How accurate is the data?
The use of so‑called wearables is immensely popular. At the end of the 1970s, Polar launched the first wearable in the form of a wireless heart rate monitor as a training tool for competitive athletes. Since then, the market has exploded: roughly 40% of people now wear a smartwatch or something similar such as an Oura ring or a Whoop band. The range of data you can measure with these devices is extensive: sleep patterns, HRV (heart rate variability), energy expenditure, daily steps, heart rate, your location, and much more.
The obvious question is how accurate these measurements actually are. After all, if they are precise, you could make huge gains in your health. I went down the rabbit hole to get more clarity on this. The examples mentioned above are discussed in more detail below.
Sleep pattern
When it comes to total sleep duration and how efficiently you sleep, the measurements are reliable. Most modern wearables deviate only slightly—about 5 to 15 minutes—compared with polysomnography (PSG), which is considered the gold standard for this assessment and can only be done in a sleep lab. However, things become less accurate when looking at sleep stages: light sleep, deep sleep, and REM sleep. Although the technology is constantly improving, wearables tend to overestimate the amount of deep sleep and underestimate the amount of REM sleep and wakefulness. They are therefore excellent for tracking trends in your total sleep, but for a true medical analysis of your sleep architecture, a visit to a sleep lab is still unavoidable (Doherty et al., 2024; Menghini et al., 2025).
HRV (Heart Rate Variability)
Heart rate variability, or HRV, is a popular recovery metric that captures the variation in time between heartbeats. Higher HRV is generally associated with better fitness and recovery. Scientific research shows that HRV measurements taken by wearables at night during rest (as done by, for example, the Oura ring and Whoop band) are surprisingly accurate. Their agreement with medical‑grade ECG measurements is often excellent. However, the reliability decreases significantly when you are active, and sometimes even during the day if there is a lot of arm movement. If you attach great value to HRV, it is best to rely primarily on the nighttime values (Doherty et al., 2024; Georgiou et al., 2018).
Energy expenditure
The number of calories burned is arguably the most commonly used, yet at the same time the least accurate measurement from a wearable. Indirect calorimetry is a very precise method for determining resting metabolic rate. When you compare its outcomes with those from a wearable, you see large error margins in the wearable’s estimates. These errors can be as large as 30% or even more. Devices tend to overestimate expenditure during low‑intensity activities and underestimate it during high‑intensity activities (O’Driscoll et al., 2020).
Daily steps
The classic target of 10,000 steps per day is a motivator for many people. Fortunately, this is one of the functions that wearables generally handle quite well. During normal walking on a flat surface, most wrist‑worn step counters are reasonably accurate, with an error margin of just a few percent compared with manual step counting. Accuracy does decline at lower walking speeds (such as in older adults or during rehabilitation) or in activities where your arms do not swing, such as pushing a stroller. Nevertheless, step counting remains a reliable and accessible way to get a sense of your daily activity (Doherty et al., 2024; Fuller et al., 2020).
Heart rate
Heart rate measurements from the back of the watch on your wrist are fairly accurate, especially at rest. In most everyday situations and sports with steady intensity, such as jogging or cycling, modern wearables provide a trustworthy picture, differing by just a few beats per minute from an ECG chest strap. The challenge arises during rapid intensity changes (for example, interval training) or sports with lots of wrist movement (such as tennis, basketball, or strength training). In those conditions, the sensor often cannot keep up with fast changes in blood flow, leading to larger errors. For the most precise measurement during intense sports, a chest strap therefore remains superior (Chevance et al., 2022).
Location
GPS‑based location tracking in sports watches is very accurate, often down to just a few meters. Modern watches use multiple satellite systems simultaneously, which significantly improves reliability. Accuracy can temporarily decrease in environments with poor signal, such as dense urban areas with tall buildings, in forests, or during very cloudy weather. Overall, however, you can trust that the recorded distance is a good reflection of reality.
Conclusion
For athletes, wearing wearables carries a double risk. The basic measurements—heart rate, nighttime HRV, sleep duration—are quite reliable. However, the composite “recovery” or “readiness” scores that many athletes use to plan their training and/or day are far less dependable. The algorithms that companies like Garmin or Apple use to derive these scores are largely secret, poorly validated, and often create a false sense of (in)security (Doherty et al., 2025).
The consequence is that athletes may start ignoring their own bodily sensations. Research shows that athletes sometimes skip a workout because their wearable shows “red,” even though they actually feel fine—and the reverse also happens (Lundstrom et al., 2024; Ibrahim et al., 2024). This can undermine the intrinsic self‑regulation that is essential in elite sport.
The solution is simple: treat your wearable as a signal, not as a command. Trust the raw data (heart rate, sleep, activity), but never use recovery scores as the sole basis for training decisions. The combination of objective data, subjective feeling, and a solid training plan remains invaluable. If you find yourself being overly influenced by recovery scores or similar composite metrics, you can usually switch these off easily in the device’s settings.
Personal note
If you are curious about how I use my Garmin watch (Forerunner 165, €155), the answer is very straightforward. I use it for displaying my heart rate in combination with a chest strap, for GPS, and for the step counter. My VO2max was determined through a labtest and manually entered into my smartwatch, so that I can also achieve accurate training goals with it, such as training in zone ‘X’, for example.For everything else, I rely on my own feelings and intuition. Garmin also offers many more expensive models, some well over €1000. It is very tempting to buy one of those because they look fancy. The same goes for more “exotic” wearables such as a Whoop band or an Oura ring.
And that is exactly where it gets tricky. People are always searching for something new, something sexy, something that captures the imagination. You see this not only in the purchase of such gadgets, but also in other areas such as specific training methods or new diets. However, it is crucial to keep distinguishing what is meaningful from what is not. Often these things work suboptimally (or simply not at all), and if you had stuck with the basics you would have achieved the same—or even better—results.
Roeg Kuijpers
Nutritonist, pro athlete coach and personal trainer
Chevance, G., Golaszewski, N. M., Tipton, E., Hekler, E. B., Buman, M., & Welk, G. J. (2022). Accuracy and precision of energy expenditure, heart rate, and steps measured by combined-sensing fitbits against reference measures: Systematic review and meta-analysis. JMIR mHealth and uHealth, 10(4), e35626. https://doi.org/10.2196/35626
Doherty, C., Baldwin, M., Lambe, R., Burke, D., & Altini, M. (2025). Readiness, recovery, and strain: An evaluation of composite health scores in consumer wearables. Translational Exercise Biomedicine, 2(2), 128–144. https://doi.org/10.1515/teb-2025-0001
Doherty, C., Baldwin, M., Keogh, A., Caulfield, B., & Argent, R. (2024). Keeping pace with wearables: A living umbrella review of systematic reviews evaluating the accuracy of consumer wearable technologies in health measurement. Sports Medicine, 54(11), 2907–2926. https://doi.org/10.1007/s40279-024-02077-2
Fuller, D., Colwell, E., Low, J., Orychock, K., Tobin, M. A., Simango, B., Buote, R., Van Heerden, D., Luan, H., Cullen, K., Slade, L., & Taylor, N. G. (2020). Reliability and validity of commercially available wearable devices for measuring steps, energy expenditure, and heart rate: Systematic review. JMIR mHealth and uHealth, 8(9), e18694. https://doi.org/10.2196/1869
Georgiou, K., Larentzakis, A. V., Khamis, N. N., Alsuhaibani, G. I., Alaska, Y. A., & Giallafos, E. J. (2018). Can wearable devices accurately measure heart rate variability? A systematic review. Folia Medica, 60(1), 7–20. https://doi.org/10.2478/folmed-2018-0012
Ibrahim, A. H., Beaumont, C. T., & Strohacker, K. (2024). Exploring regular exercisers’ experiences with readiness/recovery scores produced by wearable devices: A descriptive qualitative study. Applied Psychophysiology and Biofeedback, 49(4), 395–405. https://doi.org/10.1007/s10484-024-09645-2
Lundstrom, E. A., De Souza, M. J., Koltun, K. J., Strock, N. C. A., Canil, H. N., & Williams, N. I. (2024). Wearable technology metrics are associated with energy deficiency and psychological stress in elite swimmers. International Journal of Sports Science & Coaching, 19(5), 1578–1587. https://doi.org/10.1177/17479541231206424
Menghini, L., Plazzi, G., & Ferri, R. (2025). Beyond the sleep lab: A narrative review of wearable sleep monitoring. Bioengineering, 12(11), 1191. https://doi.org/10.3390/bioengineering12111191
O’Driscoll, R., Turicchi, J., Beaulieu, K., Scott, S., Matu, J., Deighton, K., Finlayson, G., & Stubbs, J. (2020). How well do activity monitors estimate energy expenditure? A systematic review and meta-analysis of the validity of current technologies. British Journal of Sports Medicine, 54(6), 332–340. http://dx.doi.org/10.1136/bjsports-2018-099643