Year: 2025 Volume: 27 Issue: b

Abstract:

Injury prevention has become a critical pillar in modern sports science, particularly in high-demand disciplines such as football and running. These sports, despite their biomechanical differences, share a high prevalence of lower limb injuries, which significantly impact athlete health, performance, and career longevity. This article reviews the incidence and types of injuries commonly observed in footballers and runners, emphasizing the need for targeted preventive strategies. Special attention is given to the integration of artificial intelligence (AI) and wearable technologies as innovative tools for monitoring training loads, detecting early signs of injury risk, and personalizing interventions. Evidence from recent studies highlights the effectiveness of machine learning models in predicting non-contact injuries and estimating joint loads through real-time data collection from GPS and biomechanical sensors. The discussion extends to frameworks such as SoccerGuard, which exemplifies AI-driven injury prediction in elite athletes. Ultimately, the article advocates for a unified, data-informed approach to injury prevention, reinforcing the value of technological advancements in safeguarding athlete well-being across both individual & team sports.