Validation of the metabolic power model during three intermittent running-based exercises with emphasis on aerobic...

In intermittent sports, available internal load measurements like capillary blood techniques and portable respiratory gas analyzers are considered as gold standards in controlled laboratory environments, but are impractical for daily use in training and matches. A newer approach, the metabolic power model, allows to extrapolate from speed and acceleration data to the metabolic power, simulated oxygen uptake, and aerobic and anaerobic energy supply. The aim of this study was to validate the metabolic power model against the established 3-component model to allow direct comparison of variables including energy expenditure and supplies during intermittent running-based exercises.

Twelve male athletes (24 ± 3 years) performed three different running-based exercises consisting of continuous shuttle runs and repeated accelerations and sprints with change of direction. Each exercise condition intended to primarily stress the aerobic, anaerobic alactic, and lactic energy supply. One-way repeated measures ANOVA or Friedman test and corresponding effect sizes were applied for statistical analyses. Additionally, absolute and relative biases and Bland-Altman plots were generated.

For total energy expenditure, there were statistically significant differences (p ≤ .002, d ≥ .882, large) and biases of -13.5 ± 11.8% for the continuous shuttle runs and up to 352.2 ± 115.9% for repeated accelerations and sprints. Concerning aerobic energy supply, there were statistically significant differences (p < .001, d ≥ 1.937, large effect sizes) and biases of up to -38.1 ± 11.7%. For anaerobic energy supply, there were statistically significant differences (p < .001, d ≥ 5.465, large) and biases of up to 1,849.9 ± 831.8%.

In conclusion, the metabolic power model significantly under- or overestimates total energy expenditure and supplies with large effect sizes during intermittent running-based exercises. Future studies should optimize the model before it can be used on a daily basis for scientific and practical purposes.