University of Wyoming Men’s Basketball Team Case Study Solution
Forecasting Total Revenues for 100 Seasons using Simulation Model
It is obvious to use the 50 percent wining ratio for calculating revenues over 100 simulation seasons. It can be seen through analyzing revenues on the basis of the 100 seasons that the revenue of the team are depending upon the performance of the team. The simulation model is based upon an average team win of 0.5 with average number of tickets sold of eight conference and non-conference games equals to 947.125 and 1173.625 respectively.
It can be anticipated that the team would perform exceptionally well throughout season, due to which the demand of the tickets would be increasing, hence generating revenue for the athletics department or university by increasing the price of ticket.
The previous data 16 game season data is split into two categories i.e. conference and non-conference. The simulation formula is used to calculate the number of tickets sold for the conference and non-conference and then it is multiplied with the price of ticket to get the revenue. The total revenue of the 100 seasons using simulation is $203186.88.
Forecasting Total Revenues with Random Winning Percentages Using Simulation Model
The revenue generation process has been determined by using simulation model for different seasons. In 2006-2007, the winning percentages of the team was 0.619, for 2007-2008 it was 0.4, for 2008-2009 it was 0.643 and between 2009 and 2010, the winning percentage was 0.323.
In addition to this, the variables have also used in simulation model to identify that in case of increasing the winning percentage, there is a likelihood that the revenue would also be increasing. Also, in case of decreasing winning percentage, the total revenue would be adversely affected. Likely to previous analysis, the revenue is calculated by applying simulation model, the revenue for eight conference and non –conference games are calculated by multiplying price $12 with the 16 games season and number of ticket sold, the revenue is $9625145.
Conclusion
Although, the company has substantial revenues by the previous season but still Bill Sparks faces certain problems in forecasting the actual ticket and concession sales due to uncertainty about the sales. However, these revenues can be forecasted using multiple linear regression and simulation model. The revenues forecasts using these models provide a clear picture about the profitability of the next season to Bill Sparks and other management team.........
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