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.
Part-time and Online Options**
*Based on full-time student | **Hybrid program with online and on-campus courses.
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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
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.
Read all application instructions prior to beginning an application.
- A completed online application form and fee.
- 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).
- A virtual interview with the admissions committee may be needed.
1Upon 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.
2Upon admission, an official course-by-course transcript/academic record evaluation 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
||Advanced Data Science
||Ethical and Social Implications of Data
||Business Analytics 1
|or COSC 6540
||Data at Scale 2
|or COSC 6060
||Parallel and Distributed Systems
|or COSC 6380
||Advanced Database Systems
||Advanced Exercise Physiology
||Advanced Applied Biomechanics in Injury Prevention and Performance
||Advanced Strength and Conditioning: Data Analytics
||Readings and Research in Sports and Exercise Analytics (taken once)
|Total Credit Hours
ADDITIONAL COURSE REQUIREMENTS PLAN A (THESIS)
|Total Credit Hours
ADDITIONAL COURSE REQUIREMENTS PLAN B (NON-THESIS)
||Project Design and Development in Sports and Exercise Analytics
||Professional Project in Sports and Exercise Analytics
|Total Credit Hours
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