Program Duration: 2 years
Full-time option: Yes | Part-time option: Yes
Hybrid Program: on-campus and online options
ADDITIONAL GRADUATE PROGRAMS
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.
Years to Complete*
Part-time and Online Options**
*Based on full-time student | **Hybrid program with online and on-campus courses.
Check out our latest basketball analytics evaluation in the research lab.
The goal of this program will be to train sports and exercise data analysts to:
Students are prepared to pursue careers in sport and exercise performance data science, including positions at:
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.
Ready to learn more about Marquette's sports and exercise analytics graduate program?
phone: (414) 288-7139
This program has rolling admission, which means you may apply any time before the following dates:
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.
* 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.
Paula Papanek is the founding director of the Program of Exercise Science in the Department of Exercise Science at Marquette University, teaching and training exercise physiologists for over 20 years. Her expertise and knowledge of sports and exercise data analytics will be critical to the success of this program. Her expertise in body composition and bone mineral physiology is linked to athletic injury and performance.
For more information on Dr. Papanek, please visit the Physical Therapy department page
Kristof Kipp joined the Department of Physical Therapy, Program in Exercise Science at Marquette University in the fall of 2011. He received a PhD in nutrition and exercise sciences with emphasis in biomechanics from Oregon State University and completed a post-doctoral research fellowship at the University of Michigan.
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.
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
Data Science Courses
|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|
Human Performance/Exercise Physiology Courses
|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|
|Plan A (Thesis) or Plan B (Non-thesis) - refer to requirements below.||9|
|Total Credit Hours||33|
COSC 6540 recommended for students with a programming background
COSC 6060 or COSC 6380 recommended for students with a computer science background
|SPRT 6999||Master's Thesis||6|
|Total Credit Hours||9|
|Electives - approved EXPH/EXRS/MSSC/COSC courses at 5000 level or higher||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|
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