"It has become appalingly obvious that our technology has exceeded our humanity."
~Donald Ripley
In honor of Labor Day, I’ve been thinking about the “work” we runners put in. Not just the miles, but how we measure and make sense of them. Some runners swear by the precision of a chest strap, while others prefer the convenience of a wristwatch. Perhaps your device of choice is a Whoop strap, while your training partner prefers an even more discreet Oura ring. And then there are those who rely on something even less tangible…our gut. That intuitive sense that quietly analyzes when to push and when to hold back.
The truth is, most of us use a combination of these tools, each with its quirks and margins of error. This, in my opinion, is a wise play. Rely too heavily on one, and the balance tips. This could result in too little training, leading to endless plateaus, or training too heavily where we tip-toe the line between overtraining, or worst of all, the slide toward injury or burnout.
For athletes and coaches, the ability to sift through the mountain of data our wearables provide is essential for turning numbers into meaningful training decisions. As training philosophies evolve, more athletes seek precise methods to monitor and measure their responses to training.
But what if the very devices we rely on to analyze this information give us generalized, highly presumptive data? Are general guidelines good enough? If you’re tracking assumptions after every workout, can you really trust those data points to guide the next session or help you develop a larger training plan?
The water gets even muddier when we depend on what are known as derived metrics—scores built from algorithms unknown to the public, i.e., TSS, TSB, and recovery time scores to name a few. How do we separate what I call “wearable errors” from genuine physiologic red flags—signals that if missed or ignored, could derail months of hard work or leave you sidelined with injury?
Regardless of where you stand on this debate, one point must be non-negotiable: if data is to be used for performance enhancement, and I’m not suggesting it shouldn’t be, it must be valid, reliable, and it must be meaningfully applicable…to you. Not your training partner and certainly not some of the best runners on the planet. Yes, training like the pros is probably a sound choice. But, using their data points as benchmarks to measure yours against...not so much.
How to make the most of the data our wearables give us
Get in the lab
I’m not suggesting you need a membership to a human performance lab, or that you should be poked and prodded until you feel more like a lab rat than a runner. But if you want to make sense of the data your wearable gives you, you need a credible baseline. Two tests that most serious runners can benefit from are a lactate threshold test and a VO₂max test. The information gleaned from these tests provides context for your wearable’s raw data, helping you and/or your coach make smarter training decisions. In my opinion, too many athletes let wearable metrics steer their training without a solid starting point. This results in an immense amount of noise that can cloud our decision-making. It is this same noise that I believe plays a profound role in disconnecting us from our ability to use autoregulation to help guide our training.
Know what data is accurate and applicable
With watches being the most common wearable among runners, I did a deep dive to see which metrics are based on direct measurements and which rely heavily on formulas or algorithms. Reviewing the literature across brands and models reveals a few consistent themes. For clarity, I focused on studies examining raw data, such as heart rate, speed, and distance. One key takeaway: most derived metrics, like TSS, recovery time, and TSB, can only be accurate if the underlying raw data is reliable.
Across all models of commonly worn running watches, as exercise intensity increases, reliability tends to decrease, which is especially important for runners who regularly engage in speed training. The most accurate readings are produced at rest or during low-intensity exercise. Exercise caution when interpreting workouts solely based on what your watch tells you.
Watches that use optical heart rate monitors show a highly variable margin of error, with most studies recommending a chest strap whenever possible. Since many derived metrics are based on heart rate, this is a crucial takeaway. Other factors, such as loose fit, dark skin, tattoos, sweat, and rapid arm movements, can further affect validity, so it’s important to account for these whenever possible.
Adapted from studies by Wallen, Boudreaux, and Gilgen-Ammann
The human element still matters…a lot!
No wearable, stress score, or algorithm-derived data point can tell you how you feel better than you can. Some of the best athletes I know are so incredibly in tune with their bodies that even the slightest perturbations in their environment prompt vigilance and sometimes elicit a course correction. Our bodies are constantly providing us with feedback. Whether it’s assessing overall energy levels, muscle soreness, breathing, or your response to a recent uptick in training intensity, no device on this planet can fully capture the subtle signals we experience as athletes. Wearables are most helpful when we use them as a guide, not a hard-and-fast rule. At the end of the day, training is a lot more than just numbers. After all, you can measure just about anything in training, but do these numbers really mean anything?
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