Purpose of this Project
The goal of this project is to create a working simulator for fictional baseball leagues. The simulator should accept various player, team, and league parameters from the user and generate pseudo-random results based on these inputs, with the ability to generate result reports at the end of the simulation.

Advisors
Dr. David Pankratz (Computer Science)
Dr. Kevin Quinn (Economics)

Project Details
The study of sports from an economic standpoint is based around how teams allocate scarce resources (money/talent) to satisfy unlimited wants (wins and revenue).  However, the value that is placed on winning versus profit maximization may vary from team to team.  Furthermore, how a team evaluates players, that is, the decisions that go into determining the worth of a player to a team may vary across franchises.  As teams vary how they go about scouting, signing, and utilizing players to meet their desired goals, team performance, and thus league balance, changes based on net effects of team decisions.  Lastly, leagues may impose specific rules to affect who a team can or cannot sign, how many players are available to sign, the amount of money that can be spent on player salaries, and even the number of teams in the league. 

Different management philosophies working within different league parameters result in various performances by league teams, changing player salaries, competitive balance variations, etc.  As professional sports typically operate on a one season/year basis, real-world data is slow to generate, and large samples are frequently hard to gather for the purpose of studying the effects of certain economic philosophies/parameters on sporting results.  Therefore, the ability to control and simulate sports philosophies and performance would be greatly appreciated by the field.  

The goal of the project is to write a program to create, maintain, simulate, and report data for fictional baseball leagues for the purpose of economic research and study.  Given a selection of players with varying performance statistics, a user should be able to create a league, set the parameters or rules of the league, fill it with a certain amount of teams containing a certain amount of players, and adjust the “focus” or philosophy of each team, whether it is profit maximization or winning.  Teams should also have a philosophy for signing players in terms of statistics or performance measures they emphasize.  With the various “philosophies” in place, the program should fill team rosters within the criteria set by the teams and league, along with a bit of randomness. 

Once the teams are created, a user should be able to simulate seasons for the league, generating results with appropriate team and player statistics, along with financial data. Lastly, the user should be able to gather the results of the simulation for the purpose of study, hence summary data, such as competitive balance, average salary; etc should be available either readily or as a computation.  The user should be able to alter the parameters of a league or team between simulations, as well as manage more than one league at a time.  

With such a software package available, a researcher will be able to run hundreds of simulations for various league and team structures,  resulting in a breadth of data that is both random, yet stochastic enough to be of value in testing economic theories. 

Required Reading

Moneyball
by Michael Lewis

The Mythical Man-Month
by Fred Brooks