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.
Study Type
OBSERVATIONAL
Enrollment
81
Participants will complete lower extremity performance tests including countermovement jump, reactive strength index testing, single-leg performance tests, and agility/change-of-direction assessments. Performance data will be analyzed using artificial intelligence-based methods to explore injury risk patterns.
Istanbul Gelisim University
Istanbul, Turkey (Türkiye)
Countermovement Jump Height
Vertical jump height measured during the countermovement jump (CMJ) test using an artificial intelligence-based performance assessment system.
Time frame: Baseline assessment (single session)
Reactive Strength Index (RSI)
Reactive strength performance calculated from jump height and ground contact time during reactive jump testing.
Time frame: Baseline assessment (single session)
AI-Based Injury Risk Classification Score
Injury risk profile generated using artificial intelligence and machine learning algorithms based on lower extremity performance variables, asymmetry measures, agility performance, and injury history.
Time frame: Baseline assessment (single session)
Single-Leg Hop Performance
Distance and performance outcomes obtained from right and left single-leg hop tests used to evaluate unilateral lower extremity function and limb asymmetry.
Time frame: Baseline assessment (single session)
Time to Complete the T-Test Agility Assessment (seconds)
Time required to complete the standardized T-Test agility assessment. Lower completion times indicate superior agility and change-of-direction ability in young basketball players.
Time frame: Baseline assessment (single session)
Limb Symmetry Index Calculated from Single-Leg Countermovement Jump Height (%)
Limb Symmetry Index (LSI) calculated as the ratio between dominant and non-dominant lower extremity performance during the single-leg countermovement jump test. Values closer to 100% indicate greater inter-limb symmetry.
Time frame: Baseline assessment (single session)
Previous Lower Extremity Injury History
Self-reported history of lower extremity injuries occurring within the previous 12 months.
Time frame: At study enrollment
Countermovement Jump Height Measured by the D-Wall Athlete Performance System (cm)
Countermovement jump height obtained from the D-Wall Athlete Performance System and compared among point guards, shooting guards/small forwards, power forwards, and centers.
Time frame: Baseline
Acceleration and Deceleration Scores Measured by the D-Wall Athlete Performance System (%)
Acceleration and deceleration performance scores generated by the D-Wall Athlete Performance System during athletic performance testing. These scores quantify the athlete's ability to rapidly increase and decrease movement velocity.
Time frame: Baseline
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