Early Detection of Injury, Illness, and Performance Decline in Elite Athletes
Sports & Leisure
Background
Future Of Health is a dynamic collective of senior leaders from top health organizations worldwide. Harnessing the shared vision and collective expertise of its members, FOH aims to influence, transform, and shape the future of health.
Challenge
In professional sports, a decline in performance, the onset of illness, or a developing injury is often identified only after clear symptoms appear: pain, reduced functional capacity, fatigue, or absence from training and competition. By the time these warning signs become visible, the athlete may already be facing lost training time, impaired recovery, lower performance, and increased medical and financial burden for the team and support system. This challenge is focused on athletes for whom sport is their primary occupation, including elite, professional, and high-performance players who operate under continuous physical and mental demands. These individuals are expected to maintain peak readiness while coping with intense training loads, travel, competition stress, and limited recovery windows. In such environments, even small undetected changes in physiology, biomechanics, sleep, workload tolerance, or mental state can quickly develop into meaningful setbacks. The opportunity is to move from reactive care to early identification and proactive intervention. We are seeking approaches that can help detect subtle signals of decline, illness risk, or injury risk before they become clinically or functionally significant. Solutions may draw on data, monitoring tools, predictive models, integrated assessments, or new methods for translating complex information into practical decisions for athletes, coaches, and medical teams. This is important not only for protecting athlete health and career longevity, but also for improving consistency, resilience, and performance outcomes. A successful solution should support earlier action, reduce avoidable downtime, and enable a more precise, personalized, and preventive model of care in high-performance sport.פתרונות מישראל בלבד
Required Expertise
Sports medicine, Exercise physiology, Biomechanics, Data science and predictive analytics, Cloud computing and data engineering, Wearable and sensor technology, Performance and recovery science, Clinical informatics and decision support
Challenge Objectives
• Meaningful injury, illness, and performance-risk signals are identified at least 50% faster than current practice, measured by the interval between first detectable change and staff intervention. • Non-contact injury incidence, illness-related absences, and unplanned training interruptions decrease by 20% year over year, measured per athlete exposure hours and missed sessions. • Total athlete downtime from preventable issues falls by 25% across a season, measured as days lost to injury, illness, or unexplained performance decline. • At least 85% of flagged athletes return to baseline performance or training tolerance within 14 days, measured against individualized benchmarks for readiness and functional capacity. • Proactive decision-making becomes routine, with risk status reviewed before 95% of training and competition decisions and documented action plans completed within 24 hours for 90% of high-risk cases. • Preventive care is consistently adopted, with at least 90% athlete monitoring adherence and 80% coach and medical staff use of risk insights in weekly planning workflows. • Organization-wide resilience improves, demonstrated by a 15% increase in athlete availability for selection and a 20% reduction in recurrent issues within the same season.
Incentives
• Non-cash support could include access to anonymized monitoring datasets, pilot environments with elite performance staff, expert feedback, and potential co-development of decision-support workflows for broader deployment.
