People who play baseball simulation games have known for years the power of numbers. Often, the choices you make to build a team – and your decisions during a game – are driven by data.
In another words, you go where the numbers tell you to go.
In Major League Baseball, it’s not always that simple. As depicted in the movie “Moneyball,” those who advocate a data-driven approach to baseball often run headlong into the “old guard” who resent someone coming in and trying to change a centuries-old game.
Oakland Athletics General Manager Billy Beane wasn’t the only one to go through it. Jeff Luhnow a former executive with the St. Louis Cardinals and now general manager of the Houston Astros, ran into major roadblocks in St. Louis. Some of the veteran front office people there referred to him as “Harry Potter.” They resented the changes he wanted to make.
Data Friendly Teams in Baseball
Given that, wholly committing to data analytics to make decisions for a ball club is tough. Here are the teams that have made the leap.
While “Moneyball” may have started with the Athletics, it’s seen a new Golden Age in Houston. When the Astros brought in Luhnow in 2011, the team made a complete commitment to using analytics.
How big of a commitment? They completely deconstructed the team and started all over again. Luhnow brought in a former NASA engineer, Sig Mejdal, to help him crunch the numbers. The team built a database, called Mission Control. The front office is filled with data analysts, engineers and at least one physicist. It is the most fully committed deep dive into analytics baseball has ever seen.
If you like an analytical approach to baseball, you have to like the Houston Astros. And it’s paying off – the club has the best record in baseball so far in 2017.
Much has been written about the Cubs, who won the World Series in 2016, and the analytics-driven nature of both general manager Theo Epstein and field manager Joe Maddon. The pair took a 71-wn club and turned it into one that won 103 games during the regular season in 2016.
Epstein has advanced the use of data, partnering with Bloomberg Sports to create new processes for data collection and data mining.
Beane and the A’s were groundbreaking in the use of analytics, but they have a difference with the Cubs: They are cash-strapped. The club continues to use advanced analytics to try to get an edge on other teams while spending far less money. For example, the team payroll for 2017 is $82 million, ranked 27th in the league. Compare that to their Bay area rivals, the San Francisco Giants, who have spent $177 million. The Cubs are spending $172.5 million.
While the data-driven approach has worked in most of the years since the “Moneyball”-era began in 2003 – and manager Bob Melvin has total buy in – the team has hit hard times the last two seasons.
Tampa Bay Rays
One of the few teams that spends less than the A’s – total payroll is $71 million – the Rays also have competed against higher-spending teams in the tough American League East. The Rays went all-in on analytics around 2008, investing in a data research department that, much like the A’s, looks for value in less expensive players. The team reached the World Series in 2008 and have been competitive in the many years since, although like the A’s times have been tougher of late.
These four teams are the best-known for going all-in on analytics, although every team has moved into it to some degree. For those who like the idea of brains beating massive amounts of cash, the Rays and A’s likely should be among your favorite teams.