The Center for the Study of Sport and Exercise joined forces with the SU Men’s Soccer Team to use state-of-the-art technology to improve player performance, coaching, and training. Now entering its 3rd season of collaborating, Kinesiology Department’s Exercise Scientist, Sean Machak, tested athlete fitness and supervised the management of data collected on 20 athletes who wore a Zephyr Bioharness, and used Metrifit monitoring solutions throughout the season. By gathering data in real time, not just in the Center’s Human Performance Lab, provides students in the degree program, the student athletes, and the coaches with information typically available only in professional sports.

Soccer Coach Pete Fewing, a former professional soccer player, knows how valuable that data is. Athletes thrive on competition and want to be as fit and agile as they can be, for themselves and for the team.

“It’s exciting for them and for me because technology is opening up the door to allow us to get into athlete-specific training,” Fewing said.

Our lab is now provided athlete specific training plans to prepare athletes for the demands of the season. During the season, efforts were focused around the feedback provided on athlete training load status and responses. Assisting Sean this past quarter was Brazilian graduate student, Rafael Curvello. This season the Redhawks earned their third conference championship in the last five years.

Our department hopes to provide more opportunities for our students through projects like this one. Students not only experience how their classroom and lab work are applied and benefit real people, they also witness how the information they collect is used by others.

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Kari Berkas
Program Coordinator

The work our students are doing goes beyond a one-size-fits-all approach when it comes to maximizing student- athlete performance, we monitor performance during practices and during games in order to give a level of specificity that can be used to individualize training for each player.

Professor Eric Dugan