): If one sticks with the crude analogy of treating CTL as “fitness” and ATL as “fatigue”, the difference between the two, known as training stress balance (“TSB”) can be used to approximate one’s “form” or “freshness” as seen below:

Taken together, these metrics are incredibly useful for tracking the progress of one’s training and knowing when it is appropriate to back off the overall load.  For example, a general rule of thumb is that qualifying for Kona (as of the 2019-2020 season) usually requires a minimum peak weekly TSS of 1,000, which equates to a CTL of approximately 140-150.  As one strives toward that goal by steadily progressing in both intensity and duration, given the aforementioned lag between ATL and CTL, one should see ATL exceed CTL, resulting in a negative TSB value, i.e. an indication of a rising trend in fitness.  Conversely, a positive TSB value is usually an indication of a falling trend in fitness.  That being said, an overly negative TSB is oftentimes an indication of training beyond the point of productivity.  While the exact “breaking point” TSB value varies from person to person, most coaches generally guide towards maintaining a TSB value above -30. 

To put this all into context, below is a screenshot of my personal PMC for my preparation for Ironman Wisconsin last year as well as my training so far for Kona.  Here, the blue line represents CTL (fitness), the pink line represents ATL (fatigue) and the yellow line represents TSB (form). 

Using the training plan described in prior posts, I grew CTL from a value of 68 at the beginning of my season (August 2018) to a peak value of 180 one month prior to Ironman Wisconsin (August 2019).  This progression was by no means linear, as one can easily spot a pattern of ATL “spikes”, each representing a week of training terminated by a rest day.  These spikes also tend to occur in sets of three, representing the three-week loading phase of each mesocycle, which is immediately followed by the aforementioned recovery week.  Both the rest days and recovery weeks ensure that TSB remains higher than -40 at all times and has a chance to return to a neutral value of zero on a periodic basis, thus ensuring that the body has adequate time to adapt to the increased intensity and volume.  The threshold TSB value of -40 was determined via a lengthy process of trial and error over three seasons, below which I have historically experienced drops in performance as well as a greater propensity for injury (more on this on a subsequent post). 

After achieving this peak CTL value of 180, I executed a month-long taper process which drove a slight reduction in CTL but also a very large swing in TSB to a value of +25, ensuring that I was rested and ready for what turned out to be a successful, Kona-qualifying race.  This chart also clearly shows the effects of detraining: having taken some time off in the weeks following Ironman Wisconsin, one can see a rapid rise in TSB as well as reduction in both ATL and CTL. 

Limitations / Alternatives

It should be noted however that the Coggan PMC model is not without its limits.  For example, while the PMC does a great job of tracking the stress generated from workouts, it does not capture the stress derived from activities outside training such as on the job or one’s domestic life.  My personal experience would suggest that willpower applied to any activity, whether it be for work, training, or social events, is drawn from the same “battery”, and these outside activities do have a material effect on how quickly one can ramp one’s training load.

In addition, many coaches would be quick to point out that not all TSS is created equal.  For example, one’s physiological adaptation from an easy 2 hour ride at 50% threshold would be very different from an hour ride involving hard intervals at 120% of threshold despite the fact that both workouts have a TSS of 100.  As such, TSS is only useful for tracking fatigue if one maintains a consistent mix of workouts over time. 

It should also be noted that there exist alternative ways to measure one’s fatigue levels.  For example, one’s resting heart rate tends to remain elevated when the body does not have sufficient time to recover.  More recently, several companies have advertised the use of heart rate variability, i.e. the variability in the timing between individual heart beats (a lower number usually indicates a high stress load and vice versa). 

In my next post, we will continue this exploration of rest and recovery by taking a closer look at the actual activities they entail.  In the meantime, for those of you who would like to follow my training progress, most of my sets can be found on my Strava account at: https://www.strava.com/athletes/15134014.

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