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Article

Exploring the Multidimensional Characteristics of Selected and Non-Selected White British and British South Asian Youth Cricketers: An Exploratory Machine Learning Approach

Research for Athlete and Youth Sport Development (RAYSD) Lab, College of Life Sciences, Faculty of Health, Education, and Life Sciences, Birmingham City University, Birmingham B15 3TN, UK
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Youth 2024, 4(2), 718-734; https://doi.org/10.3390/youth4020048
Submission received: 9 April 2024 / Revised: 7 May 2024 / Accepted: 13 May 2024 / Published: 23 May 2024

Abstract

Selection into a County Age Group (CAG; under 10–18) programme is the first step for young aspiring cricketers on their journey to achieving professional status. Recognising that the British South Asian (BSA) community represents 30% of those who play recreational cricket compared to less than 5% of those who are selected to play at the professional level in England and Wales, it is important to better understand the characteristics of selected and non-selected players based on ethnicity to identify potential sociocultural differences during selection. Thus, the purpose of this study was to investigate the multidimensional factors that differentiated between selected and non-selected adolescent male cricketers as well as between White British (WB) and BSA selected players into a CAG programme. A total of 82 male participants aged between 14 and 17 years were included (mean = 15.3 ± 1.1 years: selected n = 33 and non-selected n = 49: WB n = 34, BSA n = 44, Other n = 4). In total, 104 characteristics were measured over nine tests, which were subsequently placed into five overarching factors: (a) physiological and anthropometrical, (b) perceptual–cognitive expertise, (c) psychological, (d) participation history, and (e) socio-cultural influences. A Bayesian binomial regression was performed in rSTAN using a weak normal prior to highlight differentiators in selection as well as differences between WB and BSA selected players. The results highlighted that athleticism, wellbeing and cohesion, the number of older brothers, and being born in birth quarters two and three were positively correlated with player selection into a CAG. Conversely, increases in psychological scores, a greater number of younger brothers and older sisters, as well as antisocial behaviour resulted in a reduced chance of player selection. Finally, several developmental factors (i.e., athleticism, wellbeing and cohesion, psychological distress, and levels of anti-social behaviour) differed based on ethnicity. These exploratory findings serve as a useful opening to highlight there are important differences to consider based on selection and ethnicity in CAG cricket.
Keywords: talent identification; talent development; selection; equality; multidisciplinary talent identification; talent development; selection; equality; multidisciplinary

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MDPI and ACS Style

Brown, T.; Cook, R.; Gough, L.A.; Khawaja, I.; McAuley, A.B.T.; Kelly, A.L. Exploring the Multidimensional Characteristics of Selected and Non-Selected White British and British South Asian Youth Cricketers: An Exploratory Machine Learning Approach. Youth 2024, 4, 718-734. https://doi.org/10.3390/youth4020048

AMA Style

Brown T, Cook R, Gough LA, Khawaja I, McAuley ABT, Kelly AL. Exploring the Multidimensional Characteristics of Selected and Non-Selected White British and British South Asian Youth Cricketers: An Exploratory Machine Learning Approach. Youth. 2024; 4(2):718-734. https://doi.org/10.3390/youth4020048

Chicago/Turabian Style

Brown, Tom, Robert Cook, Lewis A. Gough, Irfan Khawaja, Alexander B. T. McAuley, and Adam L. Kelly. 2024. "Exploring the Multidimensional Characteristics of Selected and Non-Selected White British and British South Asian Youth Cricketers: An Exploratory Machine Learning Approach" Youth 4, no. 2: 718-734. https://doi.org/10.3390/youth4020048

APA Style

Brown, T., Cook, R., Gough, L. A., Khawaja, I., McAuley, A. B. T., & Kelly, A. L. (2024). Exploring the Multidimensional Characteristics of Selected and Non-Selected White British and British South Asian Youth Cricketers: An Exploratory Machine Learning Approach. Youth, 4(2), 718-734. https://doi.org/10.3390/youth4020048

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