{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T00:51:20Z","timestamp":1755219080627,"version":"3.43.0"},"reference-count":54,"publisher":"Public Library of Science (PLoS)","issue":"8","license":[{"start":{"date-parts":[[2025,8,6]],"date-time":"2025-08-06T00:00:00Z","timestamp":1754438400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Introduction<\/jats:title>\n<jats:p>Metabolic power is essential for assessing the physical demands of team sports. Accurately determining the energy cost of constant speed running (EC<jats:sub>0<\/jats:sub>), is crucial for refining these. EC<jats:sub>0<\/jats:sub> depends on factors like running velocity and V\u0307O\u2082max and varies between athlete groups due to training adaptations and sport-specific body characteristics. To ensure accurate energy expenditure, EC<jats:sub>0<\/jats:sub> should be individually determined based on the specific team sport, improving player monitoring, recovery, and load management.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Materials and Methods<\/jats:title>\n<jats:p>An experimental cohort study collected data from 339 incremental treadmill tests in elite team sports athletes: 11 male handball players, 120 male soccer players, 23 male and 185 female field hockey players. Athletes performed a treadmill protocol to exhaustion while O<jats:sub>2<\/jats:sub>-uptake, CO<jats:sub>2<\/jats:sub>-output, respiratory exchange ratio and ventilation were measured breath-by-breath. Data processing verified steady-state conditions. Net EC<jats:sub>0<\/jats:sub> was calculated as energy expenditure above rest divided by velocity. Sport, speed, sex and V\u0307O<jats:sub>2max<\/jats:sub> were defined as fixed effect variables.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Results<\/jats:title>\n<jats:p>Our random intercept and slope model with all predictors performed best. Handball players had the highest EC<jats:sub>0<\/jats:sub> (estimated total mean) with 4.04 J\/kg\/m (CI<jats:sub>95%<\/jats:sub> 3.88, 4.20), field hockey players with 3.95 J\/kg\/m (CI<jats:sub>95%<\/jats:sub> 3.90, 4.00) and soccer players with 3.79 J\/kg\/m (CI<jats:sub>95%<\/jats:sub> 3.73, 3.85). For the whole group, EC<jats:sub>0<\/jats:sub> showed a curvilinear dependence on speed: increasing with speed up to ~3.5 m\/s and then remaining relatively constant at higher velocities. However, grouping athletes by similar treadmill performance, EC<jats:sub>0<\/jats:sub> remained constant across speeds.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Discussion<\/jats:title>\n<jats:p>Our data show multiple predictors must be considered to determine an appropriate EC\u2080 for each athlete. Although EC\u2080 remains stable across velocities for individuals, it varies significantly between sports and V\u0307O\u2082max levels, highlighting the need for individualized assessment. Calculating EC\u2080 per athlete may improve energy cost estimations, enhance the metabolic power approach and allow for more accurate analysis of metabolic data based on positional tracking.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0329323","type":"journal-article","created":{"date-parts":[[2025,8,6]],"date-time":"2025-08-06T17:26:12Z","timestamp":1754501172000},"page":"e0329323","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Sport-specific variability in the energy cost of constant speed running: Implications for metabolic power estimations"],"prefix":"10.1371","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0746-9472","authenticated-orcid":true,"given":"Jan","family":"Venzke","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2149-8699","authenticated-orcid":true,"given":"Robin","family":"Sch\u00e4fer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Petra","family":"Platen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"340","published-online":{"date-parts":[[2025,8,6]]},"reference":[{"issue":"11","key":"pone.0329323.ref001","doi-asserted-by":"crossref","first-page":"2135","DOI":"10.1007\/s40279-017-0714-2","article-title":"Training Load Monitoring in Team Sports: A Novel Framework Separating Physiological and Biomechanical Load-Adaptation Pathways","volume":"47","author":"J Vanrenterghem","year":"2017","journal-title":"Sports Med"},{"issue":"14","key":"pone.0329323.ref002","doi-asserted-by":"crossref","first-page":"2809","DOI":"10.1242\/jeb.01700","article-title":"Sprint running: a new energetic approach","volume":"208","author":"PE di Prampero","year":"2005","journal-title":"Journal of Experimental Biology"},{"issue":"1","key":"pone.0329323.ref003","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1249\/MSS.0b013e3181ae5cfd","article-title":"Energy Cost and Metabolic Power in Elite Soccer","volume":"42","author":"C Osgnach","year":"2010","journal-title":"Medicine & Science in Sports & Exercise"},{"issue":"5","key":"pone.0329323.ref004","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1007\/s40279-015-0449-x","article-title":"Gold Standard or Fool\u2019s Gold? 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