Introduction: The Global Positioning System (GPS)-based metabolic power model for soccer, proposed by di Prampero and applied by Osgnach, rests on a fixed energy cost (EC) of running of 4.6 J·kg-1·m-1 and a biomechanical equivalence between accelerated level and constant-speed uphill running. Sources of data: A narrative review was conducted via PubMed, Scopus, and Web of Science using terms like metabolic power, EC of running, GPS soccer, sprint biomechanics, equivalent slope, and running economy (2005-2025). Areas of agreement: Running EC is relatively speed-independent across submaximal velocities typical of football (~6-18 km·h-1). The geometric principle underlying the accelerated-to-inclined running equivalence is accepted, and GPS metabolic power provides a useful metric for relative load comparisons. Areas of controversy: A universal fixed EC ignores interindividual variability (~20%), fatigue, surfaces, and drag. The equivalence model has vector orientation inconsistencies, employs the imprecise term 'equivalent mass', and derives its postural reference from sprint-start conditions unrepresentative of match-play accelerations (~2-4 m·s-2). Validation studies show systematic underestimations of 29%-85% relative to indirect calorimetry. Refinements exist but remain unimplemented in most commercial platforms. Growing points: Individually calibrated EC values, inertial measurement unit integration, and hybrid models combining GPS kinematics with cardiorespiratory data are promising. Force-velocity profiling offers a biomechanically grounded alternative for individual sprint characterization. Areas timely for developing research: Priorities include calorimetric validation under match conditions; player-specific EC models incorporating fatigue, surface, and role; implementing model updates in commercial software; and comparing alternative load metrics for injury-risk prediction.
Indirect calculation of metabolic power in soccer: a critical analysis of a popular model / F. Barba, J.P.. - In: BRITISH MEDICAL BULLETIN. - ISSN 0007-1420. - 159:1(2026 Sep), pp. ldag022.1-ldag022.14. [10.1093/bmb/ldag022]
Indirect calculation of metabolic power in soccer: a critical analysis of a popular model
J. PaduloSecondo
;
2026
Abstract
Introduction: The Global Positioning System (GPS)-based metabolic power model for soccer, proposed by di Prampero and applied by Osgnach, rests on a fixed energy cost (EC) of running of 4.6 J·kg-1·m-1 and a biomechanical equivalence between accelerated level and constant-speed uphill running. Sources of data: A narrative review was conducted via PubMed, Scopus, and Web of Science using terms like metabolic power, EC of running, GPS soccer, sprint biomechanics, equivalent slope, and running economy (2005-2025). Areas of agreement: Running EC is relatively speed-independent across submaximal velocities typical of football (~6-18 km·h-1). The geometric principle underlying the accelerated-to-inclined running equivalence is accepted, and GPS metabolic power provides a useful metric for relative load comparisons. Areas of controversy: A universal fixed EC ignores interindividual variability (~20%), fatigue, surfaces, and drag. The equivalence model has vector orientation inconsistencies, employs the imprecise term 'equivalent mass', and derives its postural reference from sprint-start conditions unrepresentative of match-play accelerations (~2-4 m·s-2). Validation studies show systematic underestimations of 29%-85% relative to indirect calorimetry. Refinements exist but remain unimplemented in most commercial platforms. Growing points: Individually calibrated EC values, inertial measurement unit integration, and hybrid models combining GPS kinematics with cardiorespiratory data are promising. Force-velocity profiling offers a biomechanically grounded alternative for individual sprint characterization. Areas timely for developing research: Priorities include calorimetric validation under match conditions; player-specific EC models incorporating fatigue, surface, and role; implementing model updates in commercial software; and comparing alternative load metrics for injury-risk prediction.| File | Dimensione | Formato | |
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