How does an organization create a culture of metrics? One example of organizations that have done so is the baseball community, including its managers, team owners, scouts, players and fans. With better information and analysis baseball teams perform better – they win. Legendary baseball manager Connie Mack, known for 3,776 career victories, has one of the most unbreakable records in baseball. Mack won nine pennants and five World Series titles in a career that spanned the first half of the 20th century. One way he gained an advantage over his contemporary managers was by understanding which player skills and metrics contributed most to winning. He was before his time in that he favored hitting power and on-base percentage players to those with a high batting average and speed – an idea that would later become the standard throughout the sport. Moneyball, the 2003 book about the business of baseball, describes the depth of analytics that general managers like Billy Beane of the Oakland Athletics apply to selecting the best players as well as selecting batter and pitcher tactics based on the conditions of the team scores, inning, number of outs and runners on base. More recently, the general manager of the Boston Red Sox, Theo Epstein, assured himself legendary status by appling statistics to help overcome the “curse of the Bambino” –originating when the team sold Babe Ruth in 1920 to the New York Yankees – to finally defeat the rival Yankees in 2004 and win a World Series. It ended Boston’s 86-year World Series drought.

Gerald W. Sculley was an economist most known for his article, “Pay for Performance in Major League Baseball,” which was published in The American Economic Review in December 1974. The article described a method of determining the contribution of individual players to the performance of their teams. He used statistical measures like slugging percentage for hitters and the strikeout-to-walk ratio for pitchers. He also devised a complex formula for determining team revenue that involved a team’s win-loss percentage and market characteristics of its home stadium, among other factors. The Society for American Baseball Research, of which I have been a member since the mid-1980s, includes arguably the most obsessive “sabermetrics” fanatics. As a result of hard efforts to reconstruct detailed box scores of every baseball game ever played, and load them into accessible databases, SABR members continue to examine every imaginable angle of the game daily. Bill James, one of SABR’s pioneers and author of The Bill James Baseball Abstract, first published in 1977, is revered as a top authority of baseball analytics. I was intrigued by baseball statistics from an early age. As a child I used dice for each player’s at-bat to play hundreds of baseball games. The game involved rolling two dice, each combination of rolls equated to hits, doubles, homers, or outs. The probabilities of the dice combinations in hits were comparable to a typical player’s season batting average.

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