Sports Analytics
Graduate Certificate
Graduate Certificate
Course Delivery
Total Credits
Credit Hour
Minimum Duration
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.
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.
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.
Albert Cohen is the Director of MSU’s new Certificate in Sports Analytics. Albert received his doctorate in mathematical sciences from Carnegie Mellon University in 2007. A lifelong hockey, soccer, and football fanatic, Albert has been combining his passion for sports with his love for, and training in, applied mathematics by working with undergraduates and MSU Hockey to develop an analytics group for the team. Recently, Albert has started working on professional sports analytics with long-time colleague and certificate program co-founder, Trevor Nill via Spartan Analytics. Building on his experience partnering with industry to build training programs in data science, and his academic research and instructional experience in quantitative finance and insurance, Albert has helped design a curriculum that will maximize the impact of the new certificate in sports analytics.
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.
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.
Theories of sports decisions are developed and assessed through quantitative and stochastic techniques.
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.
International Students:
Application Deadline
August 1st
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.
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.
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.
Albert Cohen is the Director of MSU’s new Certificate in Sports Analytics. Albert received his doctorate in mathematical sciences from Carnegie Mellon University in 2007. A lifelong hockey, soccer, and football fanatic, Albert has been combining his passion for sports with his love for, and training in, applied mathematics by working with undergraduates and MSU Hockey to develop an analytics group for the team. Recently, Albert has started working on professional sports analytics with long-time colleague and certificate program co-founder, Trevor Nill via Spartan Analytics. Building on his experience partnering with industry to build training programs in data science, and his academic research and instructional experience in quantitative finance and insurance, Albert has helped design a curriculum that will maximize the impact of the new certificate in sports analytics.
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.
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.
Theories of sports decisions are developed and assessed through quantitative and stochastic techniques.
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.
International Students:
Application Deadline
August 1st
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