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Big data in sports provide a unique and challenging opportunity for advanced statistical analysis. The goal of the sports analyst is to identify patterns from the data – to inform and optimize player and team strategy and to predict future outcomes in athletic performance.
The online graduate certificate program in sports analytics at Mizzou offers a unique opportunity for students to learn statistical methods and computational tools to perform analyses for sports. The program will help to prepare students for career opportunities in the exciting and growing industry of sports analytics.
Quick facts
Official name
Graduate certificate in sports analyticsCampus
Program type
Graduate certificateAcademic home
College of Arts & Science | Department of StatisticsDelivery mode
100% onlineAccreditation
Higher Learning CommissionCredit hours
12Estimated cost
$6,300.00*This cost is for illustrative purposes only. Your hours and costs will differ, depending on your transfer hours, your course choices and your academic progress. See more about tuition and financial aid.
Career prospects
Potential careers
Sports data analyst positions working for:
- Performance technology corporations
- Professional sports teams
- Sports analytics consulting companies
- Sports betting companies
- Sports video game developers
Program structure
The online graduate certificate in sports analytics is 100 percent online: no campus visits required.
Courses are semester-based. Students typically take two classes in fall and two classes in spring and finish the program in a year.
Delivery
100% onlineCalendar system
Semester-basedTypical program length
1 yearTypical course load
2 classes per semesterAccreditation
The University of Missouri is accredited by the Higher Learning Commission, one of six regional institutional accreditors in the United States.
Faculty spotlight
Research interests:
- Sports statistics
- Spatio-temporal models
- Dynamical models
- Bayesian hierarchical methods
- Deep learning
- Reinforcement learning
- Environmental and ecological statistics
Nicholas Grieshop is an assistant teaching professor in the Department of Statistics. Dr. Grieshop teaches methods in sports analytics, applied statistical models and introduction to Bayesian data analysis. His research interests include undergraduate research, sports statistics, Bayesian modeling and deep learning. He earned his doctorate in statistics from the University of Missouri. He previously worked as a mechanical engineer.