Learn skills in data analysis, statistical modeling, and technology application to prepare for a career in the sports industry.
The M.S. in Sport Analytics is an online program that integrates academic, practical, and research skills, enabling students to master sport business analytics with a focus on data acquisition, statistical modeling, predictive analytics, big data, and visualization techniques for effective application in the field.
The MS in Sport Analytics provides two online options:
Through an accelerated 8-week courses, students can complete the online program within one year.
Master of Sports Analytics
Sport Performance ;
Sport Business ;
Sport Business and Performance
30
Master's Program
1 year
Choosing the right graduate program can be difficult enough, so getting the application right shouldn't add to your stress. We've gathered all the info you need to apply to the Master of Science in Sport Analytics to make things as easy as possible.
Students that want to apply to the sport analytics degree can submit applications on an rolling basis, but the final deadline is one month before the start of the desired term.
Applying students must submit the following for consideration:
The GRE requirement is waived for applicants who have:
The Sport Analytics master’s program is designed to be completed in as little as 12 months, with flexible options for students who need a part-time schedule. Explore the recommended course sequence, term-by-term requirements, and important capstone information for students entering in the fall.
Check out some of the key classes you’ll encounter as a Sport Analytics graduate student. Curious about what else is offered? Browse the full catalog of courses.
GR
3 credits
The focus of this course is to provide students with an understanding of descriptive statistics (e.g., mean, standard deviation, frequency distribution) and inferential statistics (e.g., chi square, t-tests, analysis of variance [ANOVA], correlation, regression, factorial ANOVA, repeated measures ANOVA), and how to use SPSS and to interpret and present statistical results.
GR
3 credits
This course will focus on the practical applications of analytical methods with R programming. Students will gain general knowledge of analytic techniques such as statistics, data mining, visualization of data, and basic machine learning. This course will cover the applications in those methods through practice of R.
GR
3 credits
This course will provide an overview of techniques for effectively translating and communicating quantitative and qualitative data into readable graphics to varied audiences, including sport agencies and the public. Visualization and communication tools such as promotional materials (e.g., infographics), statistical graphs and plots, and oral presentations will be covered to give students skills in making sport data and messaging generalizable and easily understood.
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Median income for Director of Sports Marketing in 2026.
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