Master's in Sports and Exercise Analytics
Step up your game in the sports and exercise field
Data analytics is transforming the world of sports and exercise. The master of science in sports and exercise analytics at Marquette University intersects physiology and biomechanics with data science to address specific questions regarding elite athletic, sport, exercise and human performance.
Graduates will have the analytic skills to develop new applications and interfaces for large and complex sport and human performance data sets combined with the foundational knowledge in exercise and sport physiology by which to aid in the accurate interpretation and translation of results to consumers, end users and clients.
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Part-time and Online Options**
*Based on full-time student | **Hybrid program with online and on-campus courses.
Read an Interview with Professor Kristof Kipp
Associate Professor Kipp discusses how the Sports and Exercise Analytics program prepares students for future success in an evolving world.
See how we move
Check out our latest basketball analytics evaluation in the research lab.
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The goal of this program will be to train sports and exercise data analysts to:
- Articulate changes, trends and implications using analytics tools that can be ethically addressed across data platforms.
- Design and implement strategies for analyzing data using appropriate methods, tools and data sets.
- Analyze data to create actionable information, and use it to establish priorities, make decisions and solve problems aligning with the ethics, needs and values of individuals, communities and stakeholders
- Display and explain the results of analytics projects using effective written, graphic, and verbal tools and techniques.
- Use advanced data processing tools incorporating regulatory, data governance, master data management, data profiling, parallel and distributed processing best practices.
- Manage data analytics projects and teams throughout the analytics life cycle.
- Interpret and translate sports and exercise performance data for targeted consumers (private, public).
Students are prepared to pursue careers in sport and exercise performance data science, including positions at:
- Professional sports teams
- Collegiate sports teams
- Wearable companies
- Software companies
- Human performance laboratories
Hands-on Experience with Marquette Athletics
The program intersects with Marquette Athletics and its staff to address specific questions regarding elite athletic performance with our faculty as experts to assist in those measurements but most importantly their interpretation. Students work with real data sets from research laboratories, Marquette athletes and other large datasets including kinetics and kinematic data, performance data and physiologic data, which provides a rich learning environment with ample opportunities to network with prospective stakeholders. Students will also be trained in systems currently being used at Marquette such as Dexalytics and Catapult.
Graduates will be uniquely qualified to meet the challenges we face in analysis, management and use of large data sets and trained in the ethical considerations of collecting, managing and analyzing large data sets to make human performance decisions. This program is timely as the National Institutes of Health has identified a lack of tools and insufficient training in data science as an impediment to rapid translation of impact, decreasing our ability to advance the understanding of human health and disease.
Take the next step towards your future
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Contact Us
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Application Details
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Program Faculty
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Course Work
Application Deadline
This program has rolling admission, which means you may apply any time before the following dates:
- Fall term admissions - August 1 (June 1 for international applicants)
Your application must be complete and all required documentation must be received in the Graduate School by the above date.
Application Requirements
Read all application instructions prior to beginning an application.
- A completed online application form and fee.
- Copies of all college/university transcripts except Marquette.*
- A curriculum vitae including work history, formal education, continuing education, licensing and certification, professional organizations, honors and awards, publications, presentations and grants.
- A personal statement of no more than 500 words addressing your purpose for applying to the program, your ability to successfully complete the program and your goals (short and long term).
- Three letters of recommendation addressing the applicant’s academic, professional, clinical, personal attributes and potential for meaningful graduate study. At least one academic reference must be included.
- GRE scores. GRE scores are only required if degree GPA is below 3.000.
- For international applicants only: a minimum acceptable score on the iBT TOEFL exam of 90 overall, with minimum section scores of 25 for listening and speaking, and minimum scores of 20 for reading and writing, or other acceptable proof of English proficiency.
- Applicants may wish to submit one example of written work, such as a class project, course assignment, first author publication, grant application, etc. (optional).
- An interview with the admission committee is mandatory.
* Upon admission, final official transcripts from all previously attended colleges/universities, with certified English translations if original language is not English, must be submitted to the Graduate School within the first five weeks of the term of admission or a hold preventing registration for future terms will be placed on the student’s record.
THESIS OPTION (PLAN A)
The master's student in Plan A must complete the required courses in data science (15 credits), the required courses in human performance/exercise physiology (12 credits), and 6 credits of thesis, for a total of 33 credits.
NON-THESIS OPTION (PLAN B)
The master's student in Plan B must complete the required courses in data science (15 credits), the required courses in human performance/exercise physiology plus electives (15 credits), and 3 credits of project, for a total of 33 credits.
REQUIRED COURSE WORK FOR PLAN A AND PLAN B
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| COSC 5500 |
Advanced Data Science |
3 |
| COSC 5820 |
Ethical and Social Implications of Data |
3 |
| COSC 6510 |
Business Intelligence |
3 |
| COSC 6520 |
Business Analytics 1 |
3 |
| or COSC 6540 |
Data Analytics |
| COSC 6570 |
Data at Scale 2 |
3 |
| or COSC 6060 |
Parallel and Distributed Systems |
| or COSC 6380 |
Advanced Database Systems |
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|
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| EXPH 5192 |
Advanced Exercise Physiology |
3 |
| SPRT 6110 |
Advanced Applied Biomechanics in Injury Prevention and Performance |
3 |
| SPRT 6190 |
Advanced Strength and Conditioning: Data Analytics |
3 |
| SPRT 6958 |
Readings and Research in Sports and Exercise Analytics (taken once) |
0 |
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9 |
| Total Credit Hours |
33 |
ADDITIONAL COURSE REQUIREMENTS PLAN A (THESIS)
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3 |
| SPRT 6999 |
Master's Thesis |
6 |
| Total Credit Hours |
9 |
ADDITIONAL COURSE REQUIREMENTS PLAN B (NON-THESIS)
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6 |
| SPRT 6600 |
Project Design and Development in Sports and Exercise Analytics |
1 |
| SPRT 6998 |
Professional Project in Sport and Exercise Analytics |
2 |
| Total Credit Hours |
9 |
We Are Marquette · Advancing Human Performance
Dr. Kristof Kipp - Exercise Science
