{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,21]],"date-time":"2026-07-21T10:50:45Z","timestamp":1784631045183,"version":"3.55.0"},"reference-count":68,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2020,12,20]],"date-time":"2020-12-20T00:00:00Z","timestamp":1608422400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>The aim of this study was to update the metabolic power (MP) algorithm (PV\u02d9O2, W\u00b7kg\u22121) related to the kinematics data (PGPS, W\u00b7kg\u22121) in a soccer-specific performance model. For this aim, seventeen professional (Serie A) male soccer players (V\u02d9O2max 55.7 \u00b1 3.4 mL\u00b7min\u22121\u00b7kg\u22121) performed a 6 min run at 10.29 km\u00b7h\u22121 to determine linear-running energy cost (Cr). On a separate day, thirteen also performed an 8 min soccer-specific intermittent exercise protocol. For both procedures, a portable Cosmed K4b2 gas-analyzer and GPS (10 Hz) was used to assess the energy cost above resting (C). From this aim, the MP was estimated through a newly derived C equation (PGPSn) and compared with both the commonly used (PGPSo) equation and direct measurement (PV\u02d9O2). Both PGPSn and PGPSo correlated with PV\u02d9O2 (r = 0.66, p &lt; 0.05). Estimates of fixed bias were negligible (PGPSn = \u22120.80 W\u00b7kg\u22121 and PGPSo = \u22121.59 W\u00b7kg\u22121), and the bounds of the 95% CIs show that they were not statistically significant from 0. Proportional bias estimates were negligible (absolute differences from one being 0.03 W\u00b7kg\u22121 for PGPSn and 0.01 W\u00b7kg\u22121 for PGPSo) and not statistically significant as both 95% CIs span 1. All variables were distributed around the line of unity and resulted in an under- or overestimation of PGPSn, while PGPSo routinely underestimated MP across ranges. Repeated-measures ANOVA showed differences over MP conditions (F1,38 = 16.929 and p &lt; 0.001). Following Bonferroni post hoc test significant differences regarding the MP between PGPSo and PV\u02d9O2\/PGPSn (p &lt; 0.001) were established, while no differences were found between PV\u02d9O2 and PGPSn (p = 0.853). The new approach showed it can help the coaches and the soccer trainers to better monitor external training load during the training seasons.<\/jats:p>","DOI":"10.3390\/ijerph17249554","type":"journal-article","created":{"date-parts":[[2020,12,21]],"date-time":"2020-12-21T01:01:08Z","timestamp":1608512468000},"page":"9554","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["The Validity of an Updated Metabolic Power Algorithm Based upon di Prampero\u2019s Theoretical Model in Elite Soccer Players"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5713-0699","authenticated-orcid":false,"given":"Cristian","family":"Savoia","sequence":"first","affiliation":[{"name":"Research Institute for Sport and Exercise Sciences (RISES), Tom Reilly Building, Liverpool John Moores University, Liverpool L2 2ER, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4254-3105","authenticated-orcid":false,"given":"Johnny","family":"Padulo","sequence":"additional","affiliation":[{"name":"Department of Biomedical Sciences for Health, Universit\u00e0 degli Studi di Milano, 20122 Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roberto","family":"Colli","sequence":"additional","affiliation":[{"name":"Department of Biotechnological and Applied Clinical Sciences, University of L\u2019Aquila, 67100 L\u2019Aquila, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Emanuele","family":"Marra","sequence":"additional","affiliation":[{"name":"School of Sport Sciences and Exercise, Faculty of Medicine and Surgery, Tor Vergata University, 00133 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0964-7199","authenticated-orcid":false,"given":"Allistair","family":"McRobert","sequence":"additional","affiliation":[{"name":"Research Institute for Sport and Exercise Sciences (RISES), Tom Reilly Building, Liverpool John Moores University, Liverpool L2 2ER, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Neil","family":"Chester","sequence":"additional","affiliation":[{"name":"Research Institute for Sport and Exercise Sciences (RISES), Tom Reilly Building, Liverpool John Moores University, Liverpool L2 2ER, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vito","family":"Azzone","sequence":"additional","affiliation":[{"name":"Federazione Italiana Giuoco Calcio (F.I.G.C.), 00198 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7680-3991","authenticated-orcid":false,"given":"Samuel A.","family":"Pullinger","sequence":"additional","affiliation":[{"name":"Research Institute for Sport and Exercise Sciences (RISES), Tom Reilly Building, Liverpool John Moores University, Liverpool L2 2ER, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4753-4195","authenticated-orcid":false,"given":"Dominic A.","family":"Doran","sequence":"additional","affiliation":[{"name":"Research Institute for Sport and Exercise Sciences (RISES), Tom Reilly Building, Liverpool John Moores University, Liverpool L2 2ER, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.humov.2016.05.007","article-title":"Match play demands of 11 versus 11 professional football using Global Positioning System tracking: Variations across common playing formations","volume":"49","author":"Tierney","year":"2016","journal-title":"Hum. 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