John Wakefield builds on the fundamentals of analysing your cycling training sessions to discuss the impact of wellness on training and how to adapt your training plan accordingly.
In my previous article, I broke down the metrics that we use to measure performance in a training session and how to use them effectively. Now we’re going to discuss monitoring off-the-bike factors that affect performance and how to use past training data to plan future sessions. If you haven’t read or listened to that yet, I would encourage you to do so as it provides a lot of context to what I will discuss here.
External Wellness Monitoring For Cycling Training
Remember a training file only tells you what the session was like, it does not tell you how the athlete himself/herself is or was feeling and any other variables that can affect their training. Has their wife run off to the pool boy when they don’t have a pool? Have there been kids who have been sick and so forth? All these are important to note when understanding how the athlete is, or even your own performance.
At Science to Sport, we have a weekly report that goes out to athletes, this has a series of questions that they answer which is returned to the coaches via an algorithm to track their off-bike wellness. This is a wellness report that athletes are required to fill in weekly, it is an external monitoring system and an add-on to a standard Performance Management Chart.
What is best to do is to cross reference an athlete’s training data on their good or bad days or weeks with the subjective reporting. Often this lines up well but what is important to note is that while their wellness may not be reporting high numbers, their training data may show the opposite as they are using the bike as a great stress release. So again, tracking this over time is key and so is understanding the athlete and their personality (or yourself in the case of self-training).
One of the greatest ways to track this is to simply ask the athlete (or yourself) “How are you feeling?”
Using Submaximal Fatigue Testing
Additionally, we also use the SFT (Submaximal Fatigue Test) to track and monitor fatigue and progression of an athlete. This is a 3 min effort at a certain power value throughout the year and prescribed every 7-10 days depending on their season – if they are doing a block of racing it is hard to implement.
In this above example you can see the athlete build in form with the Time to Exertion (TTE) for the effort progressing, and a sudden dip, this was due to fatigue and some illness, a recovery block was prescribed with some more rest and recovery + easy riding. They recovered and had a good adaptation to the same training load as previous and returned to training.
Chronic Training Load (CTL) and Training Stress Scores (TSS)
Further from the Wellness document, using a performance management chart is also a good way to note at what point they are producing productive sessions or not, taking into account their CTL and TSB figures.
While this is a good tool it is often used to chase Chronic Training Load (CTL). People think the more CTL you have the fitter or stronger you are. This is totally untrue, sorry to break the hearts of basically everyone reading this and the coaches who prescribe off of or to a TSS value. That is not coaching, that is chasing a number. As long as you get that number, it is all that matters no matter how you get there.
Yes, it is a good metric but it is a small metric to be considered in the overall picture. There is no “you must be 120 CTL to race Epic”, this is specific to each athlete. Use it but use it wisely and certainly not as the holy grail.
It is good to track build, see when the recovery is needed and then build again. There will be a time when this value will not increase as you need to fill this chart with data, more data, more CTL.
Remember this is always personal and the higher the CTL is often not better.
This leaves us with the question: “How should we be analysing our data to ensure that we are improving?”
How to analyse and capture our data to ensure that we are improving
Commonly, hard training sessions consist of interval sessions. The major advantage of training with a power metre is that it provides you with an exact objective measure of your performance. You should analyse and plot each interval and calculate your “session average” for the specific sessions.
It becomes a bit harder to measure performance objectively when you are not training with a power metre, because measures such as speed and distance may be affected by the wind and other factors but as mentioned in the previous article, it can be done. Even using a RPE (perceived exertion) value from the athlete at the end of a session is a great and easy way of monitoring and tracking progress.
Creating or using a document like this is a consistent and good way to analyse and plot each interval and calculate your “session average” for the specific sessions and will allow you to track an athlete’s progression.
How to use a “session average” tracking method
A great way to track your progression is to analyse these sessions and plot the values for each interval set.
If you are doing 4min torque intervals, add up each of the 4 minute intervals and divide by the total number of intervals (6 or 8 depending on the session). This will provide you with the average for the set of intervals.
The graph below shows how we plot an athlete’s progression during their block. The first two sessions went well, but the third session shows a decrease in the amount of torque produced. The drop in torque was most likely due to some acute fatigue, so we allowed for a slightly longer rest before the next session and they were able to produce their best numbers, above the two subsequent sessions.
Remember you are tracking Nm of torque for the low cadence.
The same is applied to the (Hi) intensity sessions, where we track Power (Watts) for the session. The same formula applies:
Therefore if you do a 3 x 10 minute interval session, and you achieve 410W, 398W and 388 watts for the 3 respective intervals, your session average is 399 watts. When you prescribe this training session next time, you can set targets at 405-410W
Take home from the article?
- Use an external monitoring system
additionally i.e. Wellness
- Prescribe training based off the analysis
Inclosing, remember to keep in mind the effect of off-the-bike factors on training adaptation and performance. You need to know the athlete (or yourself) well enough to understand their subjective reporting and how that should affect the prescribed training. Consider the response to previous sessions (that is why it is best to use standardised sessions) when planning future training to ensure the appropriate level of stress is applied for the desired adaptation.
Remember to have fun on the bike, this is why you started riding in the 1st place.
Gracias y adios!
John Wakefield is a director at Science2Sport. In addition, John works as a Performance Coach for Team BORA hansgrohe. With a successful history in motocross, his cycling focus has carried over and found success in a World Championship Title, World Tour and World Cup wins and Multiple National Titles. Find more of his articles here.