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University of Michigan

Sports Performance Analytics

University of Michigan via Coursera Specialization


Sports analytics has emerged as a field of research with increasing popularity propelled, in part, by the real-world success illustrated by the best-selling book and motion picture, Moneyball. Analysis of team and player performance data has continued to revolutionize the sports industry on the field, court, and ice as well as in living rooms among fantasy sports players and online sports gambling. Drawing from real data sets in Major League Baseball (MLB), the National Basketball Association (NBA), the National Hockey League (NHL), the English Premier League (EPL-soccer), and the Indian Premier League (IPL-cricket), you’ll learn how to construct predictive models to anticipate team and player performance. You’ll also replicate the success of Moneyball using real statistical models, use the Linear Probability Model (LPM) to anticipate categorical outcomes variables in sports contests, explore how teams collect and organize an athlete’s performance data with wearable technologies, and how to apply machine learning in a sports analytics context. This introduction to the field of sports analytics is designed for sports managers, coaches, physical therapists, as well as sports fans who want to understand the science behind athlete performance and game prediction. New Python programmers and data analysts who are looking for a fun and practical way to apply their Python, statistics, or predictive modeling skills will enjoy exploring courses in this series.


Course 1: Foundations of Sports Analytics: Data, Representation, and Models in Sports
- Offered by University of Michigan. This course provides an introduction to using Python to analyze team performance in sports. Learners will ... Enroll for free.

Course 2: Moneyball and Beyond
- Offered by University of Michigan. The book Moneyball triggered a revolution in the analysis of performance statistics in professional ... Enroll for free.

Course 3: Prediction Models with Sports Data
- Offered by University of Michigan. In this course the learner will be shown how to generate forecasts of game results in professional sports ... Enroll for free.

Course 4: Wearable Technologies and Sports Analytics
- Offered by University of Michigan. Sports analytics now include massive datasets from athletes and teams that quantify both training and ... Enroll for free.

Course 5: Introduction to Machine Learning in Sports Analytics
- Offered by University of Michigan. In this course students will explore supervised machine learning techniques using the python scikit learn ... Enroll for free.


Taught by

Christopher Brooks, Peter F. Bodary, Stefan Szymanski, Wenche Wang and Youngho Park


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