Home Business FOSC main report: How data revolutionized baseball

FOSC main report: How data revolutionized baseball

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The use of data in baseball is much more than fans and commentators who express mysterious facts about the New York Yankees or the Boston Red Sox. Statistical analysis today plays a big role in building the best teams.

Fans, owners and players have a deep emotional connection to the sport – which is why data analysis can be so useful: it can relieve emotions of decision-making. In fact, it helped a team from a small market like Auckland A win six Western League titles in the American League.

“We had a great platform to use data in an emotional, in-house business,” said Billy Bean, Oakland A’s executive vice president of baseball operations. Bean was the keynote speaker during the first day of the FreightWaves Future of the Supply Chain summit in northwest Arkansas.

Founder and CEO of Beane and FreightWaves Craig Fuller on Monday discussed the role the data played in creating a team that won several division titles in the late 1990s and early 2000s.

The story of Bean and others who participated in the Auckland leadership were the subject Michael Lewis’s book “Moneyball: The Art of Winning an Unfair Game”. The book became An Oscar-nominated film in 2012 Brad Pitt played Bean.

The book and film describe Bean’s “Moneyball” philosophy, which examines how organizations can effectively, efficiently, and profitably manage their assets, talents, and resources for short-term and long-term gain.

“We watch sports because we are emotional about it. We make decisions with our eyes. And as executives, we did the same thing, even though all that data was stored for years, ”Bean said.

Bean, a retired baseball player, began his selection in the first round of the New York Mets draft in 1980 before playing six Premier League seasons as an infielder, outfielder and catcher for the Mets, Minnesota Twins, Detroit Tigers and A. His last season was in 1989 as a player at the World Cup in Team A. After working in Front Office A as a Premier League scout, he eventually became the club’s general manager in 1997.

In that role, he hired a Harvard graduate, Paul DePodest, as an assistant CEO. Thanks to DePodesta, played by actor John Hill in the film, Bean switched to using data to acquire talent.

«[By] around the mid-90s, when we moved from one of the teams with the highest salaries to one of the lowest, we had to find another way to act. Otherwise, we were destined to end up where our wages are said, ”Bean said.

FreightWaves CEO and founder Craig Fuller (left) talks to Billy Bean (right), EVP of Oakland A’s. (Photo: Jim Allen / FreightWaves)

This other method was to collect player performance data and then rely on statistical methodologies to help determine the best configuration for the winning team, countering the traditional culture of mind and instinct of the Major League Baseball.

“There was an opinion that we were taking a risk. In fact, we thought it was the other way around. We felt that the use of data gave us answers to the test. We felt mostly conservative, ”Bean said. “We tried to manage the baseball team the way actuaries set insurance rates. So for us, the risk would be to assume if we had information in the form of data. ”

As A’s success grew and his data-informed methods expanded, so did the use of data by competing teams.

After the book was published, the pursuit of statistics became the norm … What eventually happened to us and other teams over the next decade after the book [that it led] really smart people created player performance models and they were all owned. And that’s really what dominated the next decade with a lot of teams, ”Bean said. “And then, ultimately, 10 years later, most teams had their own patented models, very similar to Wall Street firms.”

Although all teams use data to some degree to make decisions, Bean said, traditional approaches still have magic. The use of intelligence as well as data is a powerful combination, he said.

The use of scouts “is a very part of the fabric of baseball, and it dates back to the years when a scout went to look at a player and pass judgment,” Bean said. “With smart people [doing data analysis], we were able to include these considerations …. They are weighed in different ways. “

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