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M A X I M E H U N A U L T , E R I C M O O R E , N I K K H OS H A N D I T T H A
World Cup 2014: Should we sponsor Brazil?
Questions
We are representing Nike:
Given a fixed budget of $110M/year, is it worth to sponsor Brazil for the next 3 years knowing that the World Cup will happen next year?
If so, how should we sponsor them to reduce risk and improve profitability?
Background Information
32 teams qualify for World Cup
16 teams advance for tournament play
Step 1: Determining Brazil’s Win Probability
Why?
Number of Games Played
Number of Viewers
Overall Market Potential
General Structure Example: Brazil
Method
Win Probability
Team Score
80% Weight
FIFA Ranking
60% Weight
Elite Players
40% Weight
Match History
20% Weight
Historical Win-Loss
Percentage
Brazil Win Percentage against NL:
53.8%
Adjusted Team Score as
Probability: 53%
FIFA Ranking: 10
Elite Player Ranking: 5
Historical Win Percentage: 4/7
= 57.14%
Brazil is 4-3 against
Netherlands
Brazil’s Win Percentage by Match
Brazil vs. Netherlands (4 Games): 53.8%
Brazil vs. Uruguay (5 Games): 50.0%
Brazil vs. Germany (6 Games): 40.1%
Brazil vs. Spain (7 Games): 34.7%
Step 2: Estimating the size of the market for Brazilian jerseys
Factors for Analysis
Rounds
Revenue
Countries
Nike Product
Population
Penetration
Price
The model: Calculating Revenue / Person
The model:Calculating Grand Total
Outcome
$53,231,408.06
$168,895,316.08
$435,229,007.57
$806,580,325.46
$1,199,224,206.58
$1,941,926,842.36
$-
$500,000,000.00
$1,000,000,000.00
$1,500,000,000.00
$2,000,000,000.00
$2,500,000,000.00
1 2 3 4 5 6
Revenue (In Millions)
Step 3: Computing the expected profitability under different scenarios
Main assumptions of our financial model
Revenues Costs
For year 1• Based on the probabilities to go
through each round
• Based on the potential markets With a different scope depending on the
number of games played With different penetration rates in each
round
For years 2 and 3• We knew that sales were going to
drop after the ‘World Cup effect’
• Decline in sales is affected by the worldwide economic context
Sales Decline (as % of year 1 sales)
Economy Crisis Thriving Probability
Years 2 & 30,50 0,70 0,60
0,60 0,80 0,40
Variable costs• 35% of sales
Fixed costs• Distribution: $15M• Marketing: $12M• Overheads: $7M• Cost of sponsorship was fixed and
variable, depending on the scenarios
We took into account inflation for distribution, marketing and overheads costs
Inflation - Fixed costs (%)
Economy Crisis Thriving Probability
Years 2 & 31% 4% 0,60
2% 6% 0,40
Scenario 1: fixed sponsorship of $110M
Round 1 Round 2 Round 3 Round 4 Round 5 Round 6
Probability of the scenario
100% 100% 54% 27% 11% 4%
NPV (Millions) $ -285,37 $ -150,22 $160,98 $ 594,89 $ 1 053,68 $ 1 921,50
Mean: $29,6M
Std Dev: $62,1M
‘31,8% chance of losing money’
Scenario 2: $90M upfront + $20M after round 2
Mean: $127,3M
Std Dev: $63,3M
‘0 % chance of losing money and significant
increase in profit’
Round 1 Round 2 Round 3 Round 4 Round 5 Round 6
Probability of the scenario
100% 100% 54% 27% 11% 4%
NPV (Millions) $ -232,68 $ -83,76 $ 211,11 $ 689,22 $ 1 194,74 $ 2 150,97
Scenario 3: $90M upfront + $10M after round 2 + $10M if they win the final
Mean: $147,5M
Std Dev: $61,4M
‘Opportunity to generate $20M more profit’
Round 1 Round 2 Round 3 Round 4 Round 5 Round 6
Probability of the scenario
100% 100% 54% 27% 11% 4%
NPV (Millions) $ -238,76 $ -107,41 $ 171,04 $ 592,78 $ 1 038,69 $ 1 858,14
Conclusion
We would probably sponsor Brazil based on our model
The best way to do it to provide a mix of fixed and variable fees
Reduces risk (scenarios 2 and 3)
Increases profit (scenario 3)
Probably gives an incentives to motivate players
Although we know that our model is a simplification of what happens in real life
We tried to capture the true essence of the problem as much as possible
There could be elements missing (full tournament simulation in particular, opportunity to sponsor other teams…)
Scenario 3 is the most appealing
