Sports Franchise Simulation

Students typically have four preconceived beliefs about sports economics at the start of a sports economics course:

1. They believe that owners will spend very large sums to get the best possible team.
   
2. Free agency has made rich teams the best.
3. A reverse-order draft equalizes teams in a sports league.
   
4. Probability plays a small role in explaining which teams win and lose.

It is often difficult to get students to understand the errors in these beliefs with analytical arguments, however well presented. By making each student, or a group of students, a franchise owner and simulating a season, students must come to grips with the decisions that must be made in running a sports franchise and how these decisions lead to outcomes that are contrary to their beliefs.

While this example was developed for a sports economics course, the microeconomics foundation of the simulation makes it a valuable example to an intermediate microeconomics insturctor looking for an active application example to use in class.

This example is not appropriate for a large lecture class.

Students often have difficulty grasping the role of probability in computer simulations. This simulation uses sets of playing cards. A student's talent is represented by the cards in the student's deck (King high, ace low). In selecting (bidding for) the "owner deck," students are constrained by given revenue functions based on the win-loss percentage.

Surdam provides a full discussion of his initial revenue endowments and simulation variations in the Journal of Economic Education article referenced below. Students first bid for franchises, each of which has a different revenue function. They next secretly chose the quality of their team and pay differential prices related to the quality selected. The highest quality, King quality, receives a full deck. The lowest quality, Ace quality, receives only four aces. Students can also choose to invest a portion of their revenue in a bond instead of "talent." The instructor sets up a league season of games, assigning home and away teams at each game. Games are played by each owner shuffling their deck of cards. The high card wins the game, with a tie going to the home team.

TIME REQUIREMENTS:
Instructor preparation: Approximately two hours to read the article and prepare class materials.
Class preparation: Thirty minutes.
Class simulation: One or two 50 minute class periods, depending on instructor preference and coverage of topics.

The basic simulation structure parameters can be varied by the instructor: the bond interest rate can be increased or decreased, the revenue functions can be changed. Variations are also easily introduced: a revenue sharing clause can be added, franchises can relocate, a salary cap can be introduced, and so on.

The major instructional issue in implementing the example is the time it takes to simulate multiple seasons in class. Once the structure of the simulation is understood, however, an instructor can generate multiple seasons away from class and bring the results in to discuss. The structure of the simulation could also be programed and used in class once students understood the importance of the "draw" from the deck of cards being a probability statement about winning and losing.

Surdam lists a set of 10 questions he uses with his students after they have used the simulation. These questions provide a good starting point for an instructor using the simulation for the first time, and also give some feedback on how students have behaved. Examples are:

"What factors did you consider when bidding for franchises? Did you weigh the extra profitability of owning New York versus the foregone interest from investing more of your capital in the bonds? Even in the initial bidding, my students realized that expending all of their capital for the New York franchise was not profit maximizing. A couple of students in my class hung back in anticipation of getting St. Louis franchises for the minimum price..."

"Given your team's revenue function, does your team have increasing, decreasing, or constant marginal revenue product?"

In addition, all traditional assessment tools can be used. For more information about assessment, see the SERC assessment module.

Surdam, D. G. (2009). A Sports Franchise Simulation Game. Journal of Economic Education, 40(2), 138-149.