## 3 Results  
The results of the Spearman correlation analysis among chronological age, training age, anthropometric variables, and motor performance parameters are presented in Table 2.  
As presented in Table 2, chronological age was strongly positively correlated with training age (r = 0.819, \(p\) = 0.0057) and moderately correlated with height (r = 0.474, \(p\) = 0.009), body weight (r = 0.434, \(p\) = 0.018), vertical jump (r = 0.519, \(p\) = 0.003), agility time (r = 0.476, \(p\) = 0.008), and 30 m sprint time (r = 0.526, \(p\) = 0.003). A low positive correlation was observed between age and BMI (r = 0.211, \(p\) = 0.271). Training age showed moderate positive correlations with vertical jump (r = 0.465, \(p\) = 0.010) and agility time (r = 0.439, \(p\) = 0.016) and low correlations with height (r = 0.244, \(p\) = 0.200), body weight (r = 0.315, \(p\) = 0.095), BMI (r = 0.245, \(p\) = 0.198), and sprint time (r = 0.283, \(p\) = 0.136). Height was strongly correlated with body weight (r = 0.657, \(p\) = 0.072), while its correlations with BMI (r = 0.189, \(p\) = 0.323), vertical jump (r = 0.066, \(p\) = 0.731), agility (r = 0.208, \(p\) = 0.277), and sprint time (r = 0.438, \(p\) = 0.017) ranged from low to moderate. Body weight exhibited a strong correlation with BMI (r = 0.832, \(p\) = 0.022) and low correlations with vertical jump (r = 0.210, \(p\) = 0.274), agility time (r = 0.165, \(p\) = 0.389), and sprint time (r = 0.324, \(p\) = 0.085). Similarly, BMI showed low positive correlations with all three motor performance variables: vertical jump (r = 0.222, \(p\) = 0.246), agility (r = 0.148, \(p\) = 0.440), and sprint (r = 0.162, \(p\) = 0.399). Vertical jump and agility time were weakly correlated (r = 0.351, \(p\) = 0.061), while the correlation between vertical jump and sprint time was negative but negligible (r = \(-\)0.012, \(p\) = 0.947). Agility time and 30 m sprint time were weakly positively correlated (r = 0.233, \(p\) = 0.222). All correlations are visually represented in the heatmap provided in Figure 2. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & **Age (years)** & \begin{tabular}{c} **Training Age** \\ **(years)** \\ \end{tabular} & **Height (cm)** & \begin{tabular}{c} **Body Weight** \\ **(kg)** \\ \end{tabular} & **BMI (kg/m\({}^{2}\))** & \begin{tabular}{c} **Vertical** \\ **Jump (cm)** \\ \end{tabular} & **Agility (s)** \\ \hline \
\begin{tabular}{c} Training Age \\ (years) \\ \end{tabular} & 0.819 ** & & & & & & \\ \hline
\begin{tabular}{c} Height (cm) \\ \end{tabular} & 0.474 ** & 0.244 & & & & & \\ \hline Body Weight (kg) & 0.434 * & 0.315 & 0.657 & & & & \\ \hline BMI (kg/m\({}^{2}\)) & 0.211 & 0.245 & 0.189 & 0.832 * & & & \\ \hline Vertical Jump & 0.519 ** & 0.465 * & 0.066 & 0.210 & 0.222 & & \\ \hline Agility (s) & 0.476 ** & 0.439 * & 0.208 & 0.165 & 0.148 & 0.351 & \\ \hline Thirty-Meter & 0.526 ** & 0.283 & 0.438 * & 0.324 & 0.162 & \(-\)0.012 & 0.233 \\ \hline \hline \end{tabular}  
* \({}^{*}p\) \(<\) 0.05, **\(p\) \(<\) 0.01.  
\end{table} 
Table 2: Spearman correlation analysis results. Figure 2: Correlation heatmap. The color scale in Figure 2 represents correlation coefficients ranging from \(-1\) to \(+1\). Dark blue areas indicate strong positive correlations between variables, while light blue areas represent weaker positive relationships. Multiple linear regression analyses were conducted to predict performance outcomes in speed, agility, and jumping. Separate regression models were constructed for each dependent variable, with height and body mass index (BMI) included as predictor variables (Table 3). Although body weight was initially considered for inclusion in the models, it was excluded due to multicollinearity issues (Table 4). As shown in Table 3, the results of the regression analysis for the speed variable indicated that the model approached statistical significance (F(2, 26) = 3.158, \(p\) = 0.059). The model explained 19.5% of the variance in speed (R\({}^{2}\) = 0.195, adjusted R\({}^{2}\) = 0.134).