A high-stakes game is taking place in Major League Baseball, and it’s not on the field. It’s in the front office and it involves the use of data.

Every baseball fan one at this point has read the book (and probably seen the movie) “Moneyball” by Michael Lewis. The book details how a statistical approach helped turn the low-budget Oakland Athletics into a contender.

Every fan of baseball simulation games already knew the value of using statistics to make future choices. Some who designed the games, such as Diamond Mind Baseball, have even gone on to success in Major League Baseball.

But now these data wars have reached a new height. With the success in 2016 of the Chicago Cubs, a team that has completely bought into using data in baseball, more teams than ever are using large data sets to determine not only the pitching rotation and hitting lineup, but how to make better in-game decisions.

The 2013 Pittsburgh Pirates

One of the best examples in the last few years of a team using data analytics involves the Pittsburgh Pirates. Their 2013 campaign came as a result of a lot of analytical work.

A 2015 book. “Big Data Baseball: Math, Miracles and the End of a 20-Year Losing Streak” by Travis Sawchik examines the Pirates 2013 season.

That year saw the Pirates end two decades of sub-.500 baseball. The team’s payroll ranked at the bottom of the Major Leagues, attendance was low and no one saw much of a future.

However, the team turned to data analytics in a way beyond just “Moneyball” maneuvers. The Pirates used advanced software systems to gather millions of in-game data points. They then used this data to change small things in their game play that led to big victories.

In reality, getting smarter was the Pirates only choice. Like many teams in baseball, they didn’t have the dollars to go after big free agents in the way teams like the New York Yankees and Boston Red Sox can do.

How The Pirates Used Big Data

The investment in using data started with Neal Huntington, the general manager who has become known for being data-driven. Working with data analysts as well as the coaching staff, the Pirates made quite a few seemingly small changes that resulted in success.

They included:

  • Used “pitch framing” by catcher Russell Martin to help the pitching staff throw more strikes
  • Convincing veteran pitchers such as A.J. Burnett to change how and when they threw certain pitches, based on the data from millions of pitching results
  • Made use of the discovery, again through data research, that many hitters struggle to hit a two-seam fastball
  • Began employing shifts in the defense for certain hitters and pitching situations after data revealed more ground balls could be turned into outs by repositioning the defense

These and other changes led to the best Pirates season in decades. The team made the playoffs in 2013, and went on to make the playoffs again in 2014 and 2015.

Other teams now have bought into data in a big way, and the real battle now is knowing what type of data is the most valuable and how to put it into use. Part of the fun of following baseball is not just the on-field pay, but the off-field maneuvering.