Math behind Moneyball from Coursera

What's inside

Syllabus

Before you start...

Module 1

You will learn how to predict a team’s won loss record from the number of runs, points, or goals scored by a team and its opponents. Then we will introduce you to multiple regression and show how multiple regression is used to evaluate baseball hitters. Excel data tables, VLOOKUP, MATCH, and INDEX functions will be discussed.

Module 2

You will concentrate on learning important Excel tools including Range Names, Tables, Conditional Formatting, PivotTables, and the family of COUNTIFS, SUMIFS, and AVERAGEIFS functions. You will concentrate on learning important Excel tools including Range Names, Tables, Conditional Formatting, PivotTables, and the family of COUNTIFS, SUMIFS, and AVERAGEIFS functions.

Module 3

You will learn how Monte Carlo simulation works and how it can be used to evaluate a baseball team’s offense and the famous DEFLATEGATE controversy.

Module 4

You will learn how to evaluate baseball fielding, baseball pitchers, and evaluate in game baseball decision-making. The math behind WAR (Wins above Replacement) and Park Factors will also be discussed. Modern developments such as infield shifts and pitch framing will also be discussed.

Module 5

You will learn basic concepts involving random variables (specifically the normal random variable, expected value, variance and standard deviation.) You will learn how regression can be used to analyze what makes NFL teams win and decode the NFL QB rating system. You will also learn that momentum and the “hot hand” is mostly a myth. Finally, you will use Excel text functions and the concept of Expected Points per play to analyze the effectiveness of a football team’s play calling.

Module 6

You will learn how two-person zero sum game theory sheds light on football play selection and soccer penalty kick strategies. Our discussion of basketball begins with an analysis of NBA shooting, box score based player metrics, and the Four Factor concept which explains what makes basketball teams win.

Module 7

You will learn about advanced basketball concepts such as Adjusted plus minus, ESPN’s RPM, SportVu data, and NBA in game decision-making.

Module 8

You will learn how to use game results to rate sports teams and set point spreads. Simulation of the NCAA basketball tournament will aid you in filling out your 2016 bracket. Final 4 is in Houston!

Module 9

You will learn how to rate NASCAR drivers and get an introduction to sports betting concepts such as the Money line, Props Bets, and evaluation of gambling betting systems.

Module 10

You will learn how Kelly Growth can optimize your sports betting, how regression to the mean explains the SI cover jinx and how to optimize a daily fantasy sports lineup. We close with a discussion of golf analytics.

Final Exam

Final exam has 10 questions. Please download and open Excel files before taking the exam. You will be referred to Excel files during the exam. Each question is wort 1 point. You need to answer 6 questions or more correctly to pass the exam.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Provides an edge in understanding sports-related topics across fields such as mathematics, probability, and statistics

Covers a comprehensive study of sports-related topics, from analyzing player metrics to simulating tournament outcomes

Suitable for learners with an interest in sports analytics and improving team performance

Taught by Professor Wayne Winston, recognized for his expertise in sports analytics

Involves the use of Excel tools and concepts for data analysis and player evaluations

May require prior knowledge of Excel and statistical concepts

Reviews summary

Moneyball mathematics

According to students, enjoyable activities and statistical analysis make this a great course for beginners interested in the application of math to sports. That said, issues with course navigation and missing content lower its rating.

Course topics are engaging and relevant for beginners interested in sports analytics.

"If you enjoy statistics and sports, this is an excellent course."

"I did learn a fair amount from it"

The Coursera platform is difficult to navigate.

"Coursera platform is not well thought out and cumbersome to navigate."

Lack of instructor engagement and missing course content hinder learning.

"This course is very low quality in terms of its engagement with students"

"What this course lacked was the ability to engage in dialogue with the instructor."

"Test 18 provided a dead link for how we were supposed to solve the problem and there was no instruction on how to complete otherwise."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Math behind Moneyball with these activities:

Review Basic Statistics

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Review the fundamentals of probability, expected value, and variance to strengthen your foundation for this course.

Browse courses on Probability

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Revisit textbooks or online resources on probability and statistics
Solve practice problems related to mean, median, and mode

Work through practice problems related to probability and statistics

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Reinforce your understanding of probability and statistics through repetitive exercises, improving your ability to solve problems related to sports analytics.

Browse courses on Probability

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Find a collection of practice problems
Solve the problems using the concepts covered in the course
Review your solutions and identify areas where you need improvement

Read 'The Mathematics of Baseball' by Alan Reifman

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Understand the mathematical principles behind baseball statistics, helping you better grasp the concepts covered in the course.

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Obtain a copy of the book
Read the book in its entirety
Take notes on key concepts and formulas
Apply the concepts to real-world baseball data

Five other activities

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Learn advanced Excel functions and techniques

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Enhance your ability to analyze sports data by mastering advanced Excel functions and techniques, such as data manipulation, pivot tables, and macros.

Browse courses on Excel

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Find online tutorials or courses on advanced Excel
Follow the tutorials and practice using Excel to solve problems related to sports analytics
Apply the techniques to analyze your own sports data

Create a fantasy baseball team

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Apply your knowledge of baseball statistics and player evaluation to make informed Entscheidungen in a fantasy baseball league.

Browse courses on Player Evaluation

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Join a fantasy baseball league
Research player statistics and projections
Draft a team of players
Manage your team throughout the season

Discuss sports analytics concepts with peers

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Engage with other students to exchange ideas, clarify concepts, and enhance your understanding of sports analytics through collaborative learning.

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Join a study group or online forum for the course
Participate in discussions and ask questions
Share your own insights and perspectives

Create a video tutorial explaining a sports analytics concept

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Solidify your understanding of a sports analytics concept by creating a video tutorial that explains it in a clear and engaging way, benefiting both yourself and others.

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Choose a concept to explain
Write a script for the video
Record and edit the video
Share the video online

Develop a data visualization dashboard for a sports team

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Apply your data analysis skills to create a comprehensive data visualization dashboard that tracks team performance, player metrics, and other relevant data, providing valuable insights for decision-making.

Browse courses on Data Visualization

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Gather data from various sources
Clean and prepare the data
Choose appropriate visualization techniques
Develop the dashboard using a data visualization tool

Career center

Learners who complete Math behind Moneyball will develop knowledge and skills that may be useful to these careers:

Baseball Analyst

A course on 'Math behind Moneyball' is highly relevant for a Baseball Analyst. Baseball Analysts use mathematical and statistical models to analyze baseball data, evaluate players, and make predictions about game outcomes. They need to have a strong understanding of probability, statistics, and baseball. This course can help Baseball Analysts develop the skills needed to analyze data, make predictions, and make informed decisions about baseball teams and players.

See salaries and explore the career path for Baseball Analyst

Business Analyst

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Operations Research Analyst

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Statistician

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Software Engineer

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Data Analyst

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Financial Analyst

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Quantitative Analyst

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Actuary

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Risk Manager

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Economist

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Sports Agent

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Data Scientist

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