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Position-Specific Lower Limb Performance and AI-Based Injury Risk Analysis in Young Male Basketball Players
Position-Specific Lower Extremity Performance and Artificial Intelligence-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.
Studie Overzicht
Toestand
Conditie
Interventie / Behandeling
Studietype
Inschrijving (Werkelijk)
Contacten en locaties
Studie Locaties
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Istanbul, Turkije (Türkiye), 34290
- Istanbul Gelisim University
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Deelname Criteria
Geschiktheidscriteria
Leeftijden die in aanmerking komen voor studie
- Kind
- Volwassen
Accepteert gezonde vrijwilligers
Bemonsteringsmethode
Studie Bevolking
Beschrijving
Inclusion Criteria:
- Male basketball players aged 12 to 18 years.
- Registered youth basketball athletes.
- Participation in regular basketball training for at least 1 year.
- Participation in basketball training at least 3 times per week.
- No acute lower extremity injury affecting performance testing within the previous 6 months.
- Ability to understand and follow testing instructions.
- Written informed consent provided by a parent or legal guardian and assent provided by the participant.
Exclusion Criteria:
- Lower extremity surgery within the previous 6 months.
- Acute musculoskeletal injury affecting test performance.
- Neurological, vestibular, or severe orthopedic conditions affecting balance, coordination, or motor performance.
- Pain, illness, fatigue, or any health condition that could affect performance on the assessment day.
- Cardiovascular or systemic conditions preventing completion of the testing protocol.
- Incomplete performance testing data or technically invalid measurements.
Studie plan
Hoe is de studie opgezet?
Ontwerpdetails
Cohorten en interventies
Groep / Cohort |
Interventie / Behandeling |
|---|---|
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Point Guard Players
Young male basketball players whose primary playing position is point guard.
Participants will undergo lower extremity performance assessments and AI-based injury risk analysis.
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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.
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Shooting Guard / Small Forward Players
Young male basketball players whose primary playing position is shooting guard or small forward.
Participants will undergo lower extremity performance assessments and AI-based injury risk analysi
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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.
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Power Forward Players
Young male basketball players whose primary playing position is power forward.
Participants will undergo lower extremity performance assessments and AI-based injury risk analysis.
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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.
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Center Players
Young male basketball players whose primary playing position is center.
Participants will undergo lower extremity performance assessments and AI-based injury risk analysis.
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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.
|
Wat meet het onderzoek?
Primaire uitkomstmaten
Uitkomstmaat |
Maatregel Beschrijving |
Tijdsspanne |
|---|---|---|
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Countermovement Jump Height
Tijdsspanne: Baseline assessment (single session)
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Vertical jump height measured during the countermovement jump (CMJ) test using an artificial intelligence-based performance assessment system.
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Baseline assessment (single session)
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Reactive Strength Index (RSI)
Tijdsspanne: Baseline assessment (single session)
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Reactive strength performance calculated from jump height and ground contact time during reactive jump testing.
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Baseline assessment (single session)
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AI-Based Injury Risk Classification Score
Tijdsspanne: Baseline assessment (single session)
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Injury risk profile generated using artificial intelligence and machine learning algorithms based on lower extremity performance variables, asymmetry measures, agility performance, and injury history.
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Baseline assessment (single session)
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Secundaire uitkomstmaten
Uitkomstmaat |
Maatregel Beschrijving |
Tijdsspanne |
|---|---|---|
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Single-Leg Hop Performance
Tijdsspanne: Baseline assessment (single session)
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Distance and performance outcomes obtained from right and left single-leg hop tests used to evaluate unilateral lower extremity function and limb asymmetry.
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Baseline assessment (single session)
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Time to Complete the T-Test Agility Assessment (seconds)
Tijdsspanne: Baseline assessment (single session)
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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.
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Baseline assessment (single session)
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Limb Symmetry Index Calculated from Single-Leg Countermovement Jump Height (%)
Tijdsspanne: Baseline assessment (single session)
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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.
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Baseline assessment (single session)
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Previous Lower Extremity Injury History
Tijdsspanne: At study enrollment
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Self-reported history of lower extremity injuries occurring within the previous 12 months.
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At study enrollment
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Countermovement Jump Height Measured by the D-Wall Athlete Performance System (cm)
Tijdsspanne: Baseline
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Countermovement jump height obtained from the D-Wall Athlete Performance System and compared among point guards, shooting guards/small forwards, power forwards, and centers.
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Baseline
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Acceleration and Deceleration Scores Measured by the D-Wall Athlete Performance System (%)
Tijdsspanne: Baseline
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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.
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Baseline
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Medewerkers en onderzoekers
Sponsor
Studie record data
Bestudeer belangrijke data
Studie start (Werkelijk)
Primaire voltooiing (Werkelijk)
Studie voltooiing (Werkelijk)
Studieregistratiedata
Eerst ingediend
Eerst ingediend dat voldeed aan de QC-criteria
Eerst geplaatst (Werkelijk)
Updates van studierecords
Laatste update geplaatst (Werkelijk)
Laatste update ingediend die voldeed aan QC-criteria
Laatst geverifieerd
Meer informatie
Termen gerelateerd aan deze studie
Andere studie-ID-nummers
- IGU-SINTECH-BASKET-AI-2026-01
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