The aim of this investigation was to analyse different anthropometrical, physical fitness and training characteristics of young handball players of different categories from a multidimensional perspective, in order to obtain statistically developed reference norms for various testing procedures, and to build multivariate models that could predict performance level at different age periods. 105 handball players with ages between 13-18 years old participated in the study, wich was made choosing the best players of the Galician Handball Federation (Spain). They were grouped into three official categories: 13-14 (U 14´s), 15-16 (U 16´s), and 17-18 (U 18´s). The multidimensional evaluation procedures included: 1) a specific questionnaire to analyse their sport participation background and training status; 2) a complete anthropometrical evaluation, including body composition analysis, somatotyping, and sexual maturation rating; 3) the Eurofit test battery (Council of Europe 1988) to measure general physical fitness; and 4) a vertical jump test battery (SJ, CMJ, and Abalakov). Different multivariate models were developed using discriminant analysis techniques (stepwise selection) to discriminate between players who were selected or not to play. The predictive capacity of the multivariate models developed by discriminant analysis , concluded that more of the 95% of players were accepted when all variables were included. The variables entering the multivariate models with highest predictive value were predominantly those derived from physica fitness and anthropometrical tests. Training levels appeared only at the oldest category group. From these results, we conclude that the best age for talent detection based on this type of multidisciplinary evaluation (sports background and training status questionnaire, anthropometry, and physical fitness comprehensive testing) seems t be 15-16 years of age (U 16´s category).
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