Beyond Moneyball: How Big Data Is Changing Baseball
Big data first came on the scene around seven years ago, and already it’s making a sizeable impact in how teams operate and make important decisions. As big data analytics become more widespread, those who follow baseball closely can expect some changes in how the sport is played, how organizations manage personnel, and how fans experience the game.
Ever since the days of Moneyball, advanced statistics have had a large influence on team strategy and personnel decisions. But despite the advances, stats were still recorded in the traditional way through observation.
That has all changed with the arrival of big data at the baseball stadium. The amount of data being generated today is mind-blowing. In fact, one baseball game is close to generating up to 1TB of data. This is all possible thanks to new technologies dedicated to data generation, which include high-speed video equipment and even doppler radar.
The technology is similar to what’s used by other sports, like in the NBA and NFL, only with a focus finely-tuned to baseball.
For example, about 20 different pieces of data are recorded with every pitch, ranging from pitch velocity to the angle of the pitcher’s arm. While generating that much data in one game may sound impressive, it’s really only scratching the surface of big data’s true potential, with some experts predicting advances will push data generation to as much as 7TB per game.
Generating and recording the data is only the first step in the process. Teams still need to analyze and apply it to get the most use out of it; and that’s where some of the latest systems like PITCHf/x and HITf/x come in.
Through these systems, teams are able to track player performance and go far beyond surface statistics. This also gives them a better view of a player’s value, which can be crucial when making decisions on who to trade or who to move up from the minor leagues. Big data analytics also gives teams a clearer look at how players perform under very specific circumstances along with a better analysis of player-batter matchups. Big data is also shaping strategic decisions, such as how managers construct their starting lineups and who they use for pinch hitting.
One of the biggest ways big data is changing baseball is in the defensive game. The past few years have seen the widespread use of what are called “defensive shifts.” Based on big data analysis, teams can determine where opposing batters will likely hit the ball. Infield coaches can then give signals to players to shift to a better area, depending on the player coming up to bat. The success of this use of data has lead to more teams adopting it and using it more often. In 2010, about 2,400 defensive shifts happened in MLB contests.
That number had increased to more than 8,000 by 2013. Some purists have expressed their dislike for the tactic, but all indications point to defensive shifts continuing.
Big data may also end up changing the fan experience as well. Baseball has always been a stat-driven game, so league officials and broadcasters are looking at the possibility of big data renewing interest in the sport. Part of that is the greater access to the cloud that customers have.
So what is cloud computing and how does it help big data and baseball?
The cloud is basically the internet, where people are able to connect to it through the mobile devices they own. Cloud computing helps store and process data, which can prove pivotal when watching a baseball game. Accessing big data analytics from a smartphone to study and analyze a game all in real-time may help fans understand baseball on a deeper level, which can, in turn, produce more enjoyment from it.
The rise of big data may represent a major change in the Major League. Strategies and decisions often hinge on what big data shows, and it may even be used to help fans have more fun while watching the game.
We’re still in the early stages of big data adoption, but as more teams invest in the infrastructure and fine-tune their analysis, baseball could transform right before our eyes.
Some opinions expressed in this article may be those of a guest author and not necessarily Analytikus. Staff authors are listed http://www.sporttechie.com/2014/11/11/sports/mlb/beyond-moneyball-how-big-data-is-changing-baseball/