Estimating Joint Kinetics During Baseball Pitching Using In-stadium Markerless Motion Capture

Markerless motion capture facilitates the collection of biomechanics data through machine-vision based approaches. In-stadium markerless motion capture has emerged as the primary modality for ball tracking and skeletal pose estimation of athletic movements at competitions. However, the criterion validity of baseball pitching kinetics using this markerless technology remains unclear. PURPOSE: To examine the equivalence of baseball pitching kinetics derived from in-stadium markerless, in-lab markerless, and marker-based motion capture modalities. METHODS: This analysis is based on a sample of 18 collegiate baseball players (height = 1.83 ± 0.02 m, mass = 86 ± 18 kg, fastball velocity = 84.3 ± 4.1 mph), all of whom provided written informed consent to participate in this study. Each participant pitched off a regulation mound while their segment motions were concurrently recorded with a 5-camera in-stadium markerless motion capture system (Hawk-Eye, Basingstoke, UK), 10-camera in-lab markerless motion capture system (Theia Markerless, Kingston, ON), and an 8-camera marker-based motion capture system (Qualisys, Göteborg, Sweden) at a sampling rate of 300 Hz. The concordance correlation coefficient (CCC) and a nested Bland-Altman analysis were used to assess the agreement and reliability of peak shoulder forces, peak shoulder rotation torques, and peak elbow valgus torques among modalities. RESULTS: Using the marker-based method as a reference, Theia and Hawk-Eye markerless modalities underestimated shoulder forces by 42 N and 37 N, respectively, with moderate reliability (CCC = 0.659). Theia underestimated shoulder and elbow torques by 16 Nm and 4 Nm (CCC = 0.426), respectively, while Hawk-Eye overestimated them by 33 Nm (CCC = 0.010). CONCLUSION: The in-stadium markerless system estimated pitching-relevant joint torques with larger biases, owing to error propagation from key point noise and deviations in segment definitions at the kinematics level.

Authors

Institutions

Publication Details

Journal
Medicine & Science in Sports & Exercise
Published
2025-09-16
DOI
https://doi.org/10.1249/01.mss.0001156236.87927.c0
Primary Topic
Sports Performance and Training
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Estimating Joint Kinetics During Baseball Pitching Using In-stadium Markerless Motion Capture

D. Taylor La Salle, Rafael F. Escamilla, Arnel Aguinaldo, Tyler Cardinale
Medicine & Science in Sports & Exercise
Sports Performance and Training
article

Estimating Joint Kinetics During Baseball Pitching Using In-stadium Markerless Motion Capture

D. Taylor La Salle, Rafael F. Escamilla, Arnel Aguinaldo, Tyler Cardinale
article en

Abstract

Markerless motion capture facilitates the collection of biomechanics data through machine-vision based approaches. In-stadium markerless motion capture has emerged as the primary modality for ball tracking and skeletal pose estimation of athletic movements at competitions. However, the criterion validity of baseball pitching kinetics using this markerless technology remains unclear. PURPOSE: To examine the equivalence of baseball pitching kinetics derived from in-stadium markerless, in-lab markerless, and marker-based motion capture modalities. METHODS: This analysis is based on a sample of 18 collegiate baseball players (height = 1.83 ± 0.02 m, mass = 86 ± 18 kg, fastball velocity = 84.3 ± 4.1 mph), all of whom provided written informed consent to participate in this study. Each participant pitched off a regulation mound while their segment motions were concurrently recorded with a 5-camera in-stadium markerless motion capture system (Hawk-Eye, Basingstoke, UK), 10-camera in-lab markerless motion capture system (Theia Markerless, Kingston, ON), and an 8-camera marker-based motion capture system (Qualisys, Göteborg, Sweden) at a sampling rate of 300 Hz. The concordance correlation coefficient (CCC) and a nested Bland-Altman analysis were used to assess the agreement and reliability of peak shoulder forces, peak shoulder rotation torques, and peak elbow valgus torques among modalities. RESULTS: Using the marker-based method as a reference, Theia and Hawk-Eye markerless modalities underestimated shoulder forces by 42 N and 37 N, respectively, with moderate reliability (CCC = 0.659). Theia underestimated shoulder and elbow torques by 16 Nm and 4 Nm (CCC = 0.426), respectively, while Hawk-Eye overestimated them by 33 Nm (CCC = 0.010). CONCLUSION: The in-stadium markerless system estimated pitching-relevant joint torques with larger biases, owing to error propagation from key point noise and deviations in segment definitions at the kinematics level.

Medicine & Science in Sports & ExerciseVol. 57(10S)
California State University, Sacramento (US), Point Loma Nazarene University (US)
Openalex Percentile: Top 68%
Sports Performance and Training
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.