In Moneyball: The Art of Winning an Unfair Game (New York: W.W. Norton and Company, 2011. Print), American author and journalist Michael Lewis artistically blends business and sports together in a story focused on finding the secret of being successful in baseball. Lewis tells the story of how the Major League Baseball team Oakland A’s, under the management of former player Billy Beane succeeded in transforming not only their own organization into a cost-efficient winning machine but revolutionized Major League Baseball as a whole. Despite a complete lack of knowledge about baseball from my part, Moneyball managed to catch my eye with its content’s relevance to both business and sports. Also, in a world where success at any cost is starting
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One of these examples is Bill James, generally considered the father of sabermetrics, whose ideas were dismissed for years before earning the respect they deserved. When James published his first Baseball Abstract in 1977, he only sold 75 copies, but as Lewis puts it in the book “[i]t didn’t occur to him to be disappointed by a sale of seventy five copies; he was encouraged”(72-73) and that “[n]o author has ever been so energized by so little”(73). James continued to publish a new copy of his Baseball Abstract annually until 1988 and both the number of sales and the amount of respect he was given increased for each year. The other example is about Billy Beane, who – despite giving up his professional baseball career sooner than he would have had to – showed great determination as the general manager when he decided to continue previous general manager Alderson’s work and fully implement sabermetrics into the Oakland A’s organization. He fired scouts who did not believe in the methods, he traded stars and other players who did not live up to their dollar value for nobodies with sabermetrics statistics to back them up. His determination paid off, as the Oakland A’s gained some success doing it, finishing first in their division in 2002, despite having one of the lowest payrolls in the …show more content…
For example, one of the principles of scientific management refers to the careful selection of workers who possesses the skills and abilities most suitable for a certain task. This is very similar to what Billy Beane and the Oakland A’s used sabermetrics for. However, instead of searching for the worker best suited for a certain task, they used the data collected to search for players with the skills they considered crucial in order to win ball
One of these examples is Bill James, generally considered the father of sabermetrics, whose ideas were dismissed for years before earning the respect they deserved. When James published his first Baseball Abstract in 1977, he only sold 75 copies, but as Lewis puts it in the book “[i]t didn’t occur to him to be disappointed by a sale of seventy five copies; he was encouraged”(72-73) and that “[n]o author has ever been so energized by so little”(73). James continued to publish a new copy of his Baseball Abstract annually until 1988 and both the number of sales and the amount of respect he was given increased for each year. The other example is about Billy Beane, who – despite giving up his professional baseball career sooner than he would have had to – showed great determination as the general manager when he decided to continue previous general manager Alderson’s work and fully implement sabermetrics into the Oakland A’s organization. He fired scouts who did not believe in the methods, he traded stars and other players who did not live up to their dollar value for nobodies with sabermetrics statistics to back them up. His determination paid off, as the Oakland A’s gained some success doing it, finishing first in their division in 2002, despite having one of the lowest payrolls in the …show more content…
For example, one of the principles of scientific management refers to the careful selection of workers who possesses the skills and abilities most suitable for a certain task. This is very similar to what Billy Beane and the Oakland A’s used sabermetrics for. However, instead of searching for the worker best suited for a certain task, they used the data collected to search for players with the skills they considered crucial in order to win ball