What Data Scientists Can Learn from Moneyball

Original article was published by Davide Camera on Artificial Intelligence on Medium


What Data Scientists Can Learn from Moneyball

Every Data Scientists should watch the movie Moneyball

According to Wikipedia Moneyball: The Art of Winning an Unfair Game is a book by Michael Lewis, published in 2003, about the Oakland Athletics baseball team and its general manager Billy Beane.

Its focus is the team’s analytical, evidence-based, sabermetric approach to assembling a competitive baseball team despite Oakland’s small budget. A film based on Lewis’ book, starring Brad Pitt and Jonah Hill, was released in 2011.

The central premise of Moneyball is that the collective wisdom of baseball insiders (including players, managers, coaches, scouts, and the front office) over the past century is outdated, subjective, and often flawed.

Statistics such as stolen bases, runs batted in, and batting average, typically used to gauge players, are relics of a 19th-century view of the game and the statistics available at that time.

Before sabermetrics was introduced to baseball, teams were dependent on the skills of their scouts to find and evaluate players.

Photo by Ben Hershey on Unsplash

The book argues that the Oakland A’s’ front office took advantage of more analytical gauges of player performance to field a team that could outsmart and better compete against richer competitors in Major League Baseball (MLB).

Moneyball traces the history of the sabermetric movement back to such people as Bill James (then a member of the Boston Red Sox front office) and Craig R. Wright. Lewis explores how James’s seminal Baseball Abstract, published annually from the late 1970s through the late 1980s, influenced many of the young, up-and-coming baseball minds that are now joining the ranks of baseball management.

Sabermetric

Sabermetrics or SABRmetrics is the empirical analysis of baseball, especially baseball statistics that measure in-game activity.

Sabermetricians collect and summarize the relevant data from this in-game activity to answer specific questions. The term is derived from the acronym SABR, which stands for the Society for American Baseball Research, founded in 1971. The term “sabermetrics” was coined by Bill James, who is one of its pioneers and is often considered its most prominent advocate and public face.