movie Money Ball discussion, business and finance homework help

Please reply to my classmates post for example you might start hi nice post i think …..

Post 1 Shannon wrote this:

In the movie Money Ball, Billy Beane a former baseball player himself and Peter Brand a graduate from Harvard wanted to change the game of baseball.  Billy had decided that he was tired of making it to the “last” game and not winning.  At the end of that last season, the team lost 2 key players and need to have them replaced.  Using the BI of the statistics and analytics they were able to build a team solely off of the numbers and not the players ability to play the game itself.  Not everyone was in agreement which meant that they were going to face some challenges.  In addition to the players, the media and even other scouts and coaches Billy continued to believe in the method that he used.  Peter whole heartedly believed in the program 100% which made Billy decide that they did not need to prove themselves to anyone else.  BI was also able to provide them with the additional information they needed on the other teams in the organization.  This information gave them the ammo in a sense to use when it was time to trade players.  In the end, the Oakland A’s still did not will that World Series pennant like they had wanted but they did in change the game.  Billy was offered a healthy salary to leave the A’s and go to Boston to be the general manager for the Red Sox.  He declined the offer and stayed on with Oakland.  To Billy, it was never about the money.  He just wanted to enjoy the game and make a difference.

If I were the general manager of a sports team I would definitely try the BI that Billy Beane did in this movie. I would want to have the best team that I thought would be able to win the game at hand.  I would also want to look at this from a long term point of view as well.  In using the analytics that were prevented in the movie, I would be able to use this in other aspects of the company as well.  As an example, it can be used in merchandise, ticket sales to labor agreements and player contracts. 

Even in today’s world these analytics are being used.  in the NBA, data analytics is what drove the contract talks at the end of the lockout in December 2012.  I think that this is just the beginning and it will get stronger and better as the time goes on.  Technology and BI go hand in hand and will continue to only be improved.

http://www.informationweek.com/software/information-management/analytics-drives-next-generation-of-moneyball-in-sports/d/d-id/1103255?

Post 2  Daniel post this:

The Oakland A’s organization from the major-league baseball got smarter by using business intelligence by focusing on on-base averages for players. Billy Beane and Paul DePodesta came to the conclusion that looking at players batting averages was not a proper method of analyzing potential players for their team. They began to focus on how many times on average each player was to get on base. They used business intelligence to apply certain methods to decipher through the data and find the players that had the best on base average. This method helped him to find better quality players for their organization.

I would use business intelligence in a similar fashion to manage a specific sports team. For example, for basketball I would develop a method of analyzing the different players and how they could generate points for the team. Looking at each potential player and what their scoring potential is for each prior season and analyzing this data. I would also want to analyze how often these players are getting hurt during the season. This would help to figure out the best possible athletes that can be used on the team.

References: 

De Luca, M., Horovitz, R., & Pitt, B. (2011). Moneyball. United States: Columbia Pictures. 

Sharda, R., Delen, D., Turban, E. (2014). Business Intelligence A Managerial Perspective on Analytics, 3rd ed. Pearson Education.

http://www.forbes.com/sites/benkerschberg/2011/11/01/manufacturing-moneyball-using-big-data-and-business-intelligence-to-spur-operational-excellence/2/#79844a9f505b