Dimundo et al 2022 Sports A Multidisciplinary Investigation into the Talent Development Processes in a RU Academy.pdf (422.46 kB)
A multidisciplinary investigation into the talent development processes in an English Premiership Rugby Union Academy: A preliminary study through an ecological lens
journal contribution
posted on 2022-01-28, 11:30 authored by Francesco Dimundo, Matthew Cole, Richard BlagroveRichard Blagrove, Kevin Till, Adam L Kelly(1) Background: The progression of youth rugby union (RU) players towards senior professional levels can be the result of various different constraints. The aim of this study was to examine characteristics that differentiated playing positions and player rankings in an English Premiership RU academy.
(2) Methods: Thirty players (mean age = 18.5 ± 2.8 years) were divided by playing positions (forwards = 18, backs = 12) and ranked (one to thirty) by coaches based on their potential to achieve senior professional status. Players were analysed across 32 characteristics from eight overreaching factors based on task, environmental, and performer constraints. MANOVA and ANOVA were used to calculate differences among variables in players’ positions (i.e., forwards vs. backs) and ranks (i.e., top 10 vs. bottom 10), with a Welch’s t-test applied to identify individual differences amongst groups and effect sizes calculated.
(3) Results: Large effect sizes were found between groups for socioeconomic, sport activity, anthropometric, physical, and psychological factors. Moreover, environmental and performer constraints differentiated playing positions, whereas task and environmental constraints discriminated player ranks.
(4) Conclusion: Present findings showed that playing positions and player ranks can be distinguished according to specific constraints.
(2) Methods: Thirty players (mean age = 18.5 ± 2.8 years) were divided by playing positions (forwards = 18, backs = 12) and ranked (one to thirty) by coaches based on their potential to achieve senior professional status. Players were analysed across 32 characteristics from eight overreaching factors based on task, environmental, and performer constraints. MANOVA and ANOVA were used to calculate differences among variables in players’ positions (i.e., forwards vs. backs) and ranks (i.e., top 10 vs. bottom 10), with a Welch’s t-test applied to identify individual differences amongst groups and effect sizes calculated.
(3) Results: Large effect sizes were found between groups for socioeconomic, sport activity, anthropometric, physical, and psychological factors. Moreover, environmental and performer constraints differentiated playing positions, whereas task and environmental constraints discriminated player ranks.
(4) Conclusion: Present findings showed that playing positions and player ranks can be distinguished according to specific constraints.
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School
- Sport, Exercise and Health Sciences
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SportsVolume
10Issue
2Publisher
MDPI AGVersion
- VoR (Version of Record)
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© the AuthorsPublisher statement
This is an Open Access Article. It is published by MDPI under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/Acceptance date
2022-01-17Publication date
2022-01-18Copyright date
2022eISSN
2075-4663Publisher version
Language
- en
Depositor
Dr Richard Blagrove. Deposit date: 27 January 2022Article number
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