The project aimed to use advanced Excel tools like Solver and Data Analysis ToolPak to maximize the expected return to risk ratio by building a baseball team from a catalog of over 3,000 players with several complex constraints including salary. The project was based on the optimization of the baseball team's lineup to achieve the best possible performance while adhering to a set budget.
The first step in the project was to collect and organize data on all the players in the catalog. This included information such as player statistics, salary, position, and team. The data was then cleaned and formatted to prepare it for analysis.
Once the data was prepared, the project moved on to using advanced Excel tools to analyze the data and optimize the lineup. The Solver tool was used to identify the optimal lineup that maximized the expected return to risk ratio while adhering to the salary constraint. The Data Analysis ToolPak was used to perform statistical analysis on the data to identify patterns and trends that could be used to make more informed decisions.
The project also included a section on data visualization, where the results were presented in an easy-to-understand format using charts and graphs. This helped to clearly identify the best players and positions to optimize the team's performance.
Overall, the project was able to use advanced Excel tools to optimize the baseball team's lineup and maximize the expected return to risk ratio while adhering to a set budget. The project provided valuable insights into how to build a winning team within a set budget and helped the team to make more informed decisions about player selection and lineup optimization.
- Microsoft Excel (Advaned)
- Solver
- Data Analysis ToolPak
