Hiring in life sciences? Share your open positions with our professional community. Read more Close

Advertisement

Indirect calculation of metabolic power in soccer: a critical analysis of a popular model.

Created on 03 Aug 2026

Authors

Furio Barba, Johnny Padulo, Nicola Maffulli

Published in

British medical bulletin. Volume 159. Issue 1. Jul 03, 2026.

Abstract

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.
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).
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.
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.
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.
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.

PMID:
42544508
Bibliographic data and abstract were imported from PubMed on 03 Aug 2026.

Read full publication at:
Please sign in to see all details.

Advertisement

Stats

  • Community rating n/a 0 votes
  • Reviewers' rating n/a 0 votes
  • Your rating

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

  • Recommendations n/a n/a positive of 0 vote(s)
  • Views 7
  • Comments 0

Recommended by

  • No recommendations yet.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.

Advertisement