movie Money Ball discussion, business and finance homework help

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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

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