Defensive shifting, in baseball, started as a trend several years ago and is rapidly becoming core strategy with major league baseball teams with the advent of complex predictive technology.
The player positions in baseball has always been such that first-baseman stands at first base, the left-fielder positions himself in left field. Now teams are aided with player profiles of rival teams and placing their infielders and outfielders in spots where they are most likely to catch that player’s hits, based on data about past performance.
Baseball Info Solutions (BIS), is the modern data analysis firm, housed in a former movie theatre on a residential street in Coplay, Pennsylvania, which provides the requisite player background and profile that makes the defensive shift away from locked positions possible.
“Shifts make a ton of difference,” says BIS vice-president Ben Jedlovic. “Absolutely. In fact, last year the leading shifting teams — teams like the Rays and the Brewers — saved between 10 and 15 runs just by shifting.” His data team is comprised of hard-core baseball fans, who watch hours of live and taped baseball, recording detailed information about individual players and selling the aggregated results to Major League teams.
Complete our SAP x Data Natives CDO Club survey now, and help us to help you
A lot of the players are unable to alter their batting patterns and to their disadvantage, although the spots hit to, may vary depending on where the players are in the strike count, but their hits remain predictable. With this kind of data readily available teams can defend against these hitters by placing potential catchers in those precise spots. It’s why there are now far fewer frantic dashes to catch fly balls.
On the downside, this takes away some of the drama and unpredictability from the game, which many fans believe, is ruining baseball.
The defensive shift strategy has seen an uprise since 2010, with 2,400 shifts in Major League games. It doubled to 4,500 in 2012 and to 8,100 in 2013. If numbers are to be believed, teams have already surpassed that this season, with predictions they’ll hit 13,000 shifts by the end of the World Series.
There are others who would say that, while big data may be taking over the game, economics could ultimately undo the big shift. Nobel-winning economist Robert Lucas briefs that teams will compensate for the big defensive shift by doing things such as scouting players who are unpredictable.