Master's in Sports and Exercise Analytics

Attend a Virtual Information Session at Marquette University

Attend Our Information Session: April 24, 2024

Join us for an Information Session for our Sports and Exercise Analytics program. You will have an opportunity to meet with the Director of the Program and the Graduate Admissions Counselor as we discuss program highlights, curriculum and the application process. There will be plenty of time for Q & A, so have your questions ready.

The Information Session will be held on Wednesday, April 24, 2024 at 6:00 PM CST. Please RSVP at the link below.  We look forward to seeing you there!

RSVP for this session

Step up your game in the sports and exercise field

Apply classroom knowledge with an industry internship.

Read one student’s experience as a football data and analytics intern for the NFL.

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.

 

  

33

Total Credits

2

Years to Complete*

PO

Part-time and Online Options**

 

 

 

 

 

*Based on full-time student  | **Hybrid program with online and on-campus courses.

 


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Learning Outcomes

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).  

Career Opportunities

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


 

  • Request Information
  • Admission Requirements
  • Application Details
  • Admission Requirements
  • Program Faculty
  • Course Work 

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:

The Sports and Exercise Analytics program can accomodate students from a wide variety of disciplies, 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:
  • 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. 

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)

Paula Papanek Marquette UniversityDr. 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. Kristoff Kipp Marquette UniversityDr. 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. Matt HawkeyDr. Matthew Hawkey - Clinical Associate Professor of Exercise Science

Matt Hawkey joined the Department of Physical Therapy, Sport and Exercise Science Analytics at Marquette University in the fall of 2022.

Matt has over 20 years of sport and performance analytics industry experience. He has served in a variety of roles built around the use of data analytics to help improve human performance. Hs experience spread across professional, collegiate, and youth sport and military domains includes serving as a data and sport scientist, director of performance and analysis, and coach. His PhD focused on providing a framework to support athlete selection in professional soccer.  Utilizing a wide variety of technology and data sources, Matt’s applied focus and research primarily investigates how human performance data and sport analytics can best profile, monitor, and forecast athlete performance to improve organizational decision making.

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


Dr. Walter BialkowskiDr. 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   

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

ADDITIONAL COURSE REQUIREMENTS PLAN A (THESIS)

Elective 3
SPRT 6999 Master's Thesis 6
Total Credit Hours 9

ADDITIONAL COURSE REQUIREMENTS PLAN B (NON-THESIS)

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 Sports and Exercise Analytics 2
Total Credit Hours 9

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