Nowadays, optimizing athletic performance in numerous sports mostly depends on biomechanical characterization. Focusing on the cross-sport application of biomechanical concepts in sports including swimming, running, and cycling, this study pays especially attention to injury prevention, performance improvement, and real-time feedback systems. One of the main gaps in current knowledge is the absence of a generalizable framework allowing biomechanical insights from one sport to another. Using universal movement patterns, joint alignments, and muscle activation measures, cross-sport biomechanical profiling fills up this void. In real-time biomechanical data gathering and evaluation, inertial measurement units (IMUs) and artificial intelligence-driven motion tracking systems are very vital tools. By allowing players to maximize characteristics including stride length and cadence across many sports, predictive approaches even more enhance the profiling process. Studies in cycling biomechanics have shown, for example, how saddle height affects knee flexion and power output; similar principles apply to stride mechanics in running and stroke efficiency in swimming. Wearable technology offers real-time technique changes based on constant feedback, hence improving performance. Future directions call for the creation of more generalizable measurements applicable across many sports, the integration of artificial intelligence to offer dynamic, tailored feedback, and longitudinal studies tracking of biomechanical adaptations over time. These developments should make biomechanical optimization more easily available and successful for sportsmen of all levels.