New feature in HRV4Training Pro: Training Monotony

Blog post by Marco Altini

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We have released a new feature in HRV4Training Pro: Training Monotony.

In case you want to jump right in, and check out our latest feature, simply login at HRV4T.com with your HRV4Training credentials, then navigate to Insights / Training Load Analysis

As a coach, you can access these estimates for all your athletes from the Coach Panel.

Overview of the Training Load Analysis in HRV4Training Pro. 

What is it?

Training monotony refers to the similarity of daily training. In practical terms, this is a statistical representation of how much your training stimulus is varying over time.

As in all other analysis included under our training load analysis, the first thing to do is to pick a training load metric, or training impulse. This can be relative effort, TSS, RPE, RPE x Duration or any other parameter that is relevant in your sport.

​Once you have picked this parameter, HRV4Training Pro will analyze on a weekly basis, to determine training monotony.

Freshness, injury risk and monotony are computed from training impulse and can be representative of different processes. Freshness is about recovery and being race ready, injury risk compares your recent and habitual load to determine if you have increased load too much with respect to what you are used to, and therefore increased injury risk. Monotony concerns variation in training, with the idea that optimal performance is associated to higher variation.

How do you use it?

In general, low monotony (a value below 1.5 for example) is preferable so that different training adaptations can be triggered, while allowing for sufficient recovery to the body. Low monotony is normally associated to a polarized training and other periodization methods alternating high and low intensity workouts. 

On the other hand, a high value for training monotony indicates that the training program might be ineffective and lead to stagnation, or lack of improvement. Hence, if your score tends to be higher, it might be time to try something different. 

Here is for example a month of workouts of varying intensity and duration, resulting in very different relative efforts (the training impulse metric available in Strava and used for this example):

You can see how training monotony is indeed very low:

On the other hand here we have a week with very similar workouts (second row in particular):

Which corresponds to the yellow spike in monotony below, an indication that the stimulus recently has been always quite similar on a day to day basis, which might be unproductive for performance:

Needless to say, this is an oversimplification of the many processes affecting human performance. However, several authors have found that lower monotony is linked to higher performance, and therefore we hope this extra data point that can be informative and help you critically analyze your progress. 

Alright, that's all for this update. Enjoy.

Useful resources:

• Fellrnr.com on training monotony 
• Simplifaster on training monotony