The “Watts up with Power?” ride is likely the slowest group ride you’ll find on Zwift, because it focuses on learning the basics of power based training while riding together on Zwift. Each ride is streamed to Zwift LIVE by ODZ on Facebook, and focuses on teaching specific principles of power-based training. For viewers that are unable to attend live, the teaching is made available for all to review afterwards.
Here is the summary for December 13th from presenter Taylor Thomas.
Perhaps the best use of power data is performance management. Knowing exactly when to train hard, recover, and how to come “into form” are invaluable for results-driven athletes. There are a variety of tools and metrics that should be utilized when managing performance with power data. The Performance Manager Concept, TSB, ATL, and CTL are the primary drivers for athletes looking to take full advantage of the data they’re producing. These metrics are central in understanding the core concepts of training and training dosage.
The Impulse-Response Model
Banister’s model is an attempt to investigate the relationship between both the volume and intensity of training, along with the resulting performance gains. The goal is to quantify this relationship with a mathematical approach vs. what is often a trial and error approach for coaches and athletes.
The crux of the model is that there are two opposing effects in training. One is that there are positive adaptations to training that result in fitness gains. Those gains are “chronic”. Two is that there is a negative response to exercise that results in fatigue. This fatigue is “acute” and is shorter lived than the chronic gains.
There are however some drawbacks to this model. Firstly, it does not accurately reflect physiological events relevant to fatigue and adaptation such as glycogen resynthesis or mitochondrial biogenesis. It also assumes that fitness is linear and that training will always lead to greater gains. This simply is not the case.
The model also requires a tremendous amount of data points that need to be tested at a frequency that isn’t realistic for training athletes. Even if athletes were able to test enough to obtain the data points they needed, the model has shown to not be a great predictor of future performance, which of course is one of the goals of this level of analysis.
The Performance Management Concept
This idea was designed to take the relatively complex concept of the Impulse-Response Model and create a more practical approach. Its goal was to be applied outside of the laboratory and compensate for some of the shortcomings of the previous approach. It uses several metrics to drive the concept.
Chronic Training Load (CTL) measures how much an athlete has been training historically, or chronically. It is calculated by an exponentially weighted moving average of daily TSS (Training Stress Score). It uses a 42 day constant to reflect the training that has been performed during the last 3 months.
Acute Training Load (ATL) provides a measurement of how much an athlete has been training recently, or acutely. ATL uses a weighted moving average of daily TSS with a 7 day constant. It can be viewed as the negative effects that training has had on an athlete.
Training Stress Balance (TSB) is the difference between CTL and ATL. TSB reflects an athlete’s “form” and must be combined properly with CTL to produce the desired results on race day.
Peaking with Power
Being “on form” requires the right blend of fitness and freshness. Too much time off before a race and too much fitness is lost. Conversely, too much heavy training leading up to a priority event and there’s too much fatigue. Use the PMC and its core metrics help strike the appropriate balance.
ATL drives CTL, meaning that the fatigue accumulated during training will eventually force time off, causing a decrease in CTL. This rest is critical, but must be balanced properly to elicit the desired response to training. Managing CTL and ATL is one of the hardest aspects of performance management.
TSB represents how well training load and rest have been managed. A positive TSB means that a rider is fit and fresh. However, negative TSB indicates fatigue. Knowing what number is optimal for key events is key to mastering this approach.
There are “optimal” levels for both CTL and ATL that can be used as guidelines for most athletes. Typically a CTL of between 100-150 TSS/day is when an athlete feels they are making the most progress. A CTL increase of 3-7 TSS/day is also optimal. Any more or less and training either feels stagnant or overtraining symptoms occur.
A range of between -10 to +25 TSB is acceptable when looking to produce peak powers for a given discipline. The ideal number is different for every athlete, but the rule of thumb is that for shorter more anaerobic efforts a more positive TSB is required than for longer more aerobic events.
Applying the Performance Manager Concept
Accuracy, as with all power based metrics, is very important. If TSS is the primary driver of the PMC then a correct and up to date FTP is paramount. If functional threshold power isn’t correct then TSS values will be too high or too low thus causing improper CTL, ATL and TSB readings.
Using a power meter consistently is ideal for this model to work. However, if there is lost data, corrupted data, or times when power was not used there are ways to estimate TSS. Comparing an effort to an historically similar one, using heart rate data, or by estimating Intensity Factor (IF) are all acceptable methods for calculating TSS in the absence of power.
If access to historical power meter data isn’t an option then there are ways to “seed” the numbers to get started. Making CTL and ATL the same and thus creating a TSB of zero is a safe place to start. Most athletes train at a TSS of 50-75 TSS/day and a weekly average IF of .70-85.
Use experience to tailor the Performance Manager Concept. Adjusting the ATL constant differently than the standard 7 days can reflect how fatigue actually occurs during times of heavy and light training. The goal is to produce a more accurate TSB.
Maintain perspective when using power to manage performance. Understanding how different times in the season impact fitness and form, as well as the demands of the training being completed. Not all efforts are equal and it’s important to apply the “art” of planning along with a quantitative approach.
