January recap 🗓️
hi there 👋
I hope all is well. I’ve decided to switch to a different format for my updates. As I tend to write quite a bit, you will now receive only one email per month, with an overview of what I’ve been writing in the previous month.
Here is my January recap, broken down by topic, with links to the individual articles.
Heart rate variability (HRV) 🫀
Stability in HRV: a training perspective. In this first article, I discussed the importance of a stable HRV. I cover the basic research showing how the stress response to training is clearly captured by HRV, and how the intensity of the stimulus (e.g. below or above the first ventilatory threshold) and the fitness level of the athlete will determine how long the recovery will be. I then highlight how a stable HRV shows an ideal response, even when training hard (a common misconception is that HRV should drop on these occasions). We will also see examples and how to keep track of the stability of your HRV in HRV4Training.
Heart Rate Variability (HRV) measurement timing: morning or night? a look at stressor timing and measurement position. In this second article, I cover some key differences between morning and night measurements. In particular, we will see how night HRV can be useful to better understand aspects of our behavior: eating habits, alcohol intake, weight loss, and exercise timing, for example, but also how measuring closer to the previous day’s stressors, we might not capture the response effectively. On the other hand, measuring in the morning, while sitting, not only is better timing but also adds a little orthostatic stressor that can make the data more representative of our capacity to assimilate additional stress on a given day. I provide examples in the blog.
eat the tortilla: on night heart rate variability and (lack of) actionability. In this blog, I look at a specific example in which night HRV is failing to provide actionable data due to its close proximity to a late “stressor” (food intake), despite the beneficial effect of such food intake on performance.
Heart rate variability (HRV) and strength training some thoughts: a typical question we get a lot is the following: “does it make sense to use HRV if I do resistance or strength training”? In this last article, I try to answer this question based on published literature, a high-level view of stress, and conversations with trusted experts in the field (thanks, Andrew).
Wearables ⌚️
Wearables: what to pay attention to and what to ignore. I have had many conversations with coaches struggling to use data from wearables and determining what data can be trusted and what not. Dismissing it all is too simplistic and fails to recognize how data - in combination with other tools at our disposal - can be used effectively. In this article, I provide some pointers that should help you think more critically about the data collected and trust some of the parameters more than others.
Training talk 🏃🏻♂️
Finding marathon intensity: a data-driven approach. Being an outlier in running (in)efficiency, training for marathons has been a challenging process. Using heart rate data (and the right training) eventually played a key role in getting better, and in this blog, I cover the approach I have used.
Training intensity distribution: notes on polarized and pyramidal training for beginner endurance athletes. Due to the different contexts in which the term polarized training is used (e.g. elite vs beginner athletes), and different interpretations of the term polarized, this can be a somewhat confusing topic.
In this blog, I spent some time trying to better convey the message to beginner endurance athletes.
Training update: Nov 2022 - Jan 2023. VO2max block for a fast 10 km after a marathon PR. Last November I’ve written extensively about my past 6-8 months of training, in which I was able to make good progress after stalling for many years. In this blog, I cover the past 2 months of training, the time between November’s marathon PR and the 10 km PR I just ran in January (36’40” at Prom’ Classic in Nice).
Training log. As the name says, this is simply my training diary for the year.
That’s all for today, see you next month, and thank you for reading!
Marco holds a PhD cum laude in applied machine learning, a M.Sc. cum laude in computer science engineering, and a M.Sc. cum laude in human movement sciences and high-performance coaching.
He has published more than 50 papers and patents at the intersection between physiology, health, technology, and human performance.
He is co-founder of HRV4Training, advisor at Oura, guest lecturer at VU Amsterdam, and editor for IEEE Pervasive Computing Magazine. He loves running.
Twitter: @altini_marco