## 5 Conclusions
### Future Directions  
Building on the present results, future research should prioritize the recruitment of larger, multi-center cohorts of elite athletes to enhance statistical power and allow for rigorous validation of predictive models incorporating FER, AII, and nonlinear classifiers. Longitudinal study designs including extended follow-up periods would help determine the durability of training-induced changes in asymmetry and performance. Additionally, the integration of complementary sensor modalities such as inertial measurement units, muscle oxygenation sensors, or tendon stiffness assessments could provide a more comprehensive characterization of inter-limb functional dynamics. The current findings also advocate for the refinement of asymmetry thresholds through normative modeling or z-score standardization, moving beyond arbitrary cut-offs. Finally, future analytical frameworks should incorporate ensemble and hybrid machine learning models that integrate neuromechanical, psychological, genetic, and contextual data (e.g., fatigue state, seasonal phase, or injury history) to improve the accuracy and applicability of athlete profiling and individualized training optimization.  
Future studies should incorporate objective physiological monitoring (e.g., heart rate, lactate, EMG amplitude) to confirm equivalency of neuromuscular load between intervention groups. Furthermore, integrating continuous predictive models and advanced machine learning approaches (e.g., gradient boosting) may enhance the precision of responder analyses and allow individualized prediction of training adaptations. Finally, longer-term follow-up assessments and systematic injury tracking would be essential to validate the relevance of asymmetry corrections in sports performance and injury prevention contexts.  
**Supplementary Materials:** The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/app15158450/s1](https://www.mdpi.com/article/10.3390/app15158450/s1)]([https://www.mdpi.com/article/10.3390/app15158450/s1](https://www.mdpi.com/article/10.3390/app15158450/s1)), Table S1: Functional Output by Asymmetry Group (Impulse Asymmetry Threshold = 10%) (Mean \(\pm\) SD for Jump Height, RSI, Peak Power, and Active Stiffness).  
**Author Contributions:** Conceptualization, M.G. and A.G.; methodology, A.M. and P.P.; software, K.O.; validation, M.G.; formal analysis, A.M.; investigation, A.G.; resources, K.O.; data curation, K.O.; writing--original draft preparation, A.M.; writing--review and editing, P.P.; visualization, A.G.; supervision, P.P.; project administration, A.M.; funding acquisition, M.G. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research received no external funding.  
**Institutional Review Board Statement:** The study protocol was approved by the Research Ethics Committee for Scientific Research at the Academy of Physical Education in Katowice, Poland (approval number: 3/2021), and conducted in accordance with the Declaration of Helsinki (2013).  
**Informed Consent Statement:** Informed consent was obtained from all subjects involved in the study.  
**Data Availability Statement:** The datasets used and analyzed during the current study are available from the corresponding author upon reasonable request.  
**Conflicts of Interest:** The authors declare no conflict of interest.