Teaching Guides

The following teaching guides have been developed by the authors or submitted by other contributors who are using Moneyball in their classroom. Each teaching guide is summarized below and includes the most relevant classes where the guides can be used.

 

If you are using Moneyball in the classroom and would like to contribute to the teaching guides, please reach out to us.

Thinking Like an Economist

Principles

What does it mean when economists encourage people to "think like an economist?" People should be aware of scarcity, but need to make decisions about how much to consume and produce under those constraints.

Derived Demand

for Labor

Labor

The demand for any input is driven by the demand for the output that is produced. Using data on team revenue, students will observe the relationship between winning percentage and revenue the team generates. 

Linear Regression in Python

Econometrics

Harry Bitten has created a guide to replicating pieces of DePodesta's statistical analysis using linear regression in Python. The project is based on data to model the 2002 regular season results.

Marginal Revenue

Product

Principles, Labor, Sports

Using data from MLB and ESPN, students calculate the marginal revenue product of free agents and compare that value to salaries. Students will determine if players are over- or under-valued relative to the player's estimated worth.

Loss

Aversion

Principles, Behavioral

Briguglio, Acchiardo, Mateer, and Geerling have published teaching guides for various film and tv clips that can be used to teach behavioral economics. This guide looks at Billy Beane's aversion to losing.

Intro to Linear Regression
in R

Econometrics

Nick Kaufmann has created a step-by-step lab to look at the relationship between runs scored and other player characteristics. The focus is on interpreting coefficients of a linear regression model.

Constrainted Optimization

Intermediate Microeconomics

Baseball teams have a fixed budget to allocate toward players, who possess particular traits. Moneyball allows an instructor to use the production values of players and the concept of payrolls to teach constrained optimization.

Teaching Advancement Placement Statistics

Statistics

Paul Buckley created a series of exercises to teach AP Statistics using Moneyball. Exercise 1 focuses on a summary of the movie, but Exercise 2 and 3 looks at Pythagorean Expectations and extrapolation. 

Forecasting Wins in Baseball

Advanced Econometrics

James Mundy has created a project that requires students to build a multiple regression model to forecast wins for a team using data from 1871 to 2006. The data has been adjusted to match performance in a standard 162 game season.

Teaching Economics with 

Moneyball

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