The Bulls signed Dwyane Wade for a two-year contract at the hefty price tag of $47 million. The Miami Heat refused to pay Wade over $40 million while the Denver Nuggets offered him approximately $50 million. While Bulls fans will be welcoming Wade back home, Heat fans will be mourning the loss of arguably the city’s all-time greatest athlete.
I created a Discounted Cash Flow model to evaluate the returns of such a deal. Due to the confidential nature of the NBA, it is difficult to obtain certain information, so some assumptions were necessary for completion.[1]
Findings:
The net present value of the Dwyane Wade deal yields a loss of approximately $6,876,134; however, the market value of the Bulls will increase by about $300 million compared to the previous year. According to Forbes, an NBA team’s valuation is a multiple of team revenue.[2] The projected revenue increase from signing Dwyane Wade will be approximately $30 million. The loss in net income can be justified due to the net change in the team’s enterprise value because the Bulls have an EV/Revenue multiple of around 10 for the year 2016.
Economic Implications:
- The NBA needs a salary cap to balance out the league. Teams that have greater revenue than their competitors have higher revenue to team value multiples. Not only do two teams with the same multiple experience different values due to different company sizes, but these values are also exacerbated by greater multiples. This means that a company/team can incur annual losses (like the Nets) while increasing the team’s market cap, which can’t be done by smaller market teams. Without a salary cap, the more lucrative teams would be able to leverage these multiples and growth potential to outbid the rest of the teams in the NBA. Historically, this is why big market teams tend to be more successful.
- There is another issue that is a common business practice – it’s called the free cash flow agency problem. In these situations, companies will invest in cash flow negative projects in order to spend money that would otherwise go to another use. This is exactly what is happening with the Bulls. They would rather expand than be operationally efficient. If they didn’t pay Dwyane Wade, they would possibly not be able to reach the salary cap minimum. If this were to happen, they would have to redistribute the remaining money to the other players on the team. Thus, they would rather invest in Dwyane Wade even if it means losing money.
The DCF model can be divided into the following 5 revenue streams: regular season games, playoff games, TV deals, apparel sales, and sponsorship. Correspondingly, expenses are broken down into Dwyane Wade’s salary, arena operations, apparel expenses, playoff expenses, and revenue sharing repayment. Lastly, to find the net present value, free cash flow is discounted using the Weighted Average Cost of Capital formula derived specifically from NBA data.
1) Attendance
I collected home game attendance data for the bulls since 2002 in order to project home game attendance for the 2016-2017 and 2017-2018 seasons. I projected an increase in attendance of 1.15% in year one and a decrease in attendance by .64% in year two. If they didn’t sign Wade and instead signed an average shooting guard, attendance is forecasted to drop by 2.61% and then by 3.42% the year following. In making these assumptions I looked at the historic median change in attendance. Without a big name like Wade, attendance is expected to drop at a faster rate.
I multiplied the attendance change by the projected Fan Cost Index for the next two years. To find the FCI, I used a linear regression to forecast the natural growth of the Bulls’ FCI. Since the FCI is what the average family of four spends at a game, I divided it by four to find per person FCI and then added in the expenses associated with FCI by breaking down the FCI’s components.
2) Playoffs
I used 2016 bonuses the NBA gives to each team that reaches a benchmark and multiplied that by the change in probability that it will reach that benchmark due to Dwyane Wade’s presence on the team. The probability was determined by using Vegas odds. I used the change in probability that the Bulls would win the Finals and Conference before and after the deal. Revenue was determined by looking at leaked financial statements of the NJ Nets in 2004 and the New Orleans Hornets in 2008 and 2009. I was able to obtain the total revenue from playoffs and find revenue per game from a playoff home game. Then, to bring the revenue to today’s date and to a different team, I used a Revenue/FCI multiple. To find the expenses, I found the percent of revenue that is expensed during playoff games.
3) Sponsorships/TV Deals
I found the total sponsorship and TV deal revenue in the league. I divided that by the number of teams to get an average. To estimate the revenue that the Bulls’ sponsorships and TV deals generates, I used a revenue multiplier by looking at the Bulls’ revenue compared with the average revenue of an NBA team. This multiplier was then used to estimate how much greater the sponsorship revenue would be compared to the league average.
4) Contract
In order to find the true cost of Dwyane Wade’s contract, we must look at its opportunity cost – the amount an average player would have signed with the Bulls. Thus, I found the median shooting guard salary for 2016 and I incorporated the growth in salary cap to account for a league wide increase in a player’s salary. I added about $2 million to each player’s contract.
5) Revenue Sharing Pool
There is little information on revenue sharing. First, neither the formula used to determine revenue sharing nor the formula used to expense it on the financial statement is available. I emailed the NBA, but they replied stating that it was “confidential information”. However, I found an estimate of the revenue shared by the Lakers in the 2013-2014 season, so I was able to come up with a percent of revenue shared by the Lakers. Since the Bulls are of a similar size, that percentage is likely comparable.
6) WACC
I used the CAPM equation to find the cost of equity. I used the risk free rate by finding the yield of a treasury bond. The market return was calculated by finding the change in aggregate of all team’s values from year to year over the past ten years. I regressed the NBA market year-to-year change with the Bull’s year-to-year change to find Beta. To find the cost of debt, I assumed the Bulls are an AA company with a market cap less than $5 billion which has spreads of 1%. Thus, I added that to the risk free rate to get cost of debt. There is no tax shield since these NBA teams are privately owned businesses. Also, I assumed a constant D/V ratio of 2% since it has been near that number for the past few years.
7) Jersey Sales
Apparel sales data is the most challenging to find. The following assumptions could not be referenced relative to past sales. Also, there is limited information on how apparel sales are divided up amongst the league, team, and players. Thus, I did not incorporate it within the final calculations, but this is what I would have done. With revenue from apparel yielding the smallest piece of the pie, it is reasonable to reach the sales number that I did because the Hornets in 2006, which had half the value of the Bulls, averaged approximately $102,000 in merchandise sales. Now that the league nearly doubled in size, it is a conservative estimate that Dwyane Wade would yield around $200,000 in apparel sales. I used generalized assumptions that local stores would sell one jersey a day and home games would sell jerseys based on .5% of total attendees per game.
8) Comparables
Using player comparables to forecast the Bull’s Revenue/Expenses and Enterprise Value is not feasible. Instead, I took twenty players who had a similar story to Dwyane Wade where a future hall of fame player towards the end of his career goes to another team. From these twenty players, I was able to reasonably filter the comparables to 3 players: Scottie Pippen, Vince Carter, and Paul Pierce. The other comparables wouldn’t provide sufficient comparison to Dwyane Wade. Scottie Pippen couldn’t be compared because the era that he played in from a team’s financial structure is almost impossible to overlay. Vince Carter changed teams during the lockout which makes financial comparisons unfeasible. Lastly, Paul Pierce joined the Nets whose financial structure is vastly different than the rest of the league since they operate at a significant net loss each year.
Conclusion:
Even though leagues, teams and players entertain fans, it is ultimately a business. Sports often times function as a microcosm for the real world. Fortune 500 companies, just like NBA teams, are willing to invest in projects that will lose money in order to increase the overall value and attractiveness of the firm. The implication of these investment strategies has long-term consequences. In the NBA, teams will sign players for a net loss to increase the team value. In real life, companies will miss opportunities and sacrifice operational efficiencies necessary to make better products or services for consumers. These asymmetries can increase disparities between market value and book value which can create financial bubbles that burst when expectations aren’t realized.
[1] Constructive criticism on the model is welcome and encouraged at [email protected].
[2] http://www.forbes.com/sites/mikeozanian/2016/06/19/nba-finals-500-million-swing-hinges-on-game-seven/#2916e7f03cdf
dwayne_wade_dcf.xlsx |