Maddie Moran | 2025 I.S. Symposium

Name: Maddie Moran
Title: An Analysis of the Impact of Front Row Attackers in Division I Women’s Volleyball using Markov Chain Processes
Major: Data Science and Sports Analytics
Minor: Philosophy
Advisor: Colby Long

This study investigates the impact of front row attackers on the outcomes of a National Collegiate Athletic Association (NCAA) Division I women’s volleyball match using Markov chain techniques. The goal is to compare consistency, efficiency, and overall quality of performance in each of the three front row attackers: outside, middle, and opposite hitters. By assessing the skill levels of these players both over full seasons and a single match, we are able to create transition matrices containing probability that the ball will move from each individual state to another, including states that represent scoring points. These transition matrices are then used to inform Markov models built to reflect points and sets of volleyball, which include stipulations to uphold the integrity of the rules of the game. From these results, we gather that middle and opposite attackers should be granted a higher frequency of attack attempts, rather than being reserved for blocking purposes. I think it would also benefit to dive deeper into back row attacks due to their rising popularity.

Posted in Symposium 2025 on May 1, 2025.