Sports Analytics Specialization

What you'll learn

When you pursue a Sports Analytics specialization, you'll gain core skills in data analysis, management, infrastructure, and ethical project management. You'll also develop expertise in sports sales, handling large data sets, cloud computing, and the data life cycle.

Curriculum

You'll build a strong foundation in data analysis, management, and infrastructure, while also gaining expertise in ethical project management. You’ll learn about key areas such as sports sales, working with large data sets, cloud computing, and understanding the data life cycle, preparing you to tackle real-world challenges in the rapidly evolving sports industry.

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)

  • DSCI-D 501 Introduction to Data Science Programming (was INFO-H 501)
  • LIS-S 511 Database Design
  • DSCI-D 510 Statistics for Data Science (was INFO-H 510)
  • DSCI-D 515 Statistical Learning (was INFO-H 515) (Prerequisite: Graduate Statistics course)
  • DSCI-D 516 Cloud Computing for Data Science (was INFO-H 516) (Prerequisites: Graduate Database course)
  • DSCI-D 517 Visualization Design, Analysis, and Evaluation (was INFO-H 517) (Prerequisite: Programming experience)
  • Other approved Applied Data Science electives

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 Courses (9 credits)

  • TESM-T 501 Advanced Sports Analytics (Fall)
  • TESM-T 582 Applied Sport Event Research (Spring)
  • TESM-T 598 Master’s Consulting Project (Summer)

Elective Courses (3 credits)

  • INFO-B 505 Informatics Project Management
  • DSCI-D 518 Deep Learning Neural Networks (was INFO-H 518)
  • DSCI-D 519 Natural Language Processing with Deep Learning (was INFO-H 519) 
  • DSCI-D 695 Thesis/Project in Data Science (was INFO-H 695) (MS Thesis students only)
  • INFO-I 575 Informatics Research Design
  • INFO-I 595 Professional Internship
  • INFO-I 698 Research in Informatics (Independent Study)
  • DSCI-D 502 Modeling Crisis (was INFO-P 502)
  • NEWM-N 510 Web Database Development

This is a recommended plan of study. If you have any questions or concerns, please email the HCC Graduate Academic Advisor for assistance.

Fall Year 1

  • DSCI-D 501 Introduction to Data Science Programming (was INFO-H 501)
  • TESM-T 501 Advanced Sports Analytics
  • Choose one:
    • LIS-S 511 Database Design
    • DSCI-D 510 Statistics for Data Science (was INFO-H 510)

Spring Year 1

  • TESM-T 582 Applied Sport Event Research
  • Choose one:
    • LIS-S 511 Database Design
    • DSCI-D 510 Statistics for Data Science (was INFO-H 510)
  • Choose one:
    • DSCI-D 515 Statistical Learning (was INFO-H 515)
    • DSCI-D 516 Cloud Computing for Data Science (was INFO-H 516)
    • DSCI-D 517 Visualization Design, Analysis, and Evaluation (was INFO-H 517)

Summer Year 1

  • TESM-T 598 Master’s Consulting Project

Fall Year 2

  • Choose two:
    • DSCI-D 515 Statistical Learning (was INFO-H 515)
    • DSCI-D 516 Cloud Computing for Data Science (was INFO-H 516)
    • DSCI-D 517 Visualization Design, Analysis, and Evaluation (was INFO-H 517)
  • Elective Course

This is a recommended plan of study. If you have any questions or concerns, please email the HCC Graduate Academic Advisor for assistance.

Spring Year 1

  • DSCI-D 501 Introduction to Data Science Programming (was INFO-H 501)
  • TESM-T 582 Applied Sport Event Research
  • Choose one:
    • LIS-S 511 Database Design
    • DSCI-D 510 Statistics for Data Science (was INFO-H 510)

Summer Year 1

  • TESM-T 598 Master’s Consulting Project

Fall Year 1

  • TESM-T 501 Advanced Sports Analytics
  • Choose one:
    • LIS-S 511 Database Design
    • DSCI-D 510 Statistics for Data Science (was INFO-H 510)
  • Choose one:
    • DSCI-D 515 Statistical Learning (was INFO-H 515)
    • DSCI-D 516 Cloud Computing for Data Science (was INFO-H 516)
    • DSCI-D 517 Visualization Design, Analysis, and Evaluation (was INFO-H 517)

Spring Year 2

  • Choose two:
    • DSCI-D 515 Statistical Learning (was INFO-H 515)
    • DSCI-D 516 Cloud Computing for Data Science (was INFO-H 516)
    • DSCI-D 517 Visualization Design, Analysis, and Evaluation (was INFO-H 517)
  • Elective Course
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 IU Indianapolis and my internship (with the Indiana Pacers) were both instrumental to where I am today."

Learn more about Gabriel