## 3 Results  
Demographic characteristics of the athletes are presented in Table 1. A correlation matrix was computed among all the collected variables. As explained above, the LESS and abductors strength for dominant lower limb analysis, and the LESS, hamstring strength, and hamstring strength (brake test) along with Biering-Sorensen test for non-dominant lower limb analysis were not included in the EFA. The KMO values were 0.647 for the dominant lower limb and 0.621 for the non-dominant lower limb, confirming the factorability of the data. For the dominant lower limb, the correlation matrix resulted in six factors, explaining 79.04% of the variance (Table 2). The first factor (F1) accounted for 22.5% of the total variance in the datasets. The results showed that factor 1 (F1) was positively correlated with prone bridge, side bridge, side bridge, and Biering-Sorensen; this first component could be named \"core stability\". The second factor (F2), which accounted for 21.63% of the total variance, showed a positive correlation with peak VGRF and RDF; this component could be defined as \"force attenuation\". The third factor (F3) represented 10.52% of the total variance. The D3 was positively correlated with total COP length, COP SDx, and COP Sdy; this component could be referred to as \"dynamic balance\". The fourth factor (F4) accounted for 10.17% of the total variance, showing a positive correlation with isometric hamstring strength and the hamstrings brake test. This factor could be named \"hamstring strength\". The fifth factor (F5) represented 8.43% and was positively correlated with Q-H EMG ratio pre-landing and Q-H EMG ratio post-landing. This factor could be referred to as \"Q-H EMG ratio\". Finally, the sixth factor (F6) accounted for 5.77% of the total variance and was positively correlated with quadriceps strength and triple hop. This factor could be named \"quadriceps performance\". \begin{table}
\begin{tabular}{c c} \hline \hline  & **Mean \(\pm\) SD** \\ \hline Age & 21.32 \(\pm\) 4.54 \\ Weight & 74.64 \(\pm\) 8.03 \\ Height & 178.75 \(\pm\) 6.42 \\ BMI & 23.33 \(\pm\) 1.83 \\ Football starting age & 7.40 \(\pm\) 2.66 \\ Years at professional level & 3.27 \(\pm\) 3.49 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Athletes’ demographics characteristics. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & **F1 (22.5\%) Core** & **F2 (21.63\%)** & **F3 (10.52\%)** & **F4 (10.17\%)** & **F5 (8.43\%)** & **F6 (5.77\%)** \\
**Stability** & **GRF** & **Dynamic Balance** & **Hamstrings** & **Q-H EMG** & **Quadriceps** \\  & & & & **Strength** & **Ratio** & **Performance** \\ \hline Q-H EMG ratio pre-landing & & & & 0.844 \\ \hline Q-H EMG ratio post-landing & & & & 0.936 \\ \hline Hamstrings isometric (brake) & & & 0.884 & \\ \hline Hamstrings isometric & & & 0.866 & & \\ \hline Quadriceps isometric & & & & 0.871 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Pattern matrix with factors and measured items for the dominant lower limb. Abbreviations: F: factors, Q–H EMG: quadriceps-hamstrings electromyography, THD: triple hop for distance, D: dominant, ND: non-dominant, VGRF: vertical ground reaction forces, COP SD: center of pressure standard deviation, RDF: rate of force development. For non-dominant lower limb, the correlation matrix resulted in five factors, explaining 76.60% of the variance (Table 3). The first factor accounted for 22.19% of the total variance in the datasets. The results indicated that factor 1 (F1) was positively correlated with prone bridge and dominant side bridge, non-dominant side bridge, and triple hop: thus, this first factor could be named \"core stability\". The second factor (F2) represented 20.35% of the total variance and was positively correlated with COP length, COP SDx, and COP SDy. Thus, this factor could be named \"dynamic balance\". The third factor (F3) accounted for 13.78% of the total variance and was positively correlated with VGRF and RDF. F3 could be referred to as \"force attenuation\".