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).
About this Course
- 5 stars63.56%
- 4 stars24.80%
- 3 stars5.42%
- 2 stars3.10%
- 1 star3.10%
TOP REVIEWS FROM FOUNDATIONS OF SPORTS ANALYTICS: DATA, REPRESENTATION, AND MODELS IN SPORTS
Great course. Although this course focuses on sports analysis, the analyzing process I learned from it can apply to any other areas of analysis.
Best course to interact with data representation programming and libraries, especially for the great sports fan.
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
About the Sports Performance Analytics Specialization
Frequently Asked Questions
When will I have access to the lectures and assignments?
What will I get if I subscribe to this Specialization?
Is financial aid available?
More questions? Visit the Learner Help Center.