Football
The Football Analytics Team meets primarily in the fall to discuss the latest happenings in football analytics and how they relate to the Notre Dame team in particular. As part of the club, we put on friendly analytics-related competitions (past ones have included modeling the results of the CFP bracket), walk through R coding basics, and discuss how the Notre Dame Football team is performing week-to-week. This is a great team to join for those with low coding experience, as we hold multiple tutorials every year teaching members the best ways to conduct their own football analysis in R, utilizing the CFBFastR package in particular to derive insight. If you’re a fan of Notre Dame Football and want to learn more about how data informs the decisions made on the field every Saturday, the Football Analytics Team is the right place for you!
For questions regarding the Football Analytics Team, please contact Isaiah Rell at irell@nd.edu.
Volleyball
The Volleyball Analytics team focuses on using data and analytics to enhance team performance and decision-making. Members work on building strong relationships with coaching staff and players while developing tools to improve in-game analysis, visualization, and practice planning. A key part of the club’s work includes leveraging Data Volley analytics to evaluate performance and uncover actionable insights.
We utilize a variety of tools, including Tableau, R, Excel, and Python, to explore and present data in meaningful ways. The club is open to everyone, and it’s especially welcoming for those with little or no coding experience who are interested in learning. Whether you’re brand new to analytics or looking to expand your skills, this is a great environment to get hands-on experience and grow.
For questions regarding the Volleyball Analytics Team, please contact Isabelle D’Souza at idsouza@nd.edu or Mackenzie Cote at mcote@nd.edu.
Hockey
The Hockey Analytics Team is broken down into 3 main projects: recruiting analytics, postgame reports, and special projects.
Recruiting Analytics: The team is working to develop a recruiting dashboard that will help Notre Dame hockey coaches identify high-potential players using advanced analytics. By analyzing eight years of NCAA Division I hockey performance data, the system learns patterns that distinguish future elite players from the rest. The dashboard presents player profiles through intuitive visualizations that highlight strengths and development areas across key performance categories. Coaches can quickly compare prospects and identify players whose skills match their team’s needs.
Postgame Reports: The club composes a concise, one-page report after each individual Notre Dame hockey game or weekend series. Club members gain access to advanced analytics from the team’s official database and critically analyze thousands of data points to consolidate a breadth of information into each report. Each report highlights individual standout performers for both teams, breaks down key team trends, and includes relevant game film analysis. Each report is promptly delivered directly to the Notre Dame coaching staff on a weekly basis.
Special Projects: The club takes on special projects throughout both the hockey season and offseason. The Notre Dame coaching staff requests some projects, while the club pitches others to the staff. Regardless, each project allows the staff to gain a deeper understanding of their own team, a rival team, or college hockey in general. The club’s most recent special projects include a breakdown of NCAA Frozen Four teams from 2015-25, a deep analytical dive into Notre Dame’s penalty kill struggles, and a Big Ten playoffs prediction model based in Python.
For questions regarding the Hockey Analytics Team, please contact Parker Davidson at pdavids2@nd.edu, Alex Styczynski at astyczyn@nd.edu, or Charlie Morris at cmorri27@nd.edu.
Men’s Lacrosse
The Men’s Lacrosse Analytics Team focuses on using data and analytics to improve team success by producing weekly post-game reports alongside targeted projects. We work closely with the coaching staff to determine what can specifically help the team and create helpful related visuals for easy translation in practices. We mostly work with spreadsheets and Tableau to track week-by-week statistics along with season-long statistics. We are open to anyone joining, regardless of coding or lacrosse experience, and believe that it is a great environment to gain experience and expand your knowledge.
For questions regarding the Men’s Lacrosse Team, please contact Caitlyn Curtin at ccurtin2@nd.edu or Saul Zabukovic at szabukov@nd.edu.
Men’s Basketball
The Men’s Basketball Analytics Team uses public data with play-by-play info and box scores to develop pregame reports and scoring analyses throughout the college basketball season. Our big project comes during February and March when the team works on a machine learning model to create a bracket for March Madness.
For questions regarding the Men’s Basketball Analytics Team, please contact Drew Villhard at dvillha2@nd.edu.
Golf
The Golf Analytics Team focuses on using historical golf data to explain trends in tournaments. Founded in 2026, the team initially concentrated on professional events and is now transitioning to working with the Notre Dame golf teams. To do this, we analyze data and present it in a clear, simple way that’s accessible even to those with minimal background knowledge. We use tools such as Python, R, and Tableau to interpret and visualize our findings. We welcome anyone to join, regardless of prior experience in analytics or golf, and see this as an opportunity to deepen our understanding of both data analysis and the sport as a whole.
For questions regarding the Golf Analytics Team, please contact Alex Weiss at aweiss5@nd.edu.
Women’s Soccer
The Women’s Soccer Analytics Team is focused on leveraging data-driven insights to evaluate player performance, support scouting efforts, and enhance team strategy. Through a combination of visual analytics and statistical modeling, members work on projects that translate complex data into actionable insights for coaches and players.
Radar Graphs: The team develops analytical player profiles using radar visualizations to highlight individual strengths and areas for improvement. These graphs enable clear comparisons across offensive metrics such as clutch performance, shooting efficiency, assists, fouls drawn, and overall impact, allowing for intuitive evaluation of player performance.
Power BI Dashboards: Members build interactive dashboards to analyze ACC competition and generate detailed scouting reports. These dashboards also focus on optimizing offensive performance, particularly in the final third, by identifying patterns and opportunities to improve scoring efficiency.
Analytical Tools Used (No Experience Necessary!): The team utilizes a variety of industry-relevant tools, including Excel, RStudio, Power BI, and Python. No prior experience is required—members will gain hands-on exposure and develop technical skills throughout the process.
For questions regarding the Women’s Soccer Analytics Team, please reach out to Lindsay Wurth at lwurth@nd.edu or Lauren LaMena at llamena@nd.edu.
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