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      Changes in physical demands between game quarters of U18 elite official basketball games

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          Abstract

          Purpose

          The aim of this study was to describe the physical demands during U18 elite basketball games according to the game quarter and to identify a smaller subset of variables and threshold scores that distinguish players’ physical performance in each quarter.

          Methods

          Data was collected from ninety-four players who participated in the study (age: 17.4 ± 0.74 years; height: 199.0 ± 0.1 cm; body mass: 87.1 ± 13.1 kg) competing in the Euroleague Basketball Next Generation Tournament. Players’ movements during the games were measured using a portable local positioning system (LPS) (WIMU PRO®, Realtrack Systems SL, Almería, Spain) and included relative distance (total distance / playing duration), relative distance in established speed zones, high-intensity running (18.1–24.0 km·h-1) and sprinting (> 24.1 km·h -1). player load, peak speed (km·h -1) and peak acceleration (m·s -2) number of total accelerations and total decelerations, high intensity accelerations (> 2 m·s -2) and decelerations (< -2 m·s -2).

          Results

          There was an overall decrease in distance covered, player load, number of high intensity accelerations and decelerations between the first and last quarter of the games in all playing positions. A classification tree analysis showed that the first quarter had much influence of distance covered (above 69.0 meters), distance covered <6.0 km·h -1 and accelerations (> 2 m·s -2), whereas the fourth quarter performance had much influence of distance covered (below 69.0) and distance covered 12.1–18.0 km·h -1.

          Conclusions

          A significant reduction in physical demands occurs during basketball, especially between first and last quarter for players in all playing positions during basketball games of under 18 elite players.

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          Most cited references26

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          Time-motion analysis and physiological data of elite under-19-year-old basketball players during competition.

          The physical demands of modern basketball were assessed by investigating 38 elite under-19-year-old basketball players during competition. Computerised time-motion analyses were performed on 18 players of various positions. Heart rate was recorded continuously for all subjects. Blood was sampled before the start of each match, at half time and at full time to determine lactate concentration. Players spent 8.8% (1%), 5.3% (0.8%) and 2.1% (0.3%) of live time in high "specific movements", sprinting and jumping, respectively. Centres spent significantly lower live time competing in high-intensity activities than guards (14.7% (1%) v 17.1% (1.2%); p<0.01) and forwards (16.6% (0.8%); p<0.05). The mean (SD) heart rate during total time was 171 (4) beats/min, with a significant difference (p<0.01) between guards and centres. Mean (SD) plasma lactate concentration was 5.49 (1.24) mmol/l, with concentrations at half time (6.05 (1.27) mmol/l) being significantly (p<0.001) higher than those at full time (4.94 (1.46) mmol/l). The changes to the rules of basketball have slightly increased the cardiac efforts involved during competition. The game intensity may differ according to the playing position, being greatest in guards.
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            The physiological load imposed on basketball players during competition.

            In this study, the intensities of activity and movement patterns during men's basketball were investigated by videoing the movements and monitoring the heart rate and blood lactate responses of eight elite players during competition. The results are expressed according to 'live time', which is actual playing time, and 'total time', which includes live time as well as all stoppages in play. The mean (+/- S.D.) frequency of all activities was 997 +/- 183, with a change in movement category every 2.0 s. A mean total of 105 +/- 52 high-intensity runs (mean duration 1.7 s) was recorded for each game, resulting in one high-intensity run every 21 s during live time. Sixty percent of live time was spent engaged in low-intensity activity, while 15% was spent in high-intensity activity. The mean heart rate (HR) during live time was 169 +/- 9 beats min-1 (89 +/- 2% peak HR attained during laboratory testing); 75% of live time was spent with a HR response of greater than 85% peak HR. The mean blood lactate concentration was 6.8 +/- 2.8 mM, indicating the involvement of glycolysis in the energy demands of basketball. It is concluded that the physiological requirements of men's basketball are high, placing considerable demands on the cardiovascular and metabolic capacities of players.
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              The Activity Demands and Physiological Responses Encountered During Basketball Match-Play: A Systematic Review

              Basketball is a popular, court-based team sport that has been extensively studied over the last decade.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: SupervisionRole: ValidationRole: VisualizationRole: Writing – review & editing
                Role: MethodologyRole: Supervision
                Role: Data curationRole: Methodology
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                3 September 2019
                2019
                : 14
                : 9
                : e0221818
                Affiliations
                [1 ] Sport Performance Department, FC Barcelona Sports, Barcelona, Spain
                [2 ] National Institute of Physical Education of Catalonia (INEFC), Barcelona, Spain
                [3 ] Unió Esportiva Santboiana, DH Rugby, Sant Boi de Llobregat, Barcelona, Spain
                [4 ] Institute for Sport, Physical Activity and Leisure, Leeds Beckett University, Leeds, United Kingdom
                [5 ] Yorkshire Carnegie Rugby Club, Headingley Carnegie Stadium, Leeds, United Kingdom
                [6 ] Leeds Rhinos Rugby Club, Headingley Carnegie Stadium, Leeds, United Kingdom
                [7 ] England Performance Unit, The Rugby Football League, Leeds, United Kingdom
                [8 ] School of Science and Technology, University of New England, Armidale, NSW, Australia
                [9 ] Division of Exercise Science and Sports Medicine, Department of Human Biology, Faculty of Health Sciences, the University of Cape Town and the Sports Science Institute of South Africa, Cape Town, South Africa
                [10 ] Research Center in Sport Sciences, Health and Human Development (CIDESD), CreativeLab Research Community, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal
                Universidade Federal de Juiz de Fora, BRAZIL
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-1376-6593
                http://orcid.org/0000-0003-3232-1178
                http://orcid.org/0000-0003-2335-9991
                Article
                PONE-D-19-08852
                10.1371/journal.pone.0221818
                6720027
                31479464
                461666d5-c248-4494-8ed4-7ad85de6b247
                © 2019 Vázquez-Guerrero et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 28 March 2019
                : 15 August 2019
                Page count
                Figures: 3, Tables: 1, Pages: 14
                Funding
                Bruno Fernández-Valdés is the recipient of a predoctoral fellowship from the Ministry of Education, Culture and Sport (FPU15/03235). Jaime Sampaio is financed by project NanoSTIMA - Macro-to-Nano Human Sensing: Towards Integrated Multimodal Health Monitoring and Analytics from operation NORTE 01 0145 FEDER 000016, co-financed by Fundo de Desenvolvimento Europeu através de NORTE 2020 (Programa Operacional Regional do Norte 2014/2020). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Psychology
                Behavior
                Recreation
                Games
                Social Sciences
                Psychology
                Behavior
                Recreation
                Games
                Biology and Life Sciences
                Psychology
                Behavior
                Recreation
                Sports
                Social Sciences
                Psychology
                Behavior
                Recreation
                Sports
                Biology and Life Sciences
                Sports Science
                Sports
                Physical Sciences
                Physics
                Classical Mechanics
                Acceleration
                Biology and Life Sciences
                Physiology
                Biological Locomotion
                Running
                Medicine and Health Sciences
                Physiology
                Biological Locomotion
                Running
                Physical Sciences
                Physics
                Classical Mechanics
                Deceleration
                Engineering and Technology
                Management Engineering
                Decision Analysis
                Decision Trees
                Research and Analysis Methods
                Decision Analysis
                Decision Trees
                Engineering and Technology
                Electronics
                Accelerometers
                Engineering and Technology
                Navigation
                Global Positioning System
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                All relevant data are within the manuscript and its Supporting Information files.

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