Search results for " Training load"

showing 2 items of 2 documents

Quantifying training intensity distribution in a group of Norwegian professional soccer players.

2011

Purpose:This study was designed to quantify the daily distribution of training intensity in a group of professional soccer players in Norway based on three different methods of training intensity quantification.Methods:Fifteen male athletes (age, 24 ± 5 y) performed treadmill test to exhaustion to determine heart rate and VO2 corresponding to ventilatory thresholds (VT1, VT2), maximal oxygen consumption (VO2max) and maximal heart rate. VT1 and VT2 were used to delineate three intensity zones based on heart rate. During a 4 wk period in the preseason (N = 15), and two separate weeks late in the season (N = 11), all endurance and on-ball training sessions (preseason: N = 378, season: N= 78) w…

AdultMalemedicine.medical_specialtyTime FactorsLactic acid bloodeducationLibrary sciencePhysical Therapy Sports Therapy and RehabilitationNorwegianPerceived exertionYoung AdultOxygen ConsumptionHeart Ratesoccer exercise intensity training zones training load perceived exertionSoccerTask Performance and AnalysismedicineHumansOrthopedics and Sports MedicineLactic AcidTraining loadMuscle SkeletalNorwaylanguage.human_languageTraining intensitylanguagePhysical therapyExercise TestPhysical EnduranceVDP::Medical disciplines: 700::Sports medicine: 850PsychologyPulmonary Ventilationhuman activitiesBiomarkersMuscle ContractionInternational journal of sports physiology and performance
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Association between internal load responses and recovery ability in U19 professional soccer players: A machine learning approach

2023

Background The objective of soccer training load (TL) is enhancing players’ performance while minimizing the possible negative effects induced by fatigue. In this regard, monitoring workloads and recovery is necessary to avoid overload and injuries. Given the controversial results found in literature, this study aims to better understand the complex relationship between internal training load (IL) by using rating of perceived exertion (RPE), recovery, and availability (i.e., subjective players’ readiness status). Methods In this cross-sectional study, twenty-two-professional soccer players (age: 18.5 ± 0.4 years, height: 177 ± 6 cm, weight: 67 ± 6.7 kg) competing in the U19 Italian Champion…

MultidisciplinaryRecoverySoccerMachine learningInjury preventionSport performanceTraining loadSoccer Sport performance Training load Recovery Injury prevention Machine learning
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