Smartwatches typically overestimate calories burned, with errors ranging from about 15% to over 100% depending on the activity. During cardio exercises like running or cycling, most devices land within 15% to 40% of the true value. During strength training, the errors can be dramatically worse. These devices are useful for spotting trends over time, but the specific calorie number on your wrist after a workout is best treated as a rough estimate, not a precise measurement.
How Smartwatches Calculate Calories
Your smartwatch combines several streams of data to guess how much energy you’re burning. A motion sensor (accelerometer) tracks your arm movements in three dimensions to identify what kind of activity you’re doing and how intensely. A light-based heart rate sensor shines green LED light into your skin and measures how much light bounces back, which changes with each heartbeat as blood pulses through your wrist capillaries. Faster heart rate generally means higher energy expenditure.
The device feeds these signals into an algorithm along with your personal profile: age, weight, height, and sex. The algorithm then estimates calories using equations that were developed and tested on specific populations, mostly in controlled lab settings. This is where much of the inaccuracy creeps in. The real world is messier than a lab, and people’s bodies vary more than any single equation can account for.
Accuracy During Cardio Exercise
Cardio is where smartwatches perform best, and the errors are still significant. In a study comparing four popular devices (Apple Watch Series 7, Galaxy Watch 4, Fitbit Charge 5, and Garmin Vivosmart 5) against a metabolic cart, the gold standard for measuring energy expenditure, all four overestimated calories during endurance exercise. The true average burn was about 204 calories. Apple Watch reported 233, Galaxy Watch came in at 222, Fitbit read 246, and Garmin showed 266.
That puts Garmin’s overestimate at roughly 30% above the actual value, while the Galaxy Watch was closest at about 9% over. But averages hide a bigger problem: individual readings varied wildly. The Garmin’s error for any single person could swing from underestimating by 19 calories to overestimating by 143 calories. The Galaxy Watch had a similarly wide spread. So even the most accurate device on average could be far off for you personally on any given day.
Accuracy During Strength Training
Calorie tracking falls apart during resistance exercise. The same study found that the true calorie burn for a strength workout averaged about 141 calories. Fitbit Charge 5 came remarkably close at 146 calories. But Apple Watch reported 299, Galaxy Watch showed 258, and Garmin displayed 305. That means Apple Watch and Garmin were overestimating by more than double the actual burn.
The reason is straightforward. Heart rate stays elevated during weight training, but much of that elevation comes from straining against resistance, holding your breath, and resting between sets rather than from sustained aerobic work. The algorithms interpret a high heart rate as high calorie burn, because they were largely calibrated on steady-state cardio activities. Movements during lifting are also less rhythmic and predictable than running or cycling, making it harder for the motion sensor to correctly classify what you’re doing.
Why Some People Get Worse Results
The algorithms powering these devices were trained on data from specific groups of people, and if your body doesn’t match those profiles, accuracy drops further.
People with higher BMI often have different walking patterns, speeds, and postures, and their bodies use energy differently at rest. Most fitness tracker algorithms don’t account for these differences, leading to less accurate calorie estimates for people with obesity. Researchers at the National Center for Advancing Translational Sciences have developed improved algorithms specifically for this population, but they haven’t made it into most consumer devices yet.
Skin tone also plays a role. Because the heart rate sensor relies on light passing through skin, melanin levels affect the signal. A systematic review in the Journal of the American College of Cardiology found that 40% of the studies examined showed significantly reduced heart rate accuracy in people with darker skin tones compared to lighter skin tones or gold-standard measurements. One study found that devices recorded fewer data points entirely for darker-skinned users. Since heart rate is a key input for calorie calculations, any heart rate error cascades directly into calorie error.
Other factors that reduce accuracy include tattoos on the wrist (which interfere with the light sensor), a loose watch band, cold temperatures that reduce blood flow to the skin, and irregular heart rhythms that confuse the pulse-detection algorithm.
Real-World Activities Are Harder to Track
Most validation studies test smartwatches during treadmill running or stationary cycling, controlled and repetitive movements that are easiest for algorithms to interpret. Real life looks different. A 2025 validation study published in JMIR Cardio tested a medically certified wrist sensor during household activities that reflect daily living, like cleaning or moving around the house. The researchers found poor accuracy for energy expenditure in these conditions, even though newer devices had shown promising results during structured exercise tests in other studies.
The gap between lab performance and real-world performance remains one of the biggest unresolved issues in wearable calorie tracking. Activities involving mostly your lower body (like cycling on a stationary bike), carrying objects, or staying relatively still while exerting effort (like yoga or climbing) are especially prone to error because the wrist sensor simply can’t “see” what your body is doing.
How to Use the Data Wisely
The calorie number on your watch is most useful as a relative measure, not an absolute one. If your watch says you burned 400 calories on Tuesday and 550 on Thursday, you probably did work harder on Thursday, even if neither number is exactly right. Tracking trends over weeks and months is where these devices genuinely help. A consistent increase in your weekly calorie burn reflects real changes in your activity level, regardless of whether each individual reading is precise.
If you’re using calorie data to manage your weight, build in a buffer. A reasonable rule of thumb is to assume the device is overestimating by at least 20% to 30% during cardio and potentially much more during strength training. If your watch says you burned 500 calories on a run, planning around 350 to 400 is closer to reality for most people.
Consistency also matters more than accuracy. Wear the same device on the same wrist with the same tightness, and enter your current weight regularly. This won’t make the absolute numbers correct, but it keeps the errors consistent, which means the trends in your data stay meaningful. Switching between brands or devices resets that consistency, since each manufacturer’s algorithm has its own biases and blind spots.