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Activity Number: 407 - Emerging Methods in Sports Injury Research: Strategies for Shifting the Paradigm
Type: Topic Contributed
Date/Time: Wednesday, August 5, 2020 : 1:00 PM to 2:50 PM
Sponsor: Section on Statistics in Sports
Abstract #313336
Title: Advancing Injury Risk Models Using Sensor-Based and Athlete Wellness Metrics
Author(s): Jay Hertel* and Natalie Kupperman
Companies: University of Virginia and University of Virginia
Keywords: athlete monitoring; injury risk; sports

Over the past decade, there has been a rapid acceleration in the field of athlete monitoring with the introduction of global positioning systems technology in field sports. Athlete monitoring is characterized by quantifying physiological workload and psychological stressors incurred by athletes during and outside practices and competitions with the goals of enhancing performance, determining athlete readiness, and mitigating injury risk. A handful of metrics have been associated with increased injury risk in studies performed on single sport teams, however, the body of evidence is inconclusive on whether metrics identified as increasing injury risk in studies of single teams can be generalized to forecast injury risk in other teams. Robust evaluation of athlete workload and wellness metrics is needed to advance the field so that predictive models can be more broadly applied to the clinical practice of sports science and sports medicine. This presentation will highlight critical measurement and analysis issues in athlete monitoring such as acute-to-chronic workload ratios, the nuances of volume versus intensity measures of workload, and limitations in existing modeling techniques.

Authors who are presenting talks have a * after their name.

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