Date of Award

Spring 5-7-2021

Level of Access Assigned by Author

Open-Access Thesis

Degree Name

Master of Science (MS)


Kinesiology and Physical Education


Robert Lehnard

Second Committee Member

Christopher Nightingale

Third Committee Member

Sid Mitchell


In competitive sports, the ultimate goal is to win as many matches, competitions, or games as possible. In an attempt to optimize this goal, the use of data analytics has risen. Soccer, a particularly popular sport across the globe, has been using data analytics for this optimization for multiple decades. One common practice for this data collection is the use of heart rate monitors paired with GPS tracking in order to collect data. Some of the data collected includes training load, total distance, sprints, and time spent in various heart rate percentage zones. Additionally, InStat Index has been used to collect skill specific data about various competition related variables such as shots completed, passes completed and goals conceded. In conjunction with the performance data, coaches can make informed decisions based off of this information to improve the outcome of winning. A University Women’s Soccer team used Polar Team Pro and InStat to analyze their performance. It was found that training load, total distance, sprints and time spent at or above 70% of heart rate maximum are weakly correlated with InStat Index.