Sports Analytics Specialization
This specialization, offered only online, provides technical and leadership training required for key positions in sports team management and analytics. It provides an understanding of how to work in sports management roles in today’s data-intensive and data-driven world. 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. Students pursuing the Sports Analytics specialization are required to take the four-course, online predictive analytics sequence below to fulfill both core and elective requirements. MSA electives do not qualify for this specialization.
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.
- PREDICT 401-DL Introduction to Statistical Analysis (Students complete Predict 401-DL in lieu of MSA 401 Sports Research Methods & Quantitative Analysis)
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.
This course examines statistical and mathematical models in sports. With a focus on sports selected by the instructor, the course introduces player performance measurement and how to value the contribution of individual players to teams. It shows how to apply statistical, mathematical, and simulation methods in player selection, team composition, and injury forecasting. The course shows how to rate team competitive strength, build winning teams and predict the probability of winning in any particular competition. Game day coaching strategies and play calling are addressed. This is a case study- and project-based course involving extensive programming and sports performance data analysis. This course begins with a review of the fundamentals of sports performance measurements and analytics. The course focuses on basic rules and parameters of the sports selected by the instructor. The course reviews principles of each of the positions of athletes in each of the sports, the use of accurate assessments for each sport, and variability due to factors such as body type, climate and playing surface. It reviews athletic performance measurements such as jumping ability, running speed, agility, and strength. It discusses exploratory data analysis, predictive modeling and presentation graphics, showing real-world implications for athletes, coaches, team managers and the sports industry. Prerequisites: PREDICT 400-DL and PREDICT 401-DL.
This course provides a comprehensive review of statistical and mathematical models as they relate to sports team administration, marketing and business management. The course gives students an opportunity to work with data relating to sports business tactics and strategy. Students explore alternative segmentation schemes for targeted marketing. They employ modeling methods in sports team marketing communications, ticket pricing, loyalty and sponsorship program development, and customer relationship marketing. This is a case study- and project-based course involving extensive programming and sports team business data analysis. Prerequisites: PREDICT 400-DL and PREDICT 401-DL.