In this post, I'd like to show some data to highlight a few important aspects when analyzing your heart rate variability (HRV) data. In particular, I'd like to cover some misconceptions about the relationship between training and HRV as well as the importance of lifestyle and psychological aspects (context!).

We'll use my own data collected between January and April 2018, so 3 months in which I went from best shape of my life to injured and then back to training regularly post-injury, but in poor shape (detrained). We'll look at:

1. The basics: acute response to high-intensity training
2. The more interesting stuff: positive long term adaptation to high intensity and high volume training
3. Context: negative response to poor lifestyle choices following an injury
4. Feedback loop vs fitness marker: assessing full (physiological) recovery
5. Putting it all together

I hope this case study can be a good starting point to identify useful ways to look at your data using HRV4Training Pro.

I​n this post we’ll show two methods we have implemented in HRV4Training Pro to let you easily track changes in aerobic endurance while preparing a running or cycling event, so that you can analyze your progress:

• Aerobic efficiency
• Cardiac decoupling (currently in Beta)

Using these two methods and analyzing changes systematically over time with respect to your historical data, it should be easy to track improvements (or lack thereof) over time and make meaningful adjustments to your training plan.

​Learn more at this link.

​In this post, we go over the 12 weeks leading to Serena's first marathon. 

We'll see how HRV data can be used to analyze positive adaptations (increasing or stable HRV baseline) and to determine when to hold back if necessary (HRV baseline below normal values, or maladaptation detected).

We'll also see how to analyze training intensity distribution and how to determine race pacing strategy using HRV4Training Pro.

As always, while this post is about data, there is no use in data without common sense. Data is not here to replace our brain. Data is here to help us improve our understanding of our body and perception of stress and effort - something we are really bad at, especially as recreational athletes. 

Hopefully, the tools we have developed as well as this case study will help you to learn more about how you respond to stress and to manage things better. 

Thank you again Serena for working with me in these three months and congratulations again on your sub-4 marathon.

Train smart, run faster