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DOI 10.1080/02701367.2024.2358962

Медицинская библиотека · Research quarterly for exercise and sport · 2024

School-Age Talent Identification in Female Handball by a Mathematical Model: Equation Proposed from Anthropometry, Maturity Offset, Fitness and Technical Field-Tests.

Caporal Guilherme, Gaya Adroaldo C A, Pedretti Augusto, Mello Júlio B

СтатьяПоддержка исследования: вне правительства СШАПеревод пока не подготовлен

Аннотация

The present study aimed to identify parameters that best discriminate between high-level and scholar-level players for the Brazilian 13-14-year-old girl's handball and propose a mathematical model to identify sports talent for handball. The sample was made up of all available handball players comprising these two groups: 100 girls who participated in the high-level handball championship in Brazil and 53 girls (age 13-14 years) as finalists of the school-level games in one region of Brazil. We assess the anthropometric profile, maturity offset, physical fitness, and technical skills for handball. To propose the equation, the Discriminant Function Analysis method was used. The discriminant function was significant (p ≤ .05), had a good canonical correlation (0.590), and still had an average Wilk Lambda (0.652). The variables considered in the talent identification model included: 1. flexibility, 2. abdominal strength, 3. lower limbs muscle power, 4. agility, 5. defensive movement and 6. slalom with ball. The values from the equation for identifying school-age athletes with high motor skills and performance for handball can be classified by a cutoff point (Y = 0.192). The results showed that the mathematical-model obtained was able to select school-age athletes with high motor skills for handball, and with the profile for participation in high-level championships.

Для цитирования: Caporal Guilherme, Gaya Adroaldo C A, Pedretti Augusto, Mello Júlio B. School-Age Talent Identification in Female Handball by a Mathematical Model: Equation Proposed from Anthropometry, Maturity Offset, Fitness and Technical Field-Tests.. Research quarterly for exercise and sport. 2024. DOI: 10.1080/02701367.2024.2358962.

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