Sports Analytics

Program Overview

Decision-making in the companies we work at and in our personal lives is increasingly data-driven. The business and practice of sports management is no different, except for the sheer quantity of data involved. Whether it is linking an athlete’s performance to compensation, designing better methods for spatiotemporal player tracking, or visualizing performance metrics for in-game and post-game analysis, folks involved in the management of player and team data have multiple decisions to make every day.

For those who are currently in management or coaching, or for those who wish to break into the field of sports analytics, we offer a novel program that combines the best of academic rigor, software development, and data management in a student-focused graduate certificate. Our educational model is informed by our experience in combining risk-management tools and project-based learning in training students at the undergraduate level for the better part of the past decade. Combining instruction from our dedicated faculty and guest lectures from alumni and industry partners, the MSU Graduate Certificate in Sports Analytics is designed to train the next generation of analysts who will become the leaders of the field of sports analytics in the decades to come.

The Michigan State University Graduate Certificate in Sports Analytics is a 12-credit program that combines best practices in data sourcing and model development with a clear understanding of why model may, or may not, suit the data collected. To earn the certificate, students will complete four 3-credit courses, which include topics in:

- Algorithm design and analysis
- Statistical Computation and Visualization
- Quantitatively Informed Decision Making Tools in Sports Analytics
- Project design and presentation.

Program Outcomes

Graduates of the certificate will be ready to work at the interface of sports management and machine learning. This course of study is designed with the understanding that models must impact the bottom line of an athletic organization, which is winning championships and increasing revenue. Our program meets the needs of current industry professionals who want to step up their data game as well as anyone who wants to understand the numbers more deeply behind their passion for sports. The certificate will be a valuable credential in our graduates’ portfolio and will demonstrate the certificate holder’s commitment to improving in-game, post-game, and revenue analysis in the competitive, interdisciplinary field that is sports analytics.

Career Outlook

The training and experience gained through the certificate is designed to impact graduates’ careers in two possible ways. First, for professionals who are already in the field, within a team, agency, or league, graduates will be able to formulate and address data-savvy questions for the groups they currently manage. By being able to contribute at different stages of the model development and testing cycle, their employers will gain a competitive edge during the season and other stages of planning, such as free-agency or revenue forecasting. Second, students looking to break into the field will gain exposure to the demands of the field of sports analytics via class and project work. This collaborative project work will also expand their network of industry connections if they partner with students in the certificate who are already in the industry.

Course Information

MTH 801 - Machine Learning Algorithms: Mathematical Analysis (3)

Introduction to the mathematical basis of machine learning and predictive analytics. Linear and ridge regression, principal component analysis, classification methods, and neural networks. Convergence of algorithms.

STT 832 - Data Visualization and Programming in R (3)

Development of sports data predictive models. Extraction and management of sport data, graphical and numerical summaries using visualization tools to model practical sports scenarios. Compilation of written reports on test results and performance outputs.

MTH 803 - Sports Decision Analytics (3)

Theories of sports decisions are developed and assessed through quantitative and stochastic techniques.

STT 834 - Sports Analytics Capstone (3)

Development of quantitative models, based on complex sports-related data sets, to support personnel or revenue-based decision-making from the perspective of a coach, manager, or player agent. Reports, presentations, and code repositories will be delivered.

Admissions Requirements

To be accepted to this program, you must have:

• Bachelor’s degree from an accredited college or university
• Have some exposure to college-level mathematics (calculus and linear algebra) OR be willing to take part in preparatory instruction in mathematics and statistics before the first course in the certificate.
  
• Taken the TOEFL. (Only required if English is not your native language)
  
• A written personal statement
• A minimum of three letters of recommendation from academic or professional contacts. Provide contact information for your recommenders and the MSU application system will provide instructions to them.
  
• Official transcripts from all previous schools
  

To apply to this program:

• Complete a university graduate application
• A non-refundable $65 application fee is required.
• Request official transcripts from each institution attended. Your application is not complete until we receive your official transcripts.

International Students:

• For non-US citizens without permanent residency status whose first language is not English, have English language proficiency test scores (TOEFL or IELTS) electronically sent to the MSU Office of Admissions directly from the testing agency.
• MSU's TOEFL code is 1465.
• Also, review MSU's international requirements here: https://grad.msu.edu/internationalapplicants. Do not have testing reports mailed to the university or Department of Mathematics.