Evan Gattis took a circuitous route to major league baseball. His…

amandadeeley293 Evan Gattis took a circuitous route to major league baseball. His…Evan Gattis took a circuitous route to major league baseball. His path to becoming a 26-year-old-rookie on the 2014 Atlanta Braves’ roster has earned comparisons to Roy Hobbs, the mythical baseball player central to the novel and movie The Natural.  As in the story of Roy Hobbs, Gattis dropped completely out of baseball for several years before returning in a big way.  In his first month in the major leagues, he hit six home runs and was named the National League’s Rookie of the Month.  He duplicated both feats in his second month – he hit six more home runs and was again named the National League’s Rookie of the Month.  But what is most unusual about Gattis is that he may be the first major league baseball player to give credit to management science and decision analysis for his success.While in the minor leagues Gattis began reading the work of University of Texas Professor J. Eric Bickel, who has used decision analysis to determine the optimal decisions for a hitter to make in each count. “One paper I wrote was how to act on different pitch counts,” Bickel said.  “Sometimes the batter will just let a pitch go by on purpose.  If it’s three balls, no strikes, a lot of times the coach will say, ‘Don’t swing at the pitch, no matter what.'”What Bickel said is that most people don’t understand why a batter would take a pitch on a 3-0 count. Because one more ball will result in a walk and put the batter on first base, under these circumstances the opposing pitcher will usually put a very hittable fastball through the heart of the strike zone on the next pitch.  However, Bickel’s research demonstrates why taking a pitch when the count is three balls and no strikes rather than swinging at what will likely be a very hittable pitch increases the probability the batter will ultimately get on base.”About 38% of all batters eventually get on base,” Bickel said. “At 3-0, 77 percent of batters eventually get on base.  Suppose you’re sitting there with a 3-0 count.  If you let the pitch go by, and the pitcher throws a strike, you’re down to a 63% chance of getting on.  If you instead put that ball in play, you only have a one-third chance of getting on base, or take a strike and still have a 63 percent chance of getting on base.  That’s why you take it.”Bickel has used decision analysis to determine a batter’s optimal strategies for all ball-strike counts. His decision analysis and his lucid explanation of the resulting ball/strike counts have helped shape the way Gattis approaches each pitch when he is at bat.*Based on Joe Lemire, “The Photo Is Just One Good Reason You Need to Know the Story of Evan Gattis,” Sports Illustrated (June 10, 2013) . There has been a lot of attention on using data analytics for recruiting players and determining strategies (including the book Moneyball by Michael Lewis and the resulting blockbuster film Moneyball (2011)). What are your thoughts on using data and analytics for decision making within sports?  ( also discuss the “business of sports”.) Can you give other examples in baseball or other sports where mathematical decision making or data analytics is used to make “better” strategic decisions to improve the success of the team and/or athlete? BusinessBusiness – Other