Derived Demand for Labor

Unlike many of the other major American sports leagues, baseball teams do not share the majority of their revenue with other teams. Demand for baseball by fans and a team's demand for baseball talent vary depending on the market in which the team operates. To estimate derived demand for labor in baseball, students can collect revenue data (using either television contracts or attendance and ticket prices) and compare that with winning percentages for each time in a given year.

Team revenue is used as a proxy for a team's willingness to pay for talent since teams experiencing higher revenues should have a greater demand for talent in order to preserve their market share. Have students create a spreadsheet with team names in the first column and team revenue in the second column. Sort teams by revenue and then plot that information on a vertical bar chart to show a downward sloping demand curve, with the highest willingness to pay on the left and those with the lowest willingness to pay on the right. Below is the plot generated for the 2019 season:

Demand Curve.png

As the plot above shows, there is a very clear drop-off from the high to the low-revenue teams in baseball. If revenue is a good proxy of the demand for baseball talent, then we should also be able to observe a similar downward trend in win percentage (a measure of team talent) when ordering the teams from highest to lowest revenue. Have students collect data in the third column for a team's winning percentage

Now have students create a scatterplot to show the relationship between winning percentage and revenue. Place the team's winning percentage on the vertical axis and their revenue on the vertical axis, but have the revenue sorted by highest to lowest so that it's matching the same order as the bar chart. Add a trendline to the graph to represent a demand curve. The following scatterplot is based on 2019 data. I've highlighted the Oakland A's as a reference as well.

This is done in the following scatterplot:

Scatterplot.png

We see a clear downward trend in win percentage when teams are ordered from highest to lowest revenue. While it's not a perfect correlation, the relationship is still consistent. It further demonstrates how much of an outlier the Oakland A's are, almost 2 decades after Moneyball. This exercise can also be conducted with On-Base Percentage (OBP) and Slugging Average (SLG) in order to determine whether or not teams that have high revenue demand greater amounts of talent (and thus have a higher willingness to pay for that talent).

Teaching Economics with 

Moneyball