Most of you will be familiar with the concept of a demand curve. They are typically downward sloping and look like this:
As an engineering student, I always thought it was odd that price (the independent variable) was on the vertical axis and quantity (the dependent variable) was on the horizontal axis, but I got over it.
A demand curve represents the quantity demanded over the range of possible prices. As price is increased, the quantity demanded will naturally decrease. Hence the downward slope.
Each team has their own unique demand curve. The slope of the curve is related to the elasticity of demand, i.e., Fan Loyalty. If a team has fiercely loyal fans (low elasticity of demand), the slope will be quite steep; the quantity demanded will change very little with price. If Fan Loyalty is low (high elasticity of demand), the slope will be more horizontal, yielding large changes in quantity demanded for small changes in ticket price. When I taught microeconomics, I would use crack cocaine as an example of a good with very low elasticity of demand and lobster as an example of a good with very high elasticity of demand. Perhaps Taylor Swift tickets might be a more contemporary example of low elasticity.
As Fan Interest changes over time, the demand curve will shift to reflect this. Assuming Fan Loyalty remains constant, an increase in Fan Interest will shift the demand curve to the right. This is called an “increase in demand.” At any given ticket price, more tickets will be sold. If Fan Interest decreases, the demand curve will shift to the left, representing a “decrease in demand.” At any given ticket price, fewer tickets will be sold.
We can use the demand curve to forecast total gate revenue, which is simply the product of ticket price and the quantity of tickets sold at that price. This is represented by the area under the demand curve.
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