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Program Overview

Sports Analytics

Sports Analytics Certificate Program

The Certificate of Advanced Graduate Study in Sports Analytics focuses on the skills necessary to work in today’s data-intensive and data-driven world. This online certificate provides the technical and leadership training required for key positions in sports team management and analytics. Building upon Northwestern University's graduate program in predictive analytics and data science, it reviews key technologies in analytics and modeling, probability theory, applied mathematics, statistics and programming. It shows how analytic techniques may be utilized in evaluating player and team performance and in sports team administration.



About the Sports Analytics Certificate Program

Sports Analytics Course Schedule

The Sports Analytics Course Schedule page provides you with detailed information on the program's offerings.

Sports Analytics Faculty

You can find a full listing of our instructors in this certificate program on the Sports Analytics Faculty page.

Admission for the Sports Analytics Certificate Program

Applicants to this certificate program must hold a graduate degree from an accredited U.S. college, university or its foreign equivalent. A competitive graduate record that indicates strong academic ability is required, though applicants need not have extensive academic experience in public policy. Work experience in the public sector is desirable but not necessary.

A list of admission requirements can be found on our Sports Analytics Admission page.

Sports Analytics Tuition

Tuition costs can vary for each of our programs. For the most up-to-date information on financial obligations, please visit our Sports Analytics Tuition page.

Sports Analytics Registration Information

Our Sports Analytics Registration Information page outlines important dates and deadlines as well as the process for adding and dropping courses.

Find out more about Northwestern's Sports Analytics Certificate Program

Sports Analytics Required Courses

To earn a certificate, students must complete the following four courses. In some cases, students who have previously completed equivalent coursework may be allowed to replace the required course with another course in the field. Graduates of the SPS Data Science program are automatically waived from MSDS 400-DL and MSDS 401-DL and will complete MSDS 450-DL Marketing Analytics and MSDS 455-DL Data Visualization in lieu of these course requirements. 

Please note that courses completed in the certificate program cannot be transferred to the corresponding graduate degree.

Core Courses:Course Detail
Math for Modelers <> MSDS 400-DL

Students learn techniques for building and interpreting mathematical models of real-world phenomena in and across multiple disciplines, including matrices, linear programming, probability, and both differential and integral calculus, with an emphasis on applications. This is for students who want a firm understanding and/or review of these fields of mathematics prior to applying them in subsequent courses. Counts as an elective for students admitted prior to fall 2014. Required as a core course for students admitted for fall 2014 and after.

View MSDS 400-DL Sections
Statistical Analysis <> MSDS 401-DL

Students learn to apply statistical techniques to the processing and interpretation of data from various industries and disciplines. Topics covered include probability, descriptive statistics, study design and linear regression. Emphasis will be placed on the application of the data across these industries and disciplines and serve as a core thought process through the entire Predictive Analytics curriculum.

Prerequisite: PREDICT 400-DL Math for Modelers.

View MSDS 401-DL Sections
Courses:Course Detail
Sports Performance Analytics <> MSDS 456-DL

An introduction to sports performance measurement and analytics, this course reviews roles of athletes at each position in sports selected by the instructor. With a focus on the individual athlete, the course discusses the development and use of accurate assessments and variability due to factors such as body type, climate, and training regimen. The course reviews athletic performance measurements, including jumping ability, running speed, agility, and strength. Students work with player on-field and on-court performance measures. The course utilizes exploratory data analysis, predictive modeling, and presentation graphics, showing real-world implications for athletes, coaches, team managers, and the sports industry.

Prerequisites: MSDS 400-DL Math for Data Scientists and MSDS 401-DL Applied Statistics with R.

View MSDS 456-DL Sections
Sports Management Analytics MSDS 457-DL

This course provides a comprehensive review of financial, statistical, and mathematical models as they relate to sports team performance, administration, marketing, and business management. The course gives students an opportunity to work with data and models relating to sports team performance, tactics, and strategy. Students employ modeling methods in studying player and team valuation, sports media, ticket pricing, game-day events management, loyalty and sponsorship program development, and customer relationship management. The course makes extensive use of sports business case studies.

Prerequisites: MSDS 400-DL Math for Data Scientists and MSDS 401-DL Applied Statistics with R.

View MSDS 457-DL Sections
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