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      The effect of bio-banding on the anthropometric, physical fitness and functional movement characteristics of academy soccer players

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          Abstract

          The study examined if maturity status bio-banding reduces within-group variance in anthropometric, physical fitness and functional movement characteristics of 319, under-14 and under-15 players from 19 UK professional soccer academies. Bio-banding reduced the within-bio-banded group variance for anthropometric values, when compared to an aggregated chronological banded group (chronological: 5.1–16.7%CV; bio-banded: 3.0–17.3%CV). Differences between these bio-banded groups ranged from moderate to very large (ES = 0.97 to 2.88). Physical performance variance (chronological: 4.8–24.9%CV; bio-banded: 3.8–26.5%CV) was also reduced with bio-banding compared to chronological aged grouping. However, not to the same extent as anthropometric values with only 68.3% of values reduced across banding methods compared to 92.6% for anthropometric data. Differences between the bio-banded groups physical qualities ranged from trivial to very large (ES = 0.00 to 3.00). The number of functional movement metrics and %CV reduced by bio-banding was lowest within the ‘circa-PHV’ groups (11.1–44.4%). The proportion of players achieving the threshold value score of ≥ 14 for the FMS™ was highest within the ‘post-PHV’ group (50.0–53.7%). The use of maturity status bio-banding can create more homogenous groups which may encourage greater competitive equity. However, findings here support a bio-banding maturity effect hypothesis, whereby maturity status bio-banding has a heightened effect on controlling for characteristics which have a stronger association to biological growth.

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          Progressive statistics for studies in sports medicine and exercise science.

          Statistical guidelines and expert statements are now available to assist in the analysis and reporting of studies in some biomedical disciplines. We present here a more progressive resource for sample-based studies, meta-analyses, and case studies in sports medicine and exercise science. We offer forthright advice on the following controversial or novel issues: using precision of estimation for inferences about population effects in preference to null-hypothesis testing, which is inadequate for assessing clinical or practical importance; justifying sample size via acceptable precision or confidence for clinical decisions rather than via adequate power for statistical significance; showing SD rather than SEM, to better communicate the magnitude of differences in means and nonuniformity of error; avoiding purely nonparametric analyses, which cannot provide inferences about magnitude and are unnecessary; using regression statistics in validity studies, in preference to the impractical and biased limits of agreement; making greater use of qualitative methods to enrich sample-based quantitative projects; and seeking ethics approval for public access to the depersonalized raw data of a study, to address the need for more scrutiny of research and better meta-analyses. Advice on less contentious issues includes the following: using covariates in linear models to adjust for confounders, to account for individual differences, and to identify potential mechanisms of an effect; using log transformation to deal with nonuniformity of effects and error; identifying and deleting outliers; presenting descriptive, effect, and inferential statistics in appropriate formats; and contending with bias arising from problems with sampling, assignment, blinding, measurement error, and researchers' prejudices. This article should advance the field by stimulating debate, promoting innovative approaches, and serving as a useful checklist for authors, reviewers, and editors.
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            An assessment of maturity from anthropometric measurements.

            The range of variability between individuals of the same chronological age (CA) in somatic and biological maturity is large and especially accentuated around the adolescent growth spurt. Maturity assessment is an important consideration when dealing with adolescents, from both a research perspective and youth sports stratification. A noninvasive, practical method predicting years from peak height velocity (a maturity offset value) by using anthropometric variables is developed in one sample and cross-validated in two different samples. Gender specific multiple regression equations were calculated on a sample of 152 Canadian children aged 8-16 yr (79 boys; 73 girls) who were followed through adolescence from 1991 to 1997. The equations included three somatic dimensions (height, sitting height, and leg length), CA, and their interactions. The equations were cross-validated on a combined sample of Canadian (71 boys, 40 girls measured from 1964 through 1973) and Flemish children (50 boys, 48 girls measured from 1985 through 1999). The coefficient of determination (R2) for the boys' model was 0.92 and for the girls' model 0.91; the SEEs were 0.49 and 0.50, respectively. Mean difference between actual and predicted maturity offset for the verification samples was 0.24 (SD 0.65) yr in boys and 0.001 (SD 0.68) yr in girls. Although the cross-validation meets statistical standards for acceptance, caution is warranted with regard to implementation. It is recommended that maturity offset be considered as a categorical rather than a continuous assessment. Nevertheless, the equations presented are a reliable, noninvasive and a practical solution for the measure of biological maturity for matching adolescent athletes
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              The relationship between peak height velocity and physical performance in youth soccer players.

              Longitudinal changes in height, weight and physical performance were studied in 33 Flemish male youth soccer players from the Ghent Youth Soccer Project. The players' ages at the start of the study ranged from 10.4 to 13.7 years, with a mean age of 12.2 +/- 0.7 years. Longitudinal changes were studied over a 5 year period. Peak height velocity and peak weight velocity were determined using non-smoothed polynomials. The estimations of peak height velocity, peak weight velocity and age at peak height velocity were 9.7 +/- 1.5 cm x year-1, 8.4 +/- 3.0 kg x year-1 and 13.8 +/- 0.8 years, respectively. Peak weight velocity occurred, on average, at the same age as peak height velocity. Balance, speed of limb movement, trunk strength, upper-body muscular endurance, explosive strength, running speed and agility, cardiorespiratory endurance and anaerobic capacity showed peak development at peak height velocity. A plateau in the velocity curves was observed after peak height velocity for upper-body muscular endurance, explosive strength and running speed. Flexibility exhibited peak development during the tear after peak height velocity. Trainers and coaches should be aware of the individual characteristics of the adolescent growth spurt and the training load should also be individualized at this time.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Formal analysisRole: InvestigationRole: MethodologyRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: MethodologyRole: Writing – review & editing
                Role: MethodologyRole: Resources
                Role: Formal analysisRole: MethodologyRole: Writing – original draftRole: Writing – review & editing
                Role: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: Project administrationRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                29 November 2021
                2021
                : 16
                : 11
                : e0260136
                Affiliations
                [1 ] School of Sport and Exercise Science, University of Birmingham, Birmingham, United Kingdom
                [2 ] The English Football Association, St Georges Park, Burton Upton Trent, Staffordshire, United Kingdom
                [3 ] School of Health and Science, Teesside University, Middlesbrough, Yorkshire, United Kingdom
                [4 ] Pro Football Support, Huddersfield, Yorkshire, United Kingdom
                [5 ] Department for Health, University of Bath, Bath, Somerset, United Kingdom
                [6 ] Department of Sport, Health and Exercise Science, University of Hull, Yorkshire, United Kingdom
                Universita degli Studi di Milano, ITALY
                Author notes

                Competing Interests: We acknowledge that the author GP was employed by the company who led the collection of the testing battery. Despite this, and to remove the potential for bias, this author was not involved in formation of the research questions, statistical analyses or data interpretation conducted during the investigation. In addition, the company in which the author GP is affiliated to, did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of the author are articulated in the ‘author contributions’ section. Lastly, the commercial affiliate of GP does not alter our adherence to PLOS ONE policies on sharing data and material and the company this author is affiliated to did not fund the study.

                Author information
                https://orcid.org/0000-0002-1580-3792
                Article
                PONE-D-21-15171
                10.1371/journal.pone.0260136
                8629286
                34843528
                a7dc55c0-2493-4601-8023-ffcec5286ee3
                © 2021 MacMaster 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
                : 11 May 2021
                : 4 November 2021
                Page count
                Figures: 2, Tables: 4, Pages: 16
                Funding
                The author(s) received no specific funding for this work.
                Categories
                Research Article
                Biology and Life Sciences
                Anatomy
                Anthropometry
                Medicine and Health Sciences
                Anatomy
                Anthropometry
                Medicine and Health Sciences
                Public and Occupational Health
                Physical Activity
                Physical Fitness
                Biology and Life Sciences
                Psychology
                Behavior
                Recreation
                Sports
                Social Sciences
                Psychology
                Behavior
                Recreation
                Sports
                Biology and Life Sciences
                Sports Science
                Sports
                Biology and Life Sciences
                Biomechanics
                Musculoskeletal Mechanics
                Biology and Life Sciences
                Physiology
                Muscle Physiology
                Musculoskeletal Mechanics
                Engineering and Technology
                Measurement
                Time Measurement
                People and Places
                Population Groupings
                Age Groups
                Physical Sciences
                Physics
                Classical Mechanics
                Motion
                Velocity
                Medicine and Health Sciences
                Epidemiology
                Medical Risk Factors
                Custom metadata
                All raw files are available from the University of Hull database ( https://hull-repository.worktribe.com/output/3763127).

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