Moneyball advantage peters out once everyone's doing it: Rotman paper

April 08, 2019

Toronto - When former Oakland Athletics' general manager Billy Beane used data analytics to build a low budget winning baseball team in the early 2000s, it was so unusual it became the subject of a book and movie.

Sixteen years after author Michael Lewis wrote the book Moneyball, every Major League Baseball (MLB) team uses the technique. But a new study shows that while the tool can help a club create a stronger team - at a lower cost -- it loses its edge once everyone's on to it.

"It's like having a secret sauce," says study author Ramy Elitzur, the Edward J. Kernaghan Professor of Financial Analysis and associate professor of accounting at the University of Toronto's Rotman School of Management. "When you have a secret sauce and nobody else knows about it, you have a competitive advantage. Once the secret sauce was outed, which was what happened with the book, everybody could imitate the Oakland A's."

Dr. Elitzur created a database for the study, inputting information from 1985 to 2013 about team payrolls, playoff success, the spread of data analytics use, and players' overall contributions to their team, represented by a key statistic from Moneyball's "sabermetrics," -- the type of data the Oakland A's used to identify lower-priced, undervalued players through statistics such as how much time spent on base.

He found that between 1997 and 2001, there were only two "Moneyball" teams in the MLB. Another three teams had taken up the practice by 2002. By 2013, more than 75 percent of MLB teams were using it. Sabermetrics gave teams the strongest advantage up until 2003, the year Moneyball was published. By 2008, the comparative advantage was lost as more and more teams adopted sabermetrics. The practice of data analytics also spread beyond sports, to business and government.

The study illustrates that regardless of whether it's sports or another enterprise, "if you have a built-in advantage, don't ever talk about it," says Dr. Elitzur. In the MLB case, "once Moneyball happened, you had a new arms race. There was no way out." However, it did help teams better match their contracts to players' true value, he says, by basing it on less biased information.
The paper is forthcoming in Omega, The International Journal of Management Science.

For the latest thinking on business, management and economics from the Rotman School of Management, visit

The Rotman School of Management is part of the University of Toronto, a global centre of research and teaching excellence at the heart of Canada's commercial capital. Rotman is a catalyst for transformative learning, insights and public engagement, bringing together diverse views and initiatives around a defining purpose: to create value for business and society. For more information, visit


For more information:

Ken McGuffin
Manager, Media Relations
Rotman School of Management
University of Toronto
Voice 416.946.3818

University of Toronto, Rotman School of Management

Related Data Articles from Brightsurf:

Keep the data coming
A continuous data supply ensures data-intensive simulations can run at maximum speed.

Astronomers are bulging with data
For the first time, over 250 million stars in our galaxy's bulge have been surveyed in near-ultraviolet, optical, and near-infrared light, opening the door for astronomers to reexamine key questions about the Milky Way's formation and history.

Novel method for measuring spatial dependencies turns less data into more data
Researcher makes 'little data' act big through, the application of mathematical techniques normally used for time-series, to spatial processes.

Ups and downs in COVID-19 data may be caused by data reporting practices
As data accumulates on COVID-19 cases and deaths, researchers have observed patterns of peaks and valleys that repeat on a near-weekly basis.

Data centers use less energy than you think
Using the most detailed model to date of global data center energy use, researchers found that massive efficiency gains by data centers have kept energy use roughly flat over the past decade.

Storing data in music
Researchers at ETH Zurich have developed a technique for embedding data in music and transmitting it to a smartphone.

Life data economics: calling for new models to assess the value of human data
After the collapse of the blockchain bubble a number of research organisations are developing platforms to enable individual ownership of life data and establish the data valuation and pricing models.

Geoscience data group urges all scientific disciplines to make data open and accessible
Institutions, science funders, data repositories, publishers, researchers and scientific societies from all scientific disciplines must work together to ensure all scientific data are easy to find, access and use, according to a new commentary in Nature by members of the Enabling FAIR Data Steering Committee.

Democratizing data science
MIT researchers are hoping to advance the democratization of data science with a new tool for nonstatisticians that automatically generates models for analyzing raw data.

Getting the most out of atmospheric data analysis
An international team including researchers from Kanazawa University used a new approach to analyze an atmospheric data set spanning 18 years for the investigation of new-particle formation.

Read More: Data News and Data Current Events is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to