The observation that a workout burns fewer calories for one person than another, even when the activity is identical, is a common and often frustrating experience. This variability in energy expenditure reflects highly complex, individualized biology and physics. The amount of energy, measured in calories, a body uses during physical activity is influenced by physical size, metabolic machinery, training history, and the accuracy of the tracking device. Understanding these factors illuminates why calorie burn is never a one-size-fits-all metric.
The Role of Body Size and Composition
The most straightforward explanation for differences in calorie expenditure lies in the basic physics of movement. A larger body requires more energy to move a given distance or perform a specific mechanical task than a smaller body. For instance, a 180-pound person must expend significantly more calories to run a mile than a 120-pound person at the same pace because they move a greater total mass against gravity and friction.
Beyond total weight, the body’s composition—the ratio of muscle mass to fat mass—plays a role. Muscle tissue is more metabolically active than fat tissue, requiring more energy to maintain even at rest. A person with more lean muscle mass may have a higher total energy demand, contributing to a greater overall calorie burn during and after a workout.
Understanding Metabolic Rate and Genetic Influence
The body’s metabolic rate is a major determinant of how many calories are burned throughout the day, including during a structured workout. The Basal Metabolic Rate (BMR) or Resting Metabolic Rate (RMR) represents the energy required to maintain basic life functions, such as breathing and circulation, when the body is at complete rest. This resting burn accounts for 60 to 75% of the total daily energy expenditure.
Individual differences in BMR are influenced by factors such as genetics, age, and sex. Males tend to have a higher BMR than females, largely due to a greater proportion of lean muscle mass and larger body sizes. Aging is associated with a decline in BMR, primarily due to a natural loss of muscle mass over time. Genetic factors contribute significantly to BMR variability, with some studies suggesting a variance of up to 26% between individuals.
Non-Exercise Activity Thermogenesis (NEAT)
Non-Exercise Activity Thermogenesis (NEAT) accounts for the energy expended in all spontaneous, non-planned movements, such as fidgeting or standing. Differences in NEAT can vary by as much as 2,000 calories per day between people of similar body size. An individual with a high level of unconscious movement will burn more total calories, even if their formal workout is the same as someone who is more sedentary outside of exercise.
Training Adaptation and Movement Efficiency
Paradoxically, becoming fitter can lead to a lower calorie burn for a standardized workout because the body adapts to become more efficient. As a person consistently performs an activity, their nervous and muscular systems learn the most energy-efficient way to execute the movements. This phenomenon, known as movement efficiency, means a highly trained individual performs the same mechanical work with a lower oxygen cost and fewer calories burned than an untrained person.
A trained body maintains a lower heart rate and uses less energy at a given speed or resistance level compared to when the exercise was novel. Improved biomechanics and muscle memory reduce wasted energy expenditure. While this increased efficiency means fewer calories are burned per minute, it allows the conditioned individual to train for longer durations or at higher intensities, leading to a greater total calorie expenditure over the entire session.
Measurement Errors and Tracking Inaccuracies
The perceived difference in calorie burn is frequently a result of the limitations of the tracking technology itself. Most commercial fitness trackers, heart rate monitors, and gym equipment rely on proprietary algorithms to estimate energy expenditure. These devices typically combine data like heart rate, body weight, age, and accelerometer readings to calculate calorie burn.
The accuracy of these estimates is highly variable. Studies have shown that while heart rate readings can be accurate, the calorie burn calculation can be off by an average of 27% to as much as 93% on the least accurate devices. These algorithms make broad assumptions about metabolic efficiency and movement patterns that do not account for unique biological variability. A lower number seen on a personal device may simply reflect a difference in the device’s estimation method, rather than a true physiological difference.