Master's in Sports and Exercise Analytics

Ready to learn more about Marquette's sports and exercise analytics graduate program? 

Request more information now or schedule an on-campus visit.

Graduate Program Recruiter

Tim Carter

phone: (414) 288-7139

email: tim.carter@marquette.edu 

Email the Graduate School

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To be eligible for admission to the Graduate School at Marquette University, applicants must meet the following requirements:

• A bachelor's degree from a regionally accredited institution or international equivalent must be completed prior to starting graduate school.
• A minimum grade point average (GPA) of 3.00 on a 4.00 scale.
• Demonstrated English proficiency for non-U.S. citizens.

The Sports and Exercise Analytics program can accommodate students from a wide variety of disciplines, including exercise science, kinesiology, anatomy and physiology, sports management, business management, computer science, data science, engineering and many other related disciplines. 

Completion of the following coursework is required: 

1. Computer programming course (e.g. COSC 1010 Introduction to Software Development at Marquette).
2. Statistics course (e.g. MATH 1700 Modern Elementary Statistics at Marquette).
3. Course in exercise physiology, anatomy, or similar. 

Contact the Graduate Admissions Counselor for this program for further clarification on any of these required courses. 

Application Requirements

Read all application instructions prior to beginning an application.

• A completed online application form and fee.
• Transcripts:
  • If coursework was completed within the United States, submit copies of all current and previous college/universities except Marquette¹
  • If coursework was completed outside of the United States, a transcript evaluation is required. A copy of a course-by-course evaluation is approved for the application process.²
• 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 TOEFL score or other acceptable proof of English proficiency. An overall TOEFL score of 90 with minimum scores of 25 for listening and speaking and minimum 20 for reading and writing.
• 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.} 

Students begin their studies in the fall of each academic year. This program has rolling admission, which means you may apply and submit application materials any time before the following dates:

• Fall term admissions – August 1 (June 1 for international applicants)

Dr. Paula Papanek - Professor and Director of the Sports and Exercise Analytics Program

Paula Papanek is the founding director of the Sports and Exercise Analytics Program and the Exercise Science Program 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

Dr. Kristof Kipp - Associate Professor of Exercise Science

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.

Dr. Kipp’s academic and research interests revolve around sports science and biomechanics. He also helps direct Marquette University’s Motion Analysis and Biomechanics Laboratory.

For more information on Dr. Kipp, please visit the Physical Therapy Department page

Dr. Walter Bialkowski - Assistant Professor of Practice

Dr. Bialkowski is trained as a clinical epidemiologist and translational data scientist. He first worked professionally as a Project and Program Manager in resuscitation research involving out-of-hospital cardiac arrest, traumatic brain injury, and hypovolemic shock clinical trials. He later moved into a Program Director role in the field of transfusion medicine and led several projects including observational and interventional clinical studies.

As an educator, Dr. Bialkowski prioritizes applied learning of data science skills. Students in his classes, and those involved in his research program, apply data science skills through individual assignment and project work. His courses engage with students across disciplines, including sports and exercise, criminal justice, accounting, healthcare, and many professional industries.

For more information on Dr. Bialkowski, please visit the Computer Science Department page

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   

ADDITIONAL COURSE REQUIREMENTS PLAN A (THESIS)

ADDITIONAL COURSE REQUIREMENTS PLAN B (NON-THESIS)