Calculate the price elasticity of demand for each team using the data from the 2017-18 and 2018-19 seasons.

FIN 333: The Economics and Finance of Sport
Case Study 5 – Ticket Pricing and Attendance
Due: 10/28/2022
Points: 80 (10 points per question)
I. Price Elasticity. The following table shows the fan cost index, attendance and team wins for all NBA
teams in the Eastern Conference Atlantic Division for the 2017-18 and 2018-19 seasons.
Fan Cost Index Attendance Wins
Team 2017-18 2018-19 2017-18 2018-19 2017-18 2018-19
BOSTON CELTICS 530.7 562.8 744960 763584 55 49
BROOKLYN NETS 388.4 404.6 622278 612597 28 42
NEW YORK KNICKS 856.0 900.1 792608 779087 29 17
PHILADELPHIA 76ERS 362.2 390.3 833503 838092 52 51
TORONTO RAPTORS 359.9 399.4 813431 812822 59 58
1. Calculate the price elasticity of demand for each team using the data from the 2017-18 and 2018-19
seasons. Recall that the price elasticity of demand is equal to the percentage change in the quantity of
the good demanded divided by the percent change in price. Use the Fan Cost Index as your measure of
price.
2. Create a new measure of elasticity called the “win elasticity of demand” for each team using the data
from the 2017-18 and 2018-19 seasons. Let this elasticity measure be equal to the percentage change in
the quantity of the good demanded divided by the percentage change in team wins.
3. Based on your results to questions 1 and 2, explain how the sports industry might differ from other
industries in regards to the standard relationship between quantity demanded and price. How might the
pricing strategy of a team with a positive price elasticity of demand differ from the pricing strategy of
a team with a negative price elasticity of demand?
II. Variable Ticket Pricing. In 2006, suppose the average ticket price for the New York Mets was $25.28.
The average home game attendance of the Mets for the season was 41,630. Suppose the Mets decide to price
each game so that the average ticket price for each game is the same for every game throughout the season
and equal to the season average ticket price of $25.28. Assume the average ticket price was set so that the
price elasticity of average demand is -1 (profit maximizing). The table below shows the home attendance for
the Mets for 7 games against the division rival Atlanta Braves during the 2006 season.
Date DOW Opponent Day(D)/Night(N) Attendance
20060417 Mon ATL N 36867
20060418 Tue ATL N 30322
20060419 Wed ATL D 40861
20060505 Fri ATL N 47720
20060506 Sat ATL D 48369
20060507 Sun ATL D 48100
20060904 Mon ATL N 42428
4. What was the actual revenue for the Mets in each game against the Braves in 2006 under the above
assumptions? What was the total revenue for these games combined?
5. Using the formulas for the profit maximizing quantity of individual games and profit maximizing price
of individual games re-price each game individually.
ˆ Price Elasticity of Average Demand: ηA = ( PA
QA
) ∗ (
∆QA
∆PA
) = −1
ˆ Profit Maximizing Price Elasticity of Individual Game Demand: ηG = ( PG
QG
) ∗ (
∆QA
∆PA
) = −1
ˆ Profit Maximizing Quantity of Individual Game: QG =
QA+QActual
2
(midpoint of new demand curve)
ˆ Profit Maximizing Price of Individual Game: PG = −1 ∗ QG ∗ (
∆QA
∆PA
) = −1 ∗ QG ∗ (
−PA
QA
)
Additional notation definitions:
ˆ PA = average price per game for the season
ˆ QA = average attendance per game for the season
ˆ QActual = actual attendance for individual game
What is the new price for each game under this variable pricing approach? Hint: First calculate the
profit maximizing quantity of each individual game and then calculate the profit maximizing price of
each individual game using the above formulas.
6. What is the new revenue for each game under this pricing approach?
7. Calculate the difference in revenue under your variable ticket pricing approach and the original average
ticket pricing approach. Which game was variable ticket pricing the most beneficial for? Similarly, which
game was variable ticket pricing the least beneficial for?
8. Compare the total revenue for these games under variable ticket pricing approach to the total revenue
under the average ticket pricing approach. What do you observe? Provide an economic explanation for
your findings.