My last post discussed how we can use data as a casual fan, but data is also used a lot in the professional side of sports. This topic is discussed in detail in the film moneyball. Moneyball is a true story about a man named Billy Beane who was the General Manager of the Oakland Athletics baseball team. The team did not have as much money as the other, bigger teams, such as the Boston Red Sox, and the New York Yankees. Proving to be a competitor would have been very hard without looking at data. He used data to get replacements for all stars. Since MoneyBall is all about baseball, I would like to give a football example of how data is used in professional leagues. Imagine that there was a safety that was targeted 100 times, and made a pass breakup 75% of the time, but he is requesting $2,000,000, but another safety was targeted 100 times, made a pass breakup 65% of the time and is requesting $750,000. If you have the money to pay $2,000,000 to one player, then that would be the obvious choice, but let's say you only had $1,500,000 then the second safety is the better choice. The second choice is better, because although he does not break up the pass 10 times comparatively, the safety is more cost-effective. This similar thing can be used in all sports.
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