Quantifying Myself
Intentions for a New Bike Racing Season of Self-Measurement
As a competitive bike racer and endurance athlete, I‘ve always focused on training, recovery, nutrition and equipment. My training is structured and specific, spent primarily on my indoor trainer, riding in coach-prescribed power zones based on my race event calendar. Recovery is about getting enough high-quality sleep for me to wake up feeling mentally and physically refreshed. Nutrition is about fueling my work, both on and off the bike. And equipment is about fitting my bike to my body, and making smart choices based on the conditions and course.
I’m aware of the sports science surrounding many of these concepts. I’ve tracked my training and sleep metrics with all types of devices — including a Fitbit, an Apple Watch, a Whoop strap, an Oura ring and others — over the years. And I’ve analyzed and reported on some of this data in previous blogs. Despite this passive tinkering, I’ve never been inspired to try to get a handle on how all of these things interact, and how any of these things impact my performance, until I listened to a DataCamp podcast on an organization called Quantified Self.
Quantified Self
The Quantified Self is an international community of users and makers of self-tracking tools who share an interest in “self-knowledge through numbers”. The community is aimed at supporting anybody who wants to use empirical methods to explore personal questions — to answer a health question, achieve a goal, explore an idea, or simply for curiosity.
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Self-Tracking Projects
For each project question, experimenters are encouraged to think through a series of four (4) activities:
- Questioning: Is the process of formulating the objectives of a self-tracking project. For me, I want to get a better perspective on the factors associated with higher or lower cycling performance so that I can be faster on the race course.
“The process of articulating your reasons to do a self-tracking project is…far more important than what gadget to use, what methods to apply or what interventions to test. When you articulate your reasons, you clarify the criteria for choosing what to track and what tools to use” — QS
- Observing: Is the act of making deliberate observations to answer your questions. This requires figuring out what to observe and then making those observations in the simplest way possible. Ideally, I will use one of my passive tracking devices to record as many metrics as possible, and couple that with minimal subjective self-assessments.
“If your project requires a lot of (observational) work every day, you’re more likely to drop it before you learn anything useful. Ask yourself: how’s this process going to feel when my initial enthusiasm dips, or my work or family life requires extra attention” — QS
- Reasoning: Is the activity of analyzing observations in order to reason about your specific question. Analysis can happen against a baseline, and over time. And it can involve any number of tools and methods. As a data scientist, it will be important for me to consolidate my observations into scalable data pipelines and automate the analytical process through interactive visualizations.
- Consolidating Insight: Is the continuous reasoning and sharing of observations over time in pursuit of the question, as a way of thinking more deeply about it, and even trying out new techniques to test or refine it over time. I’ll be sharing my learnings here, as well as on the Quantified Self Forum with other like-minded self-trackers.
Parting Thoughts
Self-measurement is probably more anecdote than rigorous science. But it’s a way for me to think more deeply and organize my thinking about my own cycling performance, which has value to me.
