The Sports Docs Podcast

142: Dr. Jacob Calcei – Wearable Technology for Athlete Performance & Injury Prevention (Part 2)


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Our conversation picks back up with an article published just last month in AJSM titled “Player Tracking Metrics to Predict Risk of ACL Injuries During Change-of-Direction Scenarios in the NFL.” The authors analyzed 216 ACL injuries that occurred in the NFL from 2018–2022 to determine how player tracking data could help predict injury risk, particularly during change-of-direction or “CoD” plays. They found that nearly half of ACL injuries occurred during CoD scenarios, most often involving high speeds followed by rapid deceleration. 

The authors noted that 98% of players were decelerating at the moment of injury. Using synchronized video and player tracking, the researchers found that maximum speed and normalized maximum deceleration power were significant predictors of ACL injury risk. Additionally, special teams plays showed the highest rates of CoD ACL injuries, though when motion data were factored in, the elevated risk was better explained by player speed and deceleration demands rather than play type alone. These findings highlight the potential to use tracking metrics for real-time risk monitoring, improved prevention programs, and possibly even future changes to training or game rules to reduce injury risk.

We’re going to wrap up today with a study that is currently ongoing and not yet published. Funded by the AOSSM Playmaker Grant, this clinical trial is investigating the use of wearable muscle oxygenation sensors to improve return-to-play assessment after ACL reconstruction. Dr. Voos, Dr. Calcei, and their team at the UH Drusinsky Sports Medicine Institute have found that muscle oxygenation recovery lagged behind clinical clearance in several cases. 

Eight athletes did not regain normal muscle oxygenation even when they were deemed ready to return. These findings suggest that wearable muscle oxygen saturation monitoring may add a valuable physiologic layer to current return to play protocols, potentially predicting safer and more individualized recovery timelines.

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