New Baseball Tech Makes 'Moneyball' Look Like Little League
This post is part of the "Future of Business" series, which examines how cutting-edge technologies are rapidly reshaping our world, from how businesses run to how we live. "The Future of Business" is sponsored by SAP.
See more Future of Business >>
Data geeks revolutionized baseball, as described in Michael Lewis' Moneyball.Now big data is going to revolutionize it even more.
A company called Sportvision has developed FIELDf/x, a means to digitally track and record the position of all players and every hit ball in real time.
By pairing live camera feeds with object recognition and tracking abilities, then feeding its observations to computers, FIELDf/x is able to pull objective, quantitative data from the game.
Baseball generates an astounding number of statistics. How many times does a batter get on base? How many runs does he score per game? How many hits does a pitcher give up while on the mound? The list goes on and on and only gets more specific and specialized. All these numbers are crunched to help coaches and managers determine the best way to set a game's lineup or figure out what kind of pitch is most likely to be successful against a hitter.
And now FIELDf/x is set up to help capture even more data.
For the first time in the 150 years that baseball statistics have been kept, ball clubs will be able to objectively measure how quickly players react to the ball, how quickly they throw it while fielding, and even keep track of where it goes.
Using this method to capture stats for one game of baseball will generate roughly two terabytes of data (2,048 GB). This is huge, but FIELDf/x is able to organize it and derive value from it.
It's a brilliant aid to team owners, coaches and managers. This system will create data that will change how up-and-coming players are scouted and how current players are valued. Ideally, this translates into more wins. The only people it seems like it will hurt are overvalued players and the coaches who display irrational cognitive bias toward them.