## 4 Discussion  
The main objective in the current study was to identify professional/semi-professional football players at high risk for ACL injury based on a classification battery of tests (four \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Group** & **H Strength** & **Q Strength** & **SLTH** & **LESS** \\ \hline Low-risk, N = 4 & 6.74 \(\pm\) 3.65 & 3.99 \(\pm\) 1.41 & 1.71 \(\pm\) 1.28 & 5.83 \(\pm\) 0.34 \\ High-risk N = 16 & 6.74 \(\pm\) 5.53 & 8.47 \(\pm\) 6.42 & 6.09 \(\pm\) 4.49 & 4.69 \(\pm\) 1.21 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The absolute values of percent asymmetry and LESS score for the 4 and 16 misclassified players, in the respective Low-risk and High-risk groups (mean \(\pm\) SD). \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Injury Percentage** & **General** & **Lower Limb** & **Knee** \\ \hline LRG (N = 30) & 57.1\% & 32.1\% & 17.9\% \\ HRG (N = 61) & 65.0\% & 30.0\% & 18.3\% \\ Pearson Chi-Square & 0.50, \(p\) = 0.48 & 0.10, \(p\) = 0.76 & 0.00, \(p\) = 0.96 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The proportion of previous injury among LRG and HRG. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Predictors** & **B** & **S.E.** & **Wald** & **df** & **Sig.** & **Exp (B)** \\ \hline LESS score & 0.93 & 0.22 & 18.54 & 1.00 & 0.00 & 2.52 \\ Prone & \(-\)0.01 & 0.00 & 4.65 & 1.00 & 0.03 & 0.99 \\ Bridge & \(-\)2.91 & 1.15 & 6.42 & 1.00 & 0.01 & 0.06 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Predictors for the categorical “ACL risk” variable (0 = Low risk, 1 = High risk). criteria). The critical values were based on the current consensus for inter-limb asymmetry (10%) and the upper limit of 6 landing errors as proposed for the LESS. Pre-season screening of the professional/semiprofessional football players classified the majority of players in the high-risk group for ACL injury. Only 30 of the 91 athletes met the four criteria and were considered low-risk. Previous injuries which were considered healed, regardless of location, did not interfere with the results, since proportions were very similar between the two risk-prediction groups. This can be explained on the basis that, players with incomplete rehabilitation, recent injuries, or those who failed to perform maximally due to pain or instability, were excluded from the study. Our results are in line with [PERSON] et al. [44], who, based on a battery of tests including hop tests and isometric strength tests, found that 83% of the athletes with ACL reconstruction and 76% of the non-injured athletes failed to pass the criteria for symmetry of \(\leq\)10%. Thus, when formulating either prevention or rehabilitation programs, acceptable functional asymmetry should be considered without being tested, even among competitive athletes. Enough evidence supports the use of a battery of tests for ACL injury risk assessment [16; 17]. Holistic body functionality is also connected to ACL protective mechanisms and all recent prevention programs try to restore correct landing biomechanics [28]. LESS is a tool that assesses the latter, considering trunk mechanics as well [7]. In addition, injury prognostic tools should be easy to perform in any non-laboratory location, without expensive and too-sophisticated equipment, while at the same time maintaining high standards of reliability and external validity. Therefore, we considered that a battery comprising of isometric testing of the major antagonistic thigh muscle groups, a functional test of multiple jumps and a more global-technically oriented test would create a meaningful tool to enhance the ACL injury predictive potential in soccer. The most important predictor variable for risk categorization was the LESS score, followed by the prone bridge test. This finding highlights the importance of a holistic approach during pre-season screening for ACL injury risk. The total LESS score is derived from 17 different scores assessing separate variables of landing technique after a drop jump.