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Moneyball and Beyond
  • Level Foundation
  • Duration 29 hours
  • Course by University of Michigan
  • Offered by

About

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.

Modules

Week 1: Lecture Videos

    • 5 Videos
    • 2 Readings
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5 Videos

  • Introduction to Moneyball
  • Reproducing Table 1 of Hakes and Sauer - Part 1
  • Reproducing Table 1 of Hakes and Sauer - Part 2
  • Reproducing Table 1 of Hakes and Sauer- Part 3
  • Reproducing Table 1 of Hakes and Sauer - Part 4

2 Readings

  • Course Syllabus
  • Help Us Learn More About You

Week 1: Lecture Notebooks

    • 1 Lab
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1 Labs

  • Lecture - H&S Table

Week 1: Assignment

    • 7 Readings
    • 1 Lab
    • 3 Assignment
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3 Assignment

  • Week 1 - Quiz 1
  • Week 1 - Quiz 2
  • Week 1 - Quiz 3

1 Labs

  • Assignment 1 Workspace

7 Readings

  • Week 1 - Assignment Overview
  • Assignment - Part 1
  • Sample Notebook - Part 1
  • Assignment - Part 2
  • Sample Notebook - Part 2
  • Assignment - Part 3
  • Sample Notebook - Full Sample

Week 1: R Content

    • 1 Readings
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1 Readings

  • Week 1 R Content

Week 2: Lecture Videos

    • 6 Videos
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6 Videos

  • Reproducing Table 3 of Hakes and Sauer- Part 1
  • Reproducing Table 3 of Hakes and Sauer- Part 2
  • Reproducing Table 3 of Hakes and Sauer- Part 3
  • Reproducing Table 3 of Hakes and Sauer- Part 4
  • Reproducing Table 3 of Hakes and Sauer- Part 5
  • Reproducing Table 3 of Hakes and Sauer- Part 6

Week 2: Lecture Notebooks

    • 1 Lab
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1 Labs

  • Lecture - Moneyball Table 3

Week 2: Assignment

    • 7 Readings
    • 1 Lab
    • 3 Assignment
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3 Assignment

  • Week 2 - Quiz 1
  • Week 2 - Quiz 2
  • Week 2 - Quiz 3

1 Labs

  • Assignment 2 Workspace

7 Readings

  • Moneyball Week 2 - Assignment Overview
  • Assignment - Part 1
  • Sample Notebook - Part 1
  • Assignment - Part 2
  • Sample Notebook - Part 2
  • Assignment - Part 3
  • Sample Notebook - Full Sample

Week 2: R Content

    • 1 Readings
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1 Readings

  • Week 2 R Content

Week 3: Lecture Videos

    • 6 Videos
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6 Videos

  • Moneyball update Part 1
  • Moneyball update Part 2
  • Moneyball Update Part 3
  • Moneyball Update Part 4
  • Moneyball Update Part 5
  • Moneyball Update Part 6

Week 3: Lecture Notebooks

    • 1 Lab
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1 Labs

  • Lecture - Moneyball Update

Week 3: Assignment

    • 8 Readings
    • 1 Lab
    • 3 Assignment
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3 Assignment

  • Week 3 - Quiz 1
  • Week 3 - Quiz 2
  • Week 3 - Quiz 3

1 Labs

  • Assignment 3 Workspace

8 Readings

  • Moneyball Week 3 - Assignment Overview
  • Assignment - Part 1
  • Sample Notebook - Part 1
  • Assignment - Part 2
  • Sample Notebook - Part 2
  • Assignment - Part 3
  • Sample Notebook - Part 3
  • Sample Notebook in R

Week 3: R Content

    • 1 Readings
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1 Readings

  • Week 3 R Content

Week 4: Lecture Videos

    • 4 Videos
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4 Videos

  • Beyond Moneyball: Run expectancy Part 1
  • Beyond Moneyball: Run Expectancy Part 2
  • Beyond Moneyball: Run expectancy Part 3
  • Beyond Moneyball: Run expectancy Part 4

Week 4: Lecture Notebooks

    • 1 Lab
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1 Labs

  • Lecture - Run Expectancy

Week 4: Assignment

    • 8 Readings
    • 1 Lab
    • 3 Assignment
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3 Assignment

  • Week 4 - Quiz 1
  • Week 4 - Quiz 2
  • Week 4 - Quiz 3

1 Labs

  • Assignment 4 Workspace

8 Readings

  • Moneyball Week 4 - Assignment Overview
  • Assignment - Part 1
  • Sample Notebook - Part 1
  • Assignment - Part 2
  • Sample Notebook - Part 2
  • Assignment - Part 3
  • Sample Notebook - Part 3
  • Sample Notebook in R

Week 4: R Content

    • 1 Readings
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1 Readings

  • Week 4 R Content

Week 5: Lecture Videos

    • 4 Videos
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4 Videos

  • Beyond Moneyball: Run values and WAR Part 1
  • Beyond Moneyball: Run values and WAR Part 2
  • Beyond Moneyball: Run values and WAR Part 3
  • Beyond Moneyball: Run values and WAR Part 4

Week 5:Lecture Notebooks

    • 1 Lab
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1 Labs

  • Lecture - From Run Expectancy to WAR

Week 5: Assignment

    • 8 Readings
    • 1 Lab
    • 3 Assignment
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3 Assignment

  • Week 5 - Quiz 1
  • Week 5 - Quiz 2
  • Week 5 - Quiz 3

1 Labs

  • Assignment 5 Workspace

8 Readings

  • Moneyball Week 5 - Assignment Overview
  • Assignment - Part 1
  • Sample Notebook - Part 1
  • Assignment - Part 2
  • Sample Notebook - Part 2
  • Assignment - Part 3
  • Sample Notebook - Part 3
  • Post-Course Survey

Week 5: R Content

    • 1 Readings
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1 Readings

  • Week 5 R Content

Auto Summary

"Moneyball and Beyond" is a foundational Data Science & AI course by Coursera, focusing on sports performance analytics. Taught by expert instructors, it guides learners through programming in Python to analyze baseball statistics, progressing from basic metrics to advanced measures like wins above replacement (WAR). Ideal for sports enthusiasts and data science beginners, this 1740-minute course offers practical skills for conducting team and player analyses, available through a Starter subscription.

Stefan Szymanski
Instructor

Stefan Szymanski