The book Moneyball triggered a revolution in the analysis of performance statistics in professional sports, by showing that data analytics could be used to increase team winning percentage. This course shows how to program data using Python to test the claims that lie behind the Moneyball story, and to examine the evolution of Moneyball statistics since the book was published. The learner is led through the process of calculating baseball performance statistics from publicly available datasets. The course progresses from the analysis of on base percentage and slugging percentage to more advanced measures derived using the run expectancy matrix, such as wins above replacement (WAR). By the end of this course the learner will be able to use these statistics to conduct their own team and player analyses.
Moneyball and Beyond
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Moneyball and Beyond
This course is part of Sports Performance Analytics Specialization
Instructor: Stefan Szymanski
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Intermediate level
Recommended experience
3 weeks to complete
at 10 hours a week
Flexible schedule
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What you'll learn
Program data using Python to test the claims that lie behind the Moneyball story.
Use statistics to conduct your own team and player analyses.
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Tools you'll learn
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Assessments
15 assignments
Taught in English
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This course is part of the Sports Performance Analytics Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 5 modules in this course
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