Development of talent identification model for cricket in Nepal

Abstract

Present study was stated as Development of talent identification Model for Cricket in Nepal , which would be more comprehensive and scientific in approach and focused on the developing a talent identification model in cricket. The study was conducted on 200 Nepalese youth male cricket players of mean age 15.87±1.31 years and 2 years of playing experience, selected from different renowned sports academies of the country (Nepal). To accomplish the main objective of the study i.e. to develop a model to identify the talent in cricket, factor analysis was applied. The developed model was tested for reliability using Cronbach s alpha, Spearman brown coefficient and Guttman split half reliability coefficient. Application of factor analysis on different anthropometrical variables and as evident from scree plot in figure 4.2.1 revealed that three factors were having eigenvalue more than one, after which the curve started flattening sharply. Different bio-motor variables were too subjected to the factor analysis and revealed that four factors were having eigenvalue more than one, evident from figure 4.3.1. Application of factor analysis, on physiological variables and as evident from scree plot in figure 4.4.1, revealed that two factors could be extracted. The thorough application of factor analysis on game skill variable suggested that two variables, batting towards target and bowling in line and length would be extracted. Factor analysis on multidimensional factors suggested eight factors named as anthropometrics, skeletal diameter, core strength, aerobic power, game skill, leg strength and flexibility could be extracted. Investigator had further calculated internal consistency, using Cronbach s alpha coefficient and finally suggested 7 variables multidimensional talent identification criteria in cricket. Application of factor analysis on finally selected seven variables and was presented in table 4.8.2 revealed that the developed talent identification model explained 77.139% of the total variance in defining the talent