How Big Data is Transforming Baseball
Over the past few years, even casual baseball fans have noticed changes in the way the game is broadcast. After Michael Lewis published Moneyball in 2003, announcers began sharing previously obscure statistics like on-base percentage and wins above replacement to provide a more complete picture of the game. But lately, thanks to technological advances (and some savvy marketing from Amazon), even newer stats like launch angle, exit velocity, and catch probability have been popping up onscreen.
Since its publication, Moneyball has become shorthand for the trend of using statistical analysis in order to better evaluate baseball players and put together a winning team. As Lewis describes it, the Oakland A’s general manager Billy Beane learned that baseball teams undervalued certain types of successful players, and was able to acquire those players cheaply, a huge advantage for the cash-strapped ballclub.
Soon, other teams quickly caught on to the market inefficiencies that Oakland identified. Meanwhile, an unorthodox group of players, coaches, and tinkerers began to pose a more fundamental question, documented by Ben Lindbergh and Travis Sawchick in their book, The MVP Machine. How can you use data, they wondered, to become a better baseball player?
The 2018 World Series was a showcase for these developments. J.D. Martinez of the Red Sox and Justin Turner of the Dodgers developed changes in their swings to transform from fringe major leaguers into two of the most feared batters in the majors. On the mound, L.A.’s Rich Hill relied on the Dodger coaches who helped him realize that his devastating curveball could turn him from a journeyman to a star at the age of 38.
Meanwhile, the poster child for these developments sat at home in Ohio, his season interrupted by a freak injury and his team eliminated in the first round of the playoffs. Trevor Bauer is a self-described non-athlete whose stubbornness, intelligence, dedication, and confidence helped him become one of the best pitchers in baseball. Lindbergh and Sawchick dedicate much of the book to Bauer, who uses unorthodox training methods to develop pitch velocity. Bauer and his father even purchased a high-speed camera to watch the exact moment pitches left his hand in order to develop a new slider. Some of his former teammates and coaches have found Bauer arrogant (and some unpleasant social media behavior certainly didn’t help) but the authors skillfully describe Bauer’s work ethic without excusing his flaws.
There are a number of other interesting characters in The MVP Machine. Kyle Boddy, a college dropout and former Olive Garden server, built an entire development business from the ground up. Using weighted balls, high speed cameras, and untraditional training, Driveline Baseball is helping to develop the next generation of baseball players. Then there’s Doug Latta, who never made it past adult hardball, but whose focus on swing planes arguably helped develop a revolution in power hitting, turning obscure utility players like Justin Turner into feared sluggers.
This is potentially dry stuff if you’re not a baseball fan. Even if you are, discussion of spin rate and launch angle may not seem interesting. Fortunately, Lindbergh and Sawchick are both talented writers with a lot of experience on the subject. In one amusing chapter, Lindbergh enrolls in Boddy and Latta’s programs. Despite ending his career in eighth grade, he goes through all of their training and evaluation. I won’t spoil the results here.
Lindbergh and Sawchick also raise some issues with this new data-driven MVP Machine world. Take for example the Houston Astros, the team most dedicated to this new method of data-driven development. While many teams believe that traditional scouts retain value in identifying talented players, the secretive Astros front office shed most of their scouts without notice. Lindbergh and Sawchick publish quoted from several sources who feel like this new wave froze them out without ever giving them a chance to get with the program.
There are also issues of consent for minor leaguers, who have no contractual rights to refuse the various trackers that organizations require they wear. Some, like GPS trackers in the field or trackers attached to bats might seem innocuous, but then there are sleep trackers and other off-the-field devices that would be considered invasive for any other employer.
Toward the end of the book, Lindbergh and Sawchick discuss “soft factors” in player development, and I wish they’d spent a bit more time on this subject. For example, franchises, while paying even fringe major leaguers countless millions, often pay minor league players less than a living wage. If they provide minor-league clubhouse meals, they consist of peanut butter sandwiches. Surely some the cost of GPS tracking vests and stadium radar sensors could be better spent on proper nutrition.
In addition, teams acquiring non-American players would certainly benefit from developing programs to acclimate those players to life in America, everything from ESL classes to tax preparation lessons. Regarding nutrition, many Latin major leaguers tell stories of surviving on KFC or Pizza Hut every day because those were the only foods that they knew how to order.
Regardless, Lindbergh and Sawchik have written an indispensable guide to 21st-century baseball. It’s rich in detail and very well told. Many baseball fans are resistant to this sort of data analysis, but it’s now a fundamental part of the game. As baseball writer Joe Sheehan points out, after reading the MVP Machine fans can no longer write off a player’s improvement as a simple hot streak. There may be a fundamental change to that player’s approach, driven by data, that we’re just beginning to understand.
(Basic Books, June 4, 2019)