Predicting elbow valgus torque from upper extremity baseball pitching kinematics using markerless motion capture
Background
Markerless motion capture in sport is becoming widely available and increasingly popular. Because of the increase in popularity, it is important to determine if the values reported by these systems are similar to that of previous research, and for the purposes of injury prevention, if these values are able to predict elbow stress.
Purpose
We aimed to investigate if elbow valgus torque can be predicted using data gathered with a KinaTrax® markerless motion capture system.
Study Design
Cross-Sectional Study
Methods
Twenty-one college baseball pitchers partook in a preseason practice where they threw bullpen pitching sessions. An eight camera KinaTrax® markerless motion capture bullpen system, capturing at 300 Hertz, was used to capturing their pitching motion. One fastball from each pitcher was randomly selected for analysis. A multiple regression analysis approach was used to predict peak elbow valgus torque using upper extremity kinematics.
Results
The combination of maximum external rotation angle, elbow flexion angle at peak elbow valgus torque, elbow flexion angle at ball release, and percent of the pitching cycle when peak elbow flexion angle occurred significantly predicted peak elbow valgus torque (F4,16 = 5.819, R2 = 0.593, p = 0.004). Additionally, reported values were similar to those of published research in baseball pitching biomechanics.
Conclusion
These findings suggest ecologically valid biomechanical data from markerless motion capture can be used to analyze key variables related to injury prevention in baseball pitching.
© Copyright 2025 Sports Medicine and Health Science. Elsevier. All rights reserved.
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| Notations: | sport games technical and natural sciences |
| Tagging: | Kinematik markerless |
| Published in: | Sports Medicine and Health Science |
| Language: | English |
| Published: |
2025
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| Online Access: | https://doi.org/10.1016/j.smhs.2025.02.006 |
| Document types: | article |
| Level: | advanced |