Engineering
INTERACTIVE SESSION MANAGEMENT Big Data Baseball Big data and analytics are sweeping the business base running, and stealing. Skill in fielding is espe- world, and the professional sports industry is no cially valued today. For example, Mike Trout, center exception. Baseball, football, soccer, hockey, ten- fielder for the Los Angeles Angels, is highly regarded nis, and even sailboat racing are finding ways to by team owners because he's an exceptional fielder analyze data about players and competing teams in and base runner and an exceptionally intelligent order to improve performance. The use of analytics base ball player, even though he lacked stellar sta- and big data has revolutionized the game of base- tistics in home runs. Today the biggest challenge is ball as we know it, including defensive shifts, swing not whether to use big data in baseball but how to path changes, and how teams acquire and develop use it effectively. It is not always possible to inter- players pret the data and separate out what is "noise" and Given the huge disparities in Major League what is actually actionable information. The amount Baseball (MLB) team budgets, wealthier teams typi- of data players and pitchers must deal with can be cally have the advantage in recruiting the best play- overwhelming-pitch usage, swing planes, spin rates, ers. Michael Lewis's book Moneyball, published in etc. When a player steps into the batter's box, every 2003, describes how Oakland Athletics manager Billy hitter is different in terms of how much information Beane was able to turn the underdog A's into a win- that person can absorb before getting bogged down in ning team by using big data analytics to guide deci- it. Some want to know what a pitcher will do in cer- sions about which players to recruit and cultivate. tain situations-what pitches the pitcher will use and Rigorous statistical analysis had demonstrated that how often that person uses them-while some want on-base percentage and slugging percentage were to just step in with a clear head and look for the ball. better indicators of offensive success and cheaper There's only so much data a person can use without to obtain on the open market) than more historically dissecting too much and getting too distracted from valued qualities such as speed and contact. These the task at hand. observations flew in the face of conventional base Many baseball experts still believe that tradi- ball wisdom and the beliefs of many baseball talent tional methods of player evaluation, along with gut scouts and coaches. Beane rebuilt the A's based on instinct, money, and luck, are still key ingredients these findings, producing a consistently winning for winning teams. For example, the San Francisco team for a number of years by using advanced ana- Giants use big data and statistics, but also base their lytics to gain insights into each player's value and player recruitment decisions on the opinions of contribution to team success that wealthier teams scouts and coaches. According to Giants bench coach had overlooked Ron Worus, numbers really can't tell the whole story Big data is credited with helping the Boston Red about the quality of the player; so the Giants inte- Sox win the World Series in 2004 and the St. Louis grate statistical data with scouting, coaching, and Cardinals win in 2006 and 2011. To varying degrees, player experience, especially when dealing with op- every Major League Baseball team today uses big ponents outside the National League that the Giants data and deep analytics to support decisions about do not see regularly. Being able to exploit an indi- many aspects of the game. However, some teams, vidual player's strengths comes more from knowing such as the Pittsburgh Pirates, Chicago Cubs, and the player and his ability as opposed to the statistics, Houston Astros, were slower to do so than others, Wotus believes. Shortstops with good arms can play and suffered lackluster performance until they em- farther from home plate than normal at times, while braced big data more fully fast runners can play closer to home plate than Findings from big data analytics have changed the usual. There are nuances to defending the opposition importance baseball teams attach to specific skills of that are not statistically related, but statistics help players Skills that previously could not be quantified when you don't know players well enough to know are now receiving more attention, including fielding what to expect from them. CASE STUDY QUESTIONS 1. How did information technology change the game 3. How much should baseball rely on big data and of baseball? Explain. analytics? Explain your answer. 2. How did information technology affect decision making at MLB teams? What kinds of decisions changed as the result of using big data?