Internal and External Load Control in Team Sports through a Multivariable Model.
Data related to 141 sessions of 10 semi-professional basketball players were analyzed during the competitive period of the 2018- 2019 season using a multivariable model to determine possible associations between internal and external load variables and fatigue. Age, height, weight, sessional rate of...
| Publicado en: | Journal of Sports Science & Medicine Vol. 20; no. 4; pp. 751 - 759 |
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| Autores principales: | , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Hakan Gur, Journal of Sports Science & Medicine
Dec2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=153181874&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 153181874 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 13032968 FYN jtl: Journal of Sports Science & Medicine issn: 13032968 maglogo: N pubinfo: dt: Dec2021 vid: 20 iid: 4 pid: 26030 pub: Hakan Gur, Journal of Sports Science & Medicine artinfo: ui: 153181874 153181874 153181874 10.52082/jssm.2021.751 153181874 ppf: 751 ppct: 8 formats: fmt: @attributes: type: P tig: atl: Internal and External Load Control in Team Sports through a Multivariable Model. aug: au: Piedra, Aitor Caparrós, Toni Vicens-Bordas, Jordi Peña, Javier affil: National Institute of Physical Education and Sport of Catalonia, University of Barcelona, Barcelona, Spain sug: subj: Muscle Fatigue Models, Theoretical Basketball Athletic Training Weight-Bearing Adult Heart Rate Variability Exertion High-Intensity Interval Training Probability Male Descriptive Statistics Confidence Intervals Odds Ratio Human Adult: 19-44 years Male ab: Data related to 141 sessions of 10 semi-professional basketball players were analyzed during the competitive period of the 2018- 2019 season using a multivariable model to determine possible associations between internal and external load variables and fatigue. Age, height, weight, sessional rate of perceived exertion (sRPE), summated-heart-rate-zones, heart rate variability, total accelerations and decelerations were the covariates, and post-session countermovement jump loss (10% or higher) the response variable. Based on the results observed, a rise in sRPE and accelerations and decelerations could be associated with increased lower-body neuromuscular fatigue. Observing neuromuscular fatigue was 1,008 times higher with each additional sRPE arbitrary unit (AU). Each additional high-intensity effort also increased the probability of significant levels of neuromuscular fatigue by 1,005 times. Fatigue arising from demanding sporting activities is acknowledged as a relevant inciting event leading to injuries. Thus, the methodology used in this study can be used then to monitor neuromuscular fatigue onset, also enhancing proper individual adaptations to training. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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