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<p>This article deals with an application of fuzzy logic on determining the talent identification of pre-pubertal, pubertal and post-pubertal soccer players based on their body composition, physical fitness and physiological variables. A total of 90 male volunteers (age: 10–16&#xa0;years) regularly playing soccer have been included from a football camp held at Salboni, Midnapore District, West Bengal, India. They have been divided into three age groups (i) pre-pubertal (<i>n</i> = 30), (ii) pubertal (<i>n</i> = 30) and (iii) post-pubertal (<i>n</i> = 30). The volunteers have been acclimatized for 15&#xa0;days and selected body composition, physical fitness and physiological variables are measured. Data have been statistically treated with one-way ANOVA followed by multiple-comparison tests and fuzzy logic systems. Results showed that ANOVA predicts which age group showed better values for each selected variables but it fails to predict the ideal value of body composition, physical fitness and physiological variables to be considered in talent identification among each age group because of the variability of the data under different situations. To validate the study, a fuzzy logic system was applied to get a clear motivation over the subject. The fuzzy logic system accurately predicts the variables for talent identification. The fuzzy system gives the highest satisfaction levels beyond the ANOVA test and hence it may be applied to the determination of sports talent identification.</p>

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A study on optimal measure for talent identification in sports performances over various age groups of soccer players using fuzzy logic

  • 期刊论文

  • 发表日期：

    2026年3月22日

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  • Sayan Jyoti Bera,
  • Soumyadip Ghosh,
  • Indranil Manna,
  • Sujit Kumar De

摘要

This article deals with an application of fuzzy logic on determining the talent identification of pre-pubertal, pubertal and post-pubertal soccer players based on their body composition, physical fitness and physiological variables. A total of 90 male volunteers (age: 10–16 years) regularly playing soccer have been included from a football camp held at Salboni, Midnapore District, West Bengal, India. They have been divided into three age groups (i) pre-pubertal (n = 30), (ii) pubertal (n = 30) and (iii) post-pubertal (n = 30). The volunteers have been acclimatized for 15 days and selected body composition, physical fitness and physiological variables are measured. Data have been statistically treated with one-way ANOVA followed by multiple-comparison tests and fuzzy logic systems. Results showed that ANOVA predicts which age group showed better values for each selected variables but it fails to predict the ideal value of body composition, physical fitness and physiological variables to be considered in talent identification among each age group because of the variability of the data under different situations. To validate the study, a fuzzy logic system was applied to get a clear motivation over the subject. The fuzzy logic system accurately predicts the variables for talent identification. The fuzzy system gives the highest satisfaction levels beyond the ANOVA test and hence it may be applied to the determination of sports talent identification.