Clinical Research Directory

Association Between Pre-Season Physical Capacity and Injury Risk in Professional Soccer Players

This prospective observational study aims to investigate the relationship between pre-season physical capacities and lower-extremity injury risk during the competitive season in professional male soccer players. A total of 28 healthy professional male soccer players aged 18-35 years, with at least five years of training experience, will be included in the study. Participants will undergo comprehensive physical performance assessments during the pre-season period without being assigned to any experimental intervention or additional exercise program. Baseline assessments will include anthropometric measurements, countermovement jump (CMJ) performance, overhead squat assessment, aerobic fitness using the 30-15 Intermittent Fitness Test (30-15 IFT), eccentric hamstring strength using the NordBord system, and hip abduction and adduction strength using the GroinBar system. Inter-limb strength asymmetries will also be evaluated. Following the pre-season assessments, participants will be monitored for lower-extremity injuries during the competitive season. Injury information, including anatomical location, injury type, duration, and recurrence, will be collected from club physiotherapists and coaching staff. The primary objective is to examine whether pre-season physical performance characteristics, particularly hamstring strength, hip muscle strength, and inter-limb strength differences, are associated with subsequent lower-extremity injury occurrence. The findings may contribute to a better understanding of the relationship between pre-season physical capacity and injury risk in professional soccer and may help sports medicine professionals, physiotherapists, and strength and conditioning coaches identify relevant physical performance indicators for athlete monitoring.

Position-Specific Lower Limb Performance and AI-Based Injury Risk Analysis in Young Male Basketball Players

This observational study aims to evaluate lower extremity performance characteristics in young male basketball players according to their playing positions and to explore injury risk patterns using artificial intelligence (AI)-based analysis. Basketball requires frequent jumping, sprinting, rapid changes of direction, acceleration, deceleration, and single-leg movements, all of which place significant demands on lower extremity function. Participants will undergo a single assessment session including anthropometric measurements and performance tests such as countermovement jump, reactive strength testing, single-leg performance tests, and agility assessments. Information regarding previous lower extremity injuries, training history, and playing position will also be collected. The study will compare performance characteristics among different basketball positions, including guards, forwards, and centers. In addition, AI and machine learning techniques will be used to analyze the collected performance data and identify patterns associated with injury risk. The purpose of the AI analysis is not to diagnose injuries but to investigate whether combinations of performance variables can help identify athletes who may demonstrate higher-risk movement or performance profiles. The findings may contribute to the development of position-specific training strategies, individualized performance monitoring, and evidence-based injury prevention approaches in youth basketball players.