Sports Analytics Specialization

Succeed with a winning combination

Analytics is a crucial part of decision-making in amateur and professional athletics. Teams rely on those with the knowledge to interpret data and relate it to the world of athletics. (Nikhil Morar—pictured above—earned his Applied Data Science master's degree with a specialization in Sports Analytics from our program, and became Manager of Business Analytics & Strategy for the Los Angeles Lakers basketball franchise.)

Indianapolis boasts 10 professional sports teams. The city is home to the National Collegiate Athletic Association (NCAA), the National Federation of State High School Associations, and is widely considered the Capital of Amateur Sports.

By teaming up, the Luddy School in Indianapolis and the Department of Tourism, Event, and Sport Management draw on a unique mix of resources to offer B.S./M.S. in this exciting field.

Rishi Chandran

I was able to use machine learning and descriptive statistics to create actionable scouting reports focused on finding strategies that will give a team a better chance of winning.

Rishi Chandran, M.S. '23 & Basketball Operations Seasonal Assistant with the Cleveland Cavaliers
Nikhil Morar at the office of the LA Lakers

Nikhil Morar

Manager of Business Analytics & Strategy for the Los Angeles Lakers

“Sports organizations need analytics experts who can turn data about their customers and teams into revenue-generating strategies."

Learn more about Nikhil
Gabriel Wachowski with the NBA Championship trophy

Gabriel Wachowski

Research and Innovation Analyst for the Milwaukee Bucks

"Overall, the job has been absolutely incredible. I definitely feel like having my master’s was extremely important to being ready for the job that I have. My classes at IUPUI and my internship (with the Indiana Pacers) were both instrumental to where I am today."

Learn more about Gabriel

A skill set tailored to sports

Students who earn a Master of Science in Applied Data Science with a specialization in Sports Analytics learn core skills in data analysis, data management and infrastructure, and client–server application development, and ethical and professional management of data projects.

Earn additional competencies in sports sales, the management of massive, high-throughput data stores, cloud computing, and the data life cycle.

The plan of study is 30 credit hours. It includes six core courses and four specialization/ elective courses. Transfer students may be able to transfer in approved graduate courses from an accredited institution.

F-1 students can only take one online course per semester. They must take a minimum of 8 credit hours per semester; the exception being in their final semester. These limitations apply to fall and spring semesters but not summer sessions.

Core Courses (18 credits)

Students may test out of LIS-S 511. Students do not receive credit toward their required 30 credit hours by testing out of a course. However, they may instead replace the course with a specialization course or approved elective.

Specialization + Elective Courses (12 credits)

Specialization Courses

Elective Courses

Thesis or Project

The Thesis/Project is available to highly motivated students ready to carry out publishable research. Students must prepare a prospectus and gain a commitment from a primary faculty advisor with research interests in data science by the end of the first semester. By the end of the second semester, students must complete a course on research design and methods (e.g., INFO-I 575 or LIS-S 506).

The thesis or project must be completed in two semesters or in a semester and summer. Thesis students register for a total of 6 credits and project students register for a total of 3–6 credits of INFO-H 695 Thesis/Project in Data Science. Students are required to prepare and defend a research proposal with a timeline of deliverables in addition to the thesis or project.

Fall Year 1

Spring Year 1

Summer Year 1 (Optional)

  • Sports Analytics Specialization or Elective Course

Fall Year 2

Spring Year 1

Summer Year 1 (Optional)

  • Sports Analytics Specialization or Elective Course

Fall Year 1

Spring Year 2