Sensor Technology and Analytics to Assess & Predict Injury in Baseball Pitchers

Data Analytics / Elite/Collegiate / Wearable Technology
baseball
Complete
Start Date
01/01/2017
End Date
12/31/2018
PIs
Other
Funding
ESSI P&F

SENSOR TECHNOLOGY AND COMPLEX ANALYTICS TO ASSESS, MONITOR AND PREDICT INJURY IN ELITE BASEBALL PITCHERS

Team: Stephen Cain (CoE), Rich Gonzalez (LSA; Ross School of Business; ISR; and CoE), Michael Freehill (Medical School), and Cristine Agresta (outside consultant)

Summary: Researchers aim to develop a practical day-to-day monitoring protocol and measurement system that can be used to quantify dynamic pitching capacity and injury. The objective is to characterize pitching patterns over loading cycles to identify aspects of pitching mechanics that correlate to player fatigue and injury risk factors and can feasibly be monitored in real-world settings using wearable sensors.