מה צריך לדעת לפני
שתתחיל
מתחיל 4 June 2026 02:59
נגמר 4 June 2026
14 hours 20 minutes
שדרוג אופציונלי זמין
Not Specified
התקדמות בקצב שלך
Paid Course
שדרוג אופציונלי זמין
סקירה כללית
This course introduces the scientific foundations of sports injury causation, workload modelling, and the emerging role of artificial intelligence in injury prevention. Learners will explore how injury mechanisms have evolved from simple monocausal views to multifactorial, dynamic, and systems-based approaches that reflect real athlete complexity.
Through clear explanations and practical football examples, the course covers essential concepts such as intrinsic and extrinsic risk factors, the dynamic recursive model, the workload–injury relationship, and modern systems thinking used in elite performance environments. The second part of the course examines precision workload metrics, including acute:
chronic workload ratios, high-speed running thresholds, acceleration load, sleep quality monitoring, and contextual load management.
Finally, learners discover how AI and machine learning are transforming injury prediction, from multi-modal data integrations to SVM models, decision trees, Bayesian networks, individualised risk profiles, and early-warning systems used in elite clubs. By the end of this course, learners will understand the biological, physiological, and data-driven mechanisms behind injuries, and how modern AI-enhanced monitoring strategies reduce injury risk, optimize performance, and enhance player availability.
סילבוס
- Physiological Characteristics: How Training Shapes Performance and Sets Limits
- Training Load and Injuries: Balancing Load to Enhance Performance and Prevent Injuries
- Injury, Avoid at All Costs: Preventing Injuries Through Smart Strategies
- Etiological Models of Injuries: Understanding Injury Causes to Prevent Them
נלמד על ידי
Marisa Sáenz
נושאים
Science