About Dataset

This dataset captures biomechanical data, injury information, and rehabilitation outcomes of basketball players. It was created to study how motion patterns contribute to injury risk and how targeted rehabilitation strategies improve recovery and reduce re-injury.

Key Features

Player Demographics

• Player_ID: Unique identifier for each player
• Age: Player’s age at the time of injury
• Height_cm: Player’s height in centimeters
• Weight_kg: Player’s weight in kilograms
• Position: Basketball position (e.g., Guard, Forward, Center)

Injury Information

• Injury_Type: Type of injury (e.g., Ankle Sprain, ACL Tear, Hamstring Strain)
• Injury_Severity: Severity of injury (Mild, Moderate, Severe)
• Date_of_Injury: Date the injury occurred
• Injury_Recurrence: Whether the injury recurred (0 = No, 1 = Yes)

Biomechanical Motion Data

• knee_angle_deg: Knee angle during movements (degrees)
• jump_height_cm: Jump height (centimeters)
• ankle_flexion_deg: Ankle flexion during motion (degrees)
• speed_m_s: Speed in meters per second
• reaction_time_ms: Reaction time in milliseconds

Rehabilitation Information

• Rehabilitation_Program: Assigned rehab type (e.g., Physiotherapy, Strength Training)
• Rehabilitation_Time_weeks: Time taken for rehab (weeks)
• Rehabilitation_Efficiency_Score: Score (0.5–1.0) reflecting recovery speed and quality

Applications

• Injury Prediction: Identify players at risk using biomechanical features
• Rehabilitation Optimization: Design individualized rehab programs based on injury history and performance
• Performance Monitoring: Track biomechanical recovery to ensure return-to-play readiness and reduce re-injury risk