After Theo Epstein’s run as general manager with the Boston Red Sox, some critics remained unconvinced of the power of analytics in baseball.
No matter that the Red Sox won the 2004 World Series under Epstein, the team’s first championship since 1918. Then, they won another under Epstein’s management in 2007.
In 2011, Epstein became president of baseball operations for the Chicago Cubs. Unlike Boston, the Cubs were a bottom of the division team when Epstein took over. By 2016, they had won their first World Series in 108 years.
As in Boston, Epstein took a data-driven approach to running the Cubs.
“The great analytics war ended end at 48 minutes after midnight on Nov. 3, 2016,” wrote sports site The Ringer. That’s when the Cubs pulled out a thrilling Game 7 World Series victory over the Cleveland Indians.
For those interested in data analytics, it was a night to remember.
The revolution for analytics in baseball started with Bill James’ publication of “statistical abstracts” on the game from 1977 to 1988. James went beyond such well-known measurements as batting average and earned run average, delving into more sophisticated ways of judging players. He coined the term sabermetrics to describe his efforts.
Some of his empirical analysis resulted in new measurements. On-base percentage accounted for how often a player reached base, whether by a hit, walk or getting hit by a pitch. Slugging percentage calculates the total number of bases reached by a hitter and divides by the number of at-bats.
Both have proven a better barometer of a player than batting average, which simply divides hits by numbers of at bats.
And that was just the beginning. Eventually, Billy Beane and the Oakland Athletics brought James’ ideas onto the field in the early 21st century, as documented in “Moneyball.” The team used advanced metrics to get a better understanding of the value of a player.
Both the “Moneyball” book by Michael Lewis and the film starring Brad Pitt offer data analytics students and professionals a glimpse into the difficulties of selling data-driven strategies to entrenched veterans who are comfortable with long-held philosophies.
Data can make a team better. But that’s not always the way others view it.
Baseball provides a great example of this in action.
Analytics in Baseball After the Red Sox
Even after Epstein proved the value of a data-driven approach to baseball in Boston, other teams were reluctant. Some on the St. Louis Cardinals staff gave data-driven general manager Jeff Luhnow a difficult time because of his new ideas on evaluating players.
He’s now with the Houston Astros and has built a winner using a data-driven approach to analytics in baseball.
In fact, every professional baseball organization now has an analytics person on staff. Some have whole teams.
However, whether individual teams actually put data-derived strategies into action is the source of debate. But the Cubs and Red Sox clearly do. It’s not a surprise that in the final month of the season, both teams look to make the playoffs again.
No team will discuss exactly how they use data. The competition is that fierce. But attentive fans can’t help but notice that numbers must be behind certain deals.
For example, take the first trade Epstein made as GM of the Red Sox. He traded superstar Nomar Garciaparra to shore up the team’s defense. At the time, media coverage focused on the sudden trade of the team’s best player. But Epstein knew the team could not win with a poor defense.
He said straightforwardly, “We weren’t going to win a World Series with our defense.” The newly structured team won the World Series that year.
Epstein also famously told Cubs ownership that the team would be ready to compete for a championship in 2016. Five years later, that’s the year they won it all.
Many are watching closely as data-driven teams seem on a collision course in the playoffs. The Los Angeles Dodgers are led by Andrew Friedman and Farhan Zaidi, who used unconventional analytics to build winners in Tampa Bay and Oakland, respectively.
The Cubs, Red Sox and Astros also all seem destined for the playoffs.
What does the future hold? Both sports fans and those interested in analytics will be watching.