Identifying and developing rugby talent among 10-year-old boys: A practical model

• Published in: Journal of sports sciences Vol. 16; no. 8; pp. 691 - 699
• Main Authors: Pienaar, Anita E., Spamer, Manie J., Steyn Jr, Hendrik S.
• Format: Journal Article
• Language: English
• Published: London Taylor & Francis 01.11.1998; Taylor and Francis
• Subjects: Analysis of Variance; Anthropometry; Aptitude; Biological and medical sciences; Child; Development; Fitness; Football; Fundamental and applied biological sciences. Psychology; Humans; Identification; Male; Models, Theoretical; Motor; Motor Skills; Physical Fitness; Talent; Tests; Vertebrates: body movement. Posture. Locomotion. Flight. Swimming. Physical exercise. Rest. Sports; Human; Competition; Rugby; Growth; Anthropometry; Selection; Aptitude test; Corporal biometry; Athlete; Sport; Physical fitness; Development; Child
• ISSN: 0264-0414; 1466-447X
• DOI: 10.1080/026404198366326

The re-entry of South Africa into the international sporting arena and the resultant need for the identification and development of talent, especially among formerly deprived groups of people, provided the incentive for this study. Its aim was to identify the physical, motor and anthropometric variables that will enable coaches to identify 10-year-old boys, based on their abilities, who could become successful rugby players. Altogether, 173 ten-year-old boys with no rugby experience from a cross-section of the population were selected at random and subjected to 14 physical and motor tests and 14 anthropometric measurements. From 22 schools which participated in the Western Transvaal primary schools under-11 rugby league, the three top teams (n = 45 individuals) were selected and also tested. The results from these three teams were used as the criteria for rugby talent among 10-year-old boys. To establish the best predictors of talent, a stepwise discriminant analysis was conducted: this indicated eight variables (four motor and four anthropometric) that discriminated maximally between the talented and the rest of the players of this age. With classification functions based on these eight variables, 93.8% of all the subjects were classified correctly, indicating good validity. A canonical analysis, based on the selected variables, was then conducted on all the under-11 teams that played in the league in the region (n = 330), and they were ranked according to the scores of the first canonical variable from the most to the least talented. By comparing these results with the players who were chosen for the region's primary schools team, a success rate of 88% in prediction of talent was established. We conclude that this is a successful and practical method to aid the teacher and the coach in selecting and developing talent among 10-year-old rugby players in South Africa.