Foundations of Sports Analytics Data, Representation, and Models in Sports

This course provides an introduction to using Python to analyze team performance in sports. Learners will discover a variety of techniques that can be used to represent sports data and how to extract narratives based on these analytical techniques. The main focus of the introduction will be on the use of regression analysis to analyze team and player performance data, using examples drawn from the National Football League (NFL), the National Basketball Association (NBA), the National Hockey League (NHL), the English Premier LEague (EPL, soccer) and the Indian Premier League (IPL, cricket). This course does not simply explain methods and techniques, it enables the learner to apply them to sports datasets of interest so that they can generate their own results, rather than relying on the data processing performed by others. As a consequence the learning will be empowered to explore their own ideas about sports team performance, test them out using the data, and so become a producer of sports analytics rather than a consumer.

While the course materials have been developed using Python, code has also been produced to derive all of the results in R, for those who prefer that environment.

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Syllabus

Syllabus - What you will learn from this course
Week 1
Introduction to Sports Performance and Data
Week 2
Introduction to Data Sources
Week 3
Introduction to Sports Data and Plots in Python
Week 4
Introduction to Sports Data and Regression Using Python
Week 5
More on Regressions
Week 6
Is There a Hot Hand in Basketball?

FAQ

When will I have access to the lectures and assignments?

Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Reviews

Great course. Although this course focuses on sports analysis, the analyzing process I learned from it can apply to any other areas of analysis.

Great material and well paced for people working. One instructor is a bit green though.

An excellent way to get hands-on experience exploring sports data in Python/R

Best course to interact with data representation programming and libraries, especially for the great sports fan.