On Saturday, September 14, before University of Virginia Football's big win over Florida State, the Alumni Association hosted researchers and alumni from the Kinesiology department for their More Than The Score lecture series. "The Science of Athletic Performance" event featured a panel discussion on how data science is increasingly used to better understand and prepare athletes for improved performance, as well as using data to prevent and treat sports-related injuries. The event was moderated by Cavaliers' Distinguished Teaching Professor and Chair of Kinesiology, Art Weltman.
The panelists pictured above from the left were Jay Hertel, Joe H. Gieck Professor of Sports Medicine; Michael Curtis (kinesiology alumnus), head strength and conditioning coach for the 2019 NCAA Champion UVA Men’s Basketball team; Susan Saliba, professor of Kinesiology; Kelli Pugh (kinesiology alumna), Associate Athletic Director for Sports Medicine; Joseph Hart, associate professor of Kinesiology; and Jacob Resch, assistant professor of Kinesiology.
Weltman: Setting the Stage
Professor Weltman moderated The Science of Athletic Performance discussion by asking each of the researchers about the projects on which they are currently working. Weltman also asked Curtis and Pugh how they are currently using technology hands-on with student athletes in men's basketball and football at UVA.
Hertel: Sensor Technology
Professor Hertel is researching the use of sensor technology with both soccer and volleyball players. In soccer, sensors that include gps trackers monitor the distance student athletes run during the course of a game or practice. They also track length of time athletes spend at varying rates of movement: jog, run, walk, or sprint.
"It used to be that 'the tape never lies,'" Hertel said. "Now it is 'the sensors never lie.'"
These sensors offer unbiased data and can help inform if there is overtraining or burnout happening.
According to Hertel, when it comes to volleyball, jump count is as important to a coach as pitch count is to a baseball coach. It is a number that needs to be tracked to avoid over-stressing a student athlete. The sensors can also inform the kinds of movements that each players do on the court, moving side to side or front to back. With this information coaches can help better prepare their players to more effectively move in their given position.
Curtis: Training Basketball Players
Coach Curtis was an early adopter of technology to help inform his role as the strength and conditioning coach for UVA men’s basketball. He is utilizing monitors and athletes' self-reporting to measure both internal and external load to optimize training student athletes. Internal load includes measures of a range of items, including heart rate, sleep or stress. External load measures include running distance, accelleration and speed, or weight training. The information from these measures not only help Coach Curtis tailor conditioning for each student athlete, it can also improve performance.
"Our competitive edge is informed decision-making," Curtis said.
Saliba: Transforming Data Into Meaningful Information
Athlete-monitoring devices collect data continuously and provide an overwhelming amount of data.
Professor Saliba is partnering with UVA's School of Engineering and Applied Sciences to transform the large amounts of data that are collected on student athletes into forms of information that are helpful for coaches. Together, they are building algorithms to process and organize the data collected by sensors. Saliba's role as connecting the data and data analysts to the real-world application on the fields and courts of play is a critical one as this work continues to grow.
With such large sets of data available to inform a wide variety of decisions by coaches and athletic trainers, Saliba sees a continued need to balance the analysis of large data sets with the particularities of each individual student athlete.
Determining An Athlete's Ability To Return to Play
Associate Professor Hart is studying how the use of sensors can determine when athletes are ready to return to play. By placing sensors on an athlete's low back, writsts and ankles, Hart can monitor if the athlete is moving in an asymmetrical way or favoring a particular side of their body, often revealing that the injury has not fully healed.
Hart is also utilizing a technology that can measure muscle volume patterns. These patterns can offer much more detailed information in post-injury areas that might reveal more time required before returning to play. With both of these tools, Hart is working to discover ways to more accurately assess injury to ensure student athletes are completely recovered before they are cleared to return to their sport.
Measuring The Impacts of Concussion
According to Assistant Professor Resch, there exists a multi-dimensional concussion diagnosis that is 100% accurate. The problem is that it takes about 1.5 hours to complete. His work is to improve the efficiency of concussion diagnosis while maintaining the high-level of accuracy. Resch discussed three ways researchers are currently working on making that happen. The first includes a technology that measures how a student athlete uses their phone: How they pick it up and hold it, if they adjust the screen brightness, how often the phone is used and when. It is possible that these data can inform a potential concussion. Second, the UVA football team is currently using a mouthguard that includes an accelerometer that can measure the magnitude of the impact of a hit during play. This data can be used to help inform a concussion diagnosis. Third, researchers are testing an alert system that football players wear that creates a vibration to warn the player they are about to get hit. This data, paired with training on how best to react to that warning, could especially reduce the impact of blind-sided hits.