Online Course – University of Michigan Certified Professional Internship in Sports Performance Analysis

Internship – 5-part course series

Sports analytics has become an increasingly popular field of study, partly due to the real-world success demonstrated in the hit book and film “Manny Ball.” Analyzing team and player performance data is quickly putting sports on the map for success, both on the field, on basketball and ice courts, and in the living rooms of fantasy players and online sports betting.

Using real data sets from Major League Baseball (MLB), National Basketball League (NBA), National Hockey League (NHL), English Premier League (EPL – Soccer), and Indian Cricket League (IPL), you will learn how to build predictive models to predict crowd and player performance.

Main contents of the course:

• Recreate the success of “Manny Ball” using real statistical models.
• Use the Linear Probability Model (LPM) to predict category results in sports competitions.
• Explore how teams collect and organize athlete performance data using wearable technologies.
• Learn which Machine Learning can be applied in the context of sports analytics.

This introduction to the world of sports analytics is intended for sports managers, coaches, physical therapists, and sports fans who are interested in understanding the science behind athlete performance and game prediction.

Target audience:

• New programmers in the Python language.
• Data analysts looking for a fun and practical way to apply their skills in Python, statistics, or predictive modeling.

Hands-on Learning Project

Learners will apply methods and techniques learned on sports data systems to produce personal results rather than relying on data processing performed by others. As a result, the learner will be given the opportunity to explore their ideas about team performance, test them with the data, and become a producer of sports analysis rather than a consumer.