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Sports Abacus: Free Tickets Per Caps Affects

I’ve written about the dangers of free tickets in terms of market devaluing of the sports franchise in general.

I decided to examine it much further on its affects on the per cap financial model for a team each season. This meant doing a lot of “regular math” along with calculating out some formulas to see if I could measure out the impact of comps (i.e. free tickets) in terms of their presence in the per cap per game.

Let’s start off with a few rules that I used, mainly to calculate this all out.

First, the per cap may appear very simple for minor league clubs:

 

PC = A / T + M + P + CP + C + B

 
PC = Team Per Cap
A = Total Attendees
T = Ticket Revenue
M = Merchandise
P = Parking
CP = Corporate Partnerships
C = Concessions
B = Broadcast Rights

 

Major League per caps also include national broadcasting packages, which makes their broadcasting per cap share higher than that in terms of overall per cap presence.

For estimating these per caps and the presence of complimentary or free ticket recipients for the in-game per cap, I decided to eliminate two parts of the per cap for a team, broadcasting and corporate sponsorship, in order to measure out exactly what presence a fan receiving complimentary tickets has on the overall team per cap.

While some may argue that the complimentary fan “appears” as optics, the truth of the matter is, broadcasting and corporate sponsorship would not be impacted game-by-game as a result of a comp ticket being issued or not. That’s perhaps an end of the season argument, but this an in-season argument, taking issue with whether the impact on a team’s per cap through in-game means shows a benefit to having complimentary folks coming through the turnstiles.

For this, let’s focus on how much per cap was actually resulted by paying fans first with a formula called Per Cap Paid.

 

PCP = T / PA

PA = Paid Attendees
PTCP = Paid Ticket Per Cap
T = Ticket Revenue

 

Let’s look at the amount of revenue that a complimentary ticket loses off of the ticket price per game. This means money lost on what on the original value of the ticket in order to let the person through the gate for free. We can easily estimate that by the above formula of dividing total ticket revenue by paid attendees, which shows the original value of the ticket per cap prior to being watered down by presence of complimentary tickets, which would deflate the ticket per cap as a result of being issued.

With this calculation, I came up with a simple formula that I call Ticket Per Cap Lost – essentially taking the Paid Ticket Per Cap times Comp Tickets issued to create a Ticket Per Cap Lost resulting from issuing the comp in the first place:

 

TPCL = PCP x CMP

TPCL = Ticket Per Cap Loss
PCP = Paid Ticket Per Cap
CMP = Comp Ticket

 

Right there, you can see a whole value of issues stemming from the loss at the ticket counter. It is within this reasoning that we would find out how much presence the complimentary ticket recipients actually have within remaining per caps. Why? Because this would add justification, in terms of math and revenue, as to what benefits there are to comp’ing tickets out. Because of their supposed intrinsic revenue impact on the per cap.

Here’s the formula that I came up with in order to show Comp Per Cap Presence for the team:

 

CPCP = CMP x (M + P + C)

CPCP = Comp Per Cap Presence
CMP = Comp Ticket
M = Merchandise
P = Parking
C = Concessions

 

To me, this shows what actually was spent within the average, by those complimentary ticket recipients, during their time at the ballpark. This does not determine whether each complimentary ticket actually spent this money, because it is an average overall combined with paid ticket buyers, but it sheds some light on attempting to even out whether or not there are benefits to having complimentary tickets within the ballpark.

Taking this information, I decided to go another step further and create another calculation. This time looking at between what was lost at the ticket counter, trying to figure out if it was realized back at the other ancillaries by issuing the complimentary ticket.

First off, there is a stark difference between ticket and parking money compared to all other ancillaries in the ballpark/arena. Ticket and parking money have fixed costs (i.e. there is no rise in the costs to produce the end product for the customer). However, there are no fixed costs with merchandise or concessions. Meaning that the maximum way to achieve profitability through selling a product is tickets and parking.

That’s where the Lost Revenue Per Cap calculation comes in. It is there to show exactly what did a team lose on potential ticket revenue compared to what they achieve by having the complimentary recipient in the facility.

Here’s the formula that I came up with:

 

LRPC = CPCP – TPCL

 

CPCP = Comp Per Cap Presence
TPCL = Ticket Per Cap Lost
LRPC = Lost Revenue Per Cap

 

 

Application Models

 

I wanted to present two scenarios where per cap models can show how complimentary tickets can truly affect a per cap drastically within a sports organization.

I went into this project with an open mind, despite my beliefs, because math is the true way to discover accuracy. Developing blog posts without math imbedded almost takes the notion of anti-free tickets to a philosophy of nodding heads. I wanted to actually prove why free/complimentary tickets are bad for the team in general, and that per cap money wasn’t realized later enough to satisfy the loss at the ticket counter.

That being said, I did the best that I could, using a projections for teams that were looking to arrive in new locations, as a way to gain access to what were potential but fair numbers for what a professional team might expect on a nightly per cap.

 

FBS College Football Per Cap

 

Since it is college football time, I thought it would be an interesting way to calculate out the revenues and apply a professional per cap model to the world of athletics. Especially FBS football, which is not the elite level (that’s BCS) but has the potential to gain hundreds of thousands in revenue per game and over the course of the year.

Those in the professional sports world may be interested to know that college athletics has ignored or lacked a financial per cap model to determine their revenues.

So, I decide to make one for an FBS football team, just to see what would happen.

No, the sky did not fall. But, suffice it to say, athletic departments across the country will not adopt such a financial measurement unless there is a Division-I equivalent to Martin Luther who nails to their door. Why? Because in terms of college athletic budgetary formulations: “It’s always been done the other way, so why change?”

Plus, because a professional per cap model may also show holes in certain lines of thinking when it comes to what builds revenue and what does not, especially the advent of free tickets (which college football programs are rather notorious for). Some of the free ticket “hokum” in college athletic departments comes from the notion that they can tell their corporate sponsors that they had “huge” attendance numbers, when in fact, they had record tickets printed with a bunch of empty seats.

Ah, the ways that lies grow bigger. I’m waiting for a movement by local corporate sponsors to actually call B.S. on some of these outlandish claims by college athletic departments in terms of what they draw compared to what they charge for corporate deals. It may happen soon as budgets grow tighter.

It doesn’t help that there is no college football or basketball per cap. Mainly, athletic departments look at their revenues in a black and white budgetary manner:

Did we make more money than we did the year before?

That’s it. That’s the entire way that they look at revenue.

Why?

My belief is that college athletic departments achieve most of their annually funding from student fees or the university. Revenues from the actual ticket buyer are looked at as a piece of secondary income, rather than primary concern.

Which is why free tickets to gain optics appear as a creditable solution.

A college football per cap would also have to take into account another piece of the revenue pie – Athletic Fund Seat Donations. These would be a form of Personnel Seat Licenses that the NFL has made so popular. While only about a fourth of the attendees pay these seat donation fees, they could be calculated in terms of a college sports per cap.

 

SDPC = (TSDR / G) / SD

 

SDPC = Seat Donor Per Cap
TSDR = Seat Donor Revenue
SD = Seat Donors
G = Games

 

Instead of merely focusing on whether or not the FBS team gained a few more donors, the attention should be paid on whether an additional game actually benefited the team.

Let me explain by way of showing an example of the fictional FBS team. The team lost 800 seat donors from 2011 but ended up playing an additional game, 7 total, during that season:

Season

SD

TSDR

G

SDPC

2011

7800

$2,433,000

7

45

Season

SD

TSDR

G

SDPC

2012

7000

$2,394,000

6

57

 

At first glance, it may look like a loss of total revenue. But realistically, by having less seat donors in 2012, they actually had a higher per cap during each of their six home games. Meaning, for those six games, they earned more money than if they would have had seven games.

Here how I broke down other per cap items:

Year

Games

Concessions PC

Merchandise PC

Parking PC

2011

7

$1.50

$1.42

$1.83

2012

6

$3.00

$1.83

$1.67

Year

Games

Concessions Avg

Merchandise Avg

Parking Avg

2011

7

$69,007.08

$62,159.25

$82,081.50

2012

6

$108,085.00

$65,810.00

$60,588.33

Year

Games

Concessions Total

Merchandise Total

Parking Total

2011

7

$483,049.56

$435,114.75

$574,570.50

2012

6

$648,510.00

$394,860.00

$363,529.98

 

So, looking at the following breakout, it looks credible to suggest that an additional game brought in more revenue, but cut the average down considerably.

College football and college athletics issue a lot of comps. They are one of the biggest offenders of issuing complimentary tickets. In some ways, they are required to in order to stay above the NCAA’s 15,000 seat-attendance rule in order to qualify to be in the Football Bowl Subdivision. There is considerable money for those FBS teams, especially if they make a bowl, in terms of broadcasting and other merchandise rights, and they will issue enough complimentary tickets to stay above those lines.

Here are the amount of comps, on average, that I had my FBS team issue per game:

Year

Games

Comps

Reported Attendance

Paid Attendance

2011

7

6,931

43,385

36,454

2012

6

4,604

34,978

30,374

 

Essentially, the FBS squad issued more complimentary tickets on average during their 2011 campaign. It was a reported attendance that issued 1,300 comps more than the year after in 2012, yet attendance was lower with one less game to play.

Here is what the loss on the per cap comes out to as well with the average ticket price of $23 per ticket:

Year

Comps

TPCL

CPCP

LRPC

2011

6,931

 $160,469.00

 $33,552.00

 $126,917.00

2012

4,604

 $123,130.00

 $8,101.00

 $115,029.00

 

This explains where revenue losses go as a result of the per cap.

 

 

NBA Team Per Cap

 

Focusing on the NBA per cap was a little different, because I eliminated corporate sponsorship and broadcasting again, to show the impact of complimentary tickets on not only the static ticket price, but also the dynamic ticket price.

For the static ticket per cap price, I calculated it out to $25 per ticket which averaged out to almost the same gate receipts reported by Forbes the last few years. Give or take a million here or there. But I feel comfortable sharing them, specifically because they feel accurate enough.

The fictional NBA team also applied the reported attendance of the same actual NBA team within my model. I decided to apply a way to examine complimentary tickets without actually knowing the true data.

I went by attendance numbers. If the attendance numbers were high, the comps were lower. Mainly because those games were enough in demand that comps were not needed not utilized.

It is really the terrible Tuesday night games where the team is reporting small crowds (around 10,000) that I assumed the worst for comps. When NBA averages were considered most, so comp’ing begins as a solution.

Here was the attendance breakdown for the amount of comps issued for the fictional NBA team:

 

Reported Attendance

Comps

 18000 – 22000

200

 15000 – 17999

400

 13000 – 14999

600

 11000 – 12999

1000

 10000 – 11999

2000

 

Now, I can’t prove that a team would generate that many comps per game, but I definitely think optics in terms of corporate sponsorship would push a lot of teams to decide to comp out more as the attendance is falling. If the team has less than 10,000 average attendance per game, it likely affects the contracts with sponsors, therefore, the comp may not be “issued” at all to anyone but just “boosted” in terms of the numbers reported to the media, etc.

But it provides a good launching point for the discussing below.

Here are the other per cap totals, to showcase how I arrived at the calculations that I did:

 

Merch PC

 Merch Total

Parking PC

Parking Total

Concessions PC

Concessions Total

 $2.59

 $42,729

 $2.93

 $24,150

 $3.59

 $58,402

 

The only calculation above which I worked with was the parking revenue one, simply because not everyone is going to pay for parking. I assumed for every two people, a sale would be made at the per cap. I am willing to debate this one, since it is hard to figure how many folks show up together in one car (could be two, three or four), so I went with an average of charging the overall fans instead of individually per game (which would probably be impossible without knowing true numbers).

 

NBA Team Per Cap With Static Ticket Pricing

 

Here are the numbers for the fictional NBA team’s 41 home game schedule for the under static ticket pricing measurements. The price point was always $25 regardless of the opponent. These are the averages, per game, along with the total per game, and the static ticket loss by way of complimentary tickets which undercut the original ticket value by not being compensated for:

Announced

Paid Attend

Comps

 StTix PC

 StTix Total

 StTix Loss

14,782

14,035

746

 $25

 $350,887

 $18,659

 

If you notice, the same formulas are used for projecting losses via complementary tickets against the static ticket price and lost revenue by not selling those tickets, instead, giving them away.

Here is an annual total for the year based on static ticket pricing models:

Games

 StTix Total

 StTix Loss

 41

 $14,386,350

 $765,000

 

 

NBA Team Per Cap With Dynamic Ticket Pricing

 

I can up with a dynamic ticket pricing matrix as well, grading the opponents, and pricing accordingly. Dynamic pricing typically only has a small segment of games which go below the original price point (in this case $25), yet I decided to mark down 9 total games $5 less as “demand” decreased. I put these games at the ones where it was less than a large crowd.

Games

 Price

Rating

11

 $50

A

9

 $40

B

13

 $30

C

9

 $20

D

 

Here is what we have in terms of dynamic pricing for the average game, along with the amount of revenue generated from a dynamic ticket price per cap instead of a static one:

Announced

Paid Attend

Comps

 DyTix PC

 DyTix Total

 DyTix Loss

14,782

14,035

746

 $36.10

 $543,047

 $22,146.00

 

You’ll notice that that dynamic ticket price loss is substantially more, per game, as a result of the complimentary recipients not purchasing tickets, especially to the most in-demand contests.

Now, let’s look at what the Complimentary Per Cap Presence equates against a static ticket pricing structure on average, per game.

Avg Comps

Comps Revenue

 StTix Loss

 StDifferential

746

 $81,826

 $765,000

 $(683,174)

 

Above shows the amount of money lost on complimentary tickets not being paid for, and the amount for revenue realized by complimentary recipients’ purchased on the other per cap items of merchandise, concessions and parking per 41 of the games. The differential shows a large gap between the money realized at ancillaries by complimentary ticket buyers and the revenue lost by not having those same ticket buyers pay for their tickets.

Let’s examine this further, instead focusing on dynamic ticket pricing and its structure:

Avg Comps

Comps Revenue

 DyTix Loss

 DyDifferential

746

 $81,826

 $908,000

 $(826,174)

 

Above shows the amount of money lost on complimentary tickets in the form of a larger loss, because dynamic ticket prices are, on average, higher than those on the static market. It also inflated the loss differential between the amount of money realized by complimentary recipients on other ancillaries against the loss of money on the dynamic ticket price.

Here is an annual total for the year with a Dynamic Ticket Pricing model:

Games

 DyTix Total

 DyTix Loss

 41

 $22,264,910.00

 $908,000.00

 

 

Final Thoughts

 

I thought this presented a good per cap option for both an FBS college football and NBA model in terms of complimentary tickets.

Optics and broadcasting contracts carry with them a very strange component. If you issue a bunch of comps to “get people in the building” so that it “looks good on television,” you end up deflating the initial price point. This can have dual affects of harming the urgency to buy tickets at all, as well as prevent people from “showing to the event.”

Math is also an imperfect science without hardcore data. All of these are guesses in terms of numbers, but I took every type of precaution in terms of using real reported data from an actual FBS team and an actual NBA team in order to come up with attendance figures.

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