The Case of the Ultimate Fighting Championship A

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REACTING TO A POTENTIAL RIVAL’S SUBSTANTIAL PRICE DECREASE: THE CASE OF THE ULTIMATE FIGHTING CHAMPIONSHIP

A THESIS

Presented to

The Faculty of the Department of Economics and Business

The Colorado College

In Partial Fulfillment of the Requirements for the Degree

Bachelor of Arts

Brendan Michael Quinn

May 2014

REACTING TO A POTENTIAL RIVAL’S SUBSTANTIAL PRICE DECREASE: THE CASE OF THE ULTIMATE FIGHTING CHAMPIONSHIP

Brendan Michael Quinn

May 2014

Economics

Abstract

This thesis measures the degree of substitutability in consumption between televised mixed martial arts competition presented by the Ultimate Fighting Championship (UFC) and professional wrestling presented by World Wrestling Entertainment (WWE) in order to estimate the potential impact on UFC’s revenues after WWE’s announcement of a change in its pay-per-view model that dramatically decreases prices. Using a variety of control variables, the seemingly unrelated regression model finds significant substitutability in consumption between the products offered by each company as well as decreasing revenues for UFC as time goes on. This thesis then analyzes WWE’s decision to offer a far less expensive digital subscription service and UFC’s decision to continue using the traditional pay-per-view model.

KEYWORDS: (Pay-Per-View, Digital Subscription Services, Mixed Martial Arts, Ultimate Fighting Championship, Professional Wrestling, World Wrestling Entertainment, Income Effect, Substitution Effect, Game Theory)

ON MY HONOR, I HAVE NEITHER GIVEN NOR RECEIVED UNAUTHORIZED AID ON THIS THESIS

Signature

TABLE OF CONTENTS

ABSTRACT ii 1 INTRODUCTION 1

2 THEORY 9 2.1 Substitution Effect vs. Income Effect…...... 9 2.2 Introducing Game Theory...... 12

3 LITERATURE REVIEW 16 3.1 Tainsky, Salaga and Santos (2013)………………………………………… 16 3.2 Watanabe (2012)…………………………………………………………… 17

4 METHODOLOGY 20 4.1 Data Selection……………………………………………………………… 20 4.2 Seemingly Unrelated Regression Model…………………………………… 28 4.3 Summary Statistics…………………………………………………………. 29

5 RESULTS 31

6 CONCLUSION 37 APPENDIX 40 SOURCES CONSULTED 42

LIST OF TABLES

4.1 UFC Pay-Per-View Summary Statistics (2005-2013)……………………... 29

4.2 WWE Pay-Per-View Summary Statistics (2005-2013)……………………. 30

5.1 Seemingly Unrelated Regression Results………………………………...... 31

5.2 ln(UFC PPV Revenue) as Dependent Variable…………………………….. 31

5.3 ln(WWE PPV Revenue) as Dependent Variable…………………………… 32

Variable Descriptions………………………………………………………. 40

LIST OF FIGURES

2.1 Zero Substitutability; WWE Price Decrease………...………………………. 11

2.2 Perfect Substitutability; WWE Price Decrease.…………………………….. 11

2.3 WWE vs. UFC Decision Tree: Network or Pay-Per-View…………………. 13

5.1 Graph of UFC Revenue Per Event Trend Line ……………………………... 33 (February 4, 2006–October 19, 2013)

CHAPTER I

INTRODUCTION

The Ultimate Fighting Championship (UFC) is the world’s largest mixed martial arts promotion. Their main line of business involves staging events featuring several bouts, or “fights,” between competitors from varying weight classes practicing a wide variety of martial arts disciplines. Their main line of revenue comes through airing certain events on pay-per-view. UFC airs anywhere from twelve to sixteen of their events through pay-per-view per year, and each event is priced at $45.

Since debuting in 1993, UFC has gone through a number of important changes.

First and foremost, the entire sport of mixed martial arts has transformed from a “no holds barred” type of competition with very little regulation and very low safety standards to one which is regulated in all forty-nine states and emphasizes the importance of rules which promote fighter safety. Senator John McCain famously labelled the sport

“human cockfighting” during his nationwide campaign in the late 1990’s to ban the sport throughout the country (Silverman, 1998). Furthermore, early mixed martial arts events

(including UFC) featured “freak show” type fights such as those between two fighters of drastically different sizes as well as experience; today, all competitors compete with others in their own weight class, and fighters are generally matched up with those of similar skill level. These changes have allowed mixed martial arts to become better

1 appreciated for the athleticism and competition involved, whereas many once criticized the earlier UFC shows for being a grotesque form of entertainment. Even Senator

McCain has told UFC star Jon Jones that he would purchase the upcoming UFC 172 event, which Jones will be headlining (Raimondi, 2014).

The business of the UFC likewise evolved along with the sport. After several years of being in danger of ending due to financial troubles and scrutiny from politicians and regulators, the UFC found its first major success with its reality show, The Ultimate

Fighter, in 2005, and built enormous momentum both in the number of pay-per-views it sold for each event and in its effort to become recognized as a “mainstream” sport. In addition to being discussed seriously on shows such as SportsCenter, UFC also burst into the mainstream when one of its fighters, Roger Huerta, became the first mixed martial artist to grace the cover of Sports Illustrated in May 2007 (Al-Shatti, 2013). In July

2009, the UFC aired its most successful event ever when UFC 100 sold over 1.6 million pay-per-views (Meltzer, 2009). 2011 saw the UFC begin a seven-year broadcast deal with Fox Sports to air certain events live for free on Fox as well as Fox Sports 1.

Throughout this time, the UFC became recognized as the premier mixed martial arts organization throughout this country and the whole world, buying off several smaller promotions along the way and consistently featuring the most skilled roster of professional fighters from around the world.

Over the past few years, however, the UFC’s momentum has stalled. 2010 was the company’s most successful in terms of total pay-per-view buys, as well as the number of buys per event. The company sold over nine million pay-per-views that year. In 2011, they sold about 6.8 million, and in 2012 they sold about 5.9 million. Journalists and fans

2 of the sport have come up with many possible explanations. Some say the company has failed to create stars that fans will pay to see while the biggest stars of yesteryear have retired or fallen from their prime. Others suggest that the company has cannibalized its own product by airing more and more free events on television through their Fox Sports partnership, diluting the value of pay-per-view cards by pushing certain stars onto free

TV (Doyel, 2013). One suggestion that is growing in popularity is that the pay-per-view business model is a dying one, as fans of the sport are becoming less willing to spend a hefty sum of money for a one-off event. This suggestion has drawn countless comparisons between the UFC and one of its rivals in the pay-per-view industry, World

Wrestling Entertainment (WWE) (Meltzer, 2014a).

While both are major presences in the pay-per-view industry, WWE offers a different product than what UFC offers. While UFC is undoubtedly a sporting promotion, those in charge of WWE prefer to call their product “sports entertainment,” with an emphasis on “entertainment.” Many people, including UFC President Dana

White, suggest that the UFC and WWE are not rivals at all (Hall, 2014). These people first note that the UFC stages legitimate sporting contests with no writers or storylines, whereas WWE provides more of a weekly “soap opera” based around the staged performance known as professional wrestling. White has stated that he believes there is a much larger crossover between mixed martial arts and boxing than there is with professional wrestling. Still, many contend that there is enough of a crossover to consider the two companies rivals. Dave Meltzer (2012) of Yahoo! Sports wrote, “The closest business model to UFC is that of World Wrestling Entertainment” in an article about compensation for UFC’s fighters. He insists in the article that the UFC is

“structured completely differently from the big four team sports” and “also structured differently than boxing.” Meltzer also defends against those who, like Dana White, believe WWE’s “scripted” environment make all similarities between WWE and UFC irrelevant: “While some will argue WWE is a form of performance art and not a real athletic competition – and thus the performers don’t deserve as much money – the dollars

WWE derives from its performers, who take a legitimate physical pounding, is every bit as green as those which UFC makes.” Like the UFC, WWE also airs pay-per-view events about once per month for a similar price. Although there are other mixed martial arts companies that are certainly in competition with UFC, none are close to as big as

WWE. Likewise, while there are other professional wrestling companies that try to compete with WWE, none are nearly as big as UFC. For these reasons, it is not stretching the truth to acknowledge a rivalry between the two companies. Unlike the UFC, WWE’s success through the pay-per-view market revolves around selling matches between competitors using compelling, fabricated storylines on its weekly cable television shows; the UFC must convince fans to purchase their events by advertising the sport itself and the legitimate mixed martial arts credentials of its competitors. Another major difference is that WWE has the luxury of reusing its major stars for just about every pay-per-view they air, whereas individual UFC fighters typically never compete more than three times per year. Thus, the company must more carefully choose when their most popular competitors should appear on particular events throughout the year. UFC fighters are also much more prone to injuries that make scheduling even more difficult for the UFC.

One planned event, UFC 151, had to be cancelled entirely when a main-event championship contender, Dan Henderson, had to pull out of the event due to injury, and

4 the reigning champion, Jon Jones, refused to fight someone else on short notice (McNeil,

2012). Such a catastrophic series of events would never occur in the scripted environment of WWE. Still, the crossover between the two companies is hard to deny: the successful first season of The Ultimate Fighter, which many contend helped launch the UFC into mainstream acceptance, aired directly after WWE’s weekly television show, Monday Night Raw, on the same network (USA) and certainly captured a great deal of the Raw audience (Meltzer, 2012). In addition, the UFC’s biggest star, largely responsible for the aforementioned 1.6 million sales of UFC 100, was Brock Lesnar, an

NCAA wrestling champion who had previously been one of the biggest stars in WWE.

Given these facts, the similarities between the two companies become apparent even though one sells sport and the other sells entertainment. These similarities and differences between the two companies have recently become a major topic of conversation for fans and journalists alike, as both UFC and WWE announced plans within weeks of each other to start their own digital subscription services.

Both the “UFC Fight Pass” and the “WWE Network” will charge $9.99 per month for exclusive content. They will also both contain video libraries of previous events presented by each respective company. They are both “digital” in the sense that each service is not offered as a traditional cable channel; rather, one must access them through a streaming device such as an Xbox 360 (or other gaming device), a smartphone, a tablet, a smart TV, or simply a personal computer. The greatest difference between the two is that the WWE Network will air every single one of its pay-per-view events live at no additional cost, whereas the UFC Fight Pass will offer no such deal for its pay-per-views.

By doing this, WWE is almost completely changing their business model. Their pay-per-

5 view business was once identical to UFC’s: a $45 pay-per-view sold through a cable or satellite company about once per month. Now, for a mere $10 per month, fans of WWE will be able to access all of these pay-per-views live on almost any streaming device.

While they will still offer their pay-per-views through the traditional method in the foreseeable future, they are certainly counting on that old form of distribution dying out soon because they are dramatically undercutting the price through their own service.

Purchasing a year’s worth of WWE pay-per-views once cost $545, but soon this will now only cost $120; WWE has effectively reduced the price of watching every pay-per-view by about 78%. After WWE announced the Network, the satellite television company

DirecTV issued a statement to the Los Angeles Times which expressed doubt that they would have any kind of relationship with WWE going forward: “Clearly we need to quickly reevaluate the economics and viability of their business with us, as it now appears the WWE feels they do not need their PPV distributors” (Meltzer, 2014a).

Fans of the UFC were quick to point out the WWE Network’s superior value to

UFC’s Fight Pass, and Dana White soon had to respond to criticism for not offering a similar deal. “The NFL gets $9 billion in their rights deal for television. When FOX pays us $9 billion for our rights deal, we won’t do pay-per-view” (“Video: Dana White,”

2014). While his comments may have been an exaggeration, White brought up perhaps the most important difference between the UFC’s business and WWE’s: television rights.

WWE’s Monday Night Raw draws a large audience to the USA Network every single

Monday year-round with new storylines and an ever-changing cast of characters.

Although the UFC does air some shows on television, such as The Ultimate Fighter, none come close to Raw’s consistent success in the ratings. As such, the ability to air live

WWE television is very desirable for cable networks. WWE’s current contract for television rights with NBC Universal ends this year, and WWE expects to make considerably more revenue through television rights when they renew or sign with a competing network. Meanwhile, pay-per-view numbers for WWE have dropped in recent years (Meltzer, 2014a). In 2012, the company’s pay-per-views averaged just under 318,000 worldwide pay-per-view buys; in the same year, the UFC sold an average of 449,000 per event in North America alone. Relative to the UFC, television is becoming a much higher priority compared to pay-per-view for WWE, and their ability to generate revenue through television allows them to take the major risk they are taking with the Network. The UFC has no such cushion, as pay-per-view remains their largest source of revenue. In response to the WWE Network announcement, Dana White said,

“And when I look at his model and he's basically taking everything in and devalued it.

Saying everything we do is worth $10. That doesn't make sense to me” (Martin, 2014).

He also called the Network “ridiculous.” Clearly, White still sees greater value in retaining the traditional pay-per-view format.

Still, WWE would not get rid of their old pay-per-view model in order to support their own digital network just because they have the ability to take that risk; the company clearly sees greater potential for long-term company health by offering a subscription service than they do with the traditional pay-per-view model. One must ask what reasons

WWE has for changing models that the UFC doesn’t have. For one, the UFC has been outperforming WWE on pay-per-view for the last several years, so the current method of distribution is working better for them. Another is that WWE aims to attract fans who no longer watch their current product but would be willing to spend ten dollars per month to

7 watch WWE’s extensive video library which includes historical footage from its own events and those put on by rival wrestling promotions that WWE later bought. Doing so may encourage these fans to give the current product another chance since they will be able to view live pay-per-views at no additional cost and further boost WWE’s increasingly important television ratings. The UFC, being a much younger company, has far fewer of these lapsed fans as well as a much smaller video library. Still, with the UFC

Fight Pass infrastructure in place, the company has laid the groundwork to one day provide live pay-per-views just as the WWE Network does. The service has already begun airing exclusive live events, but they are not what most would consider to be pay- per-view quality; clearly, the opportunity is present for the UFC to make the same jump

WWE has made. Perhaps the company wishes to see how WWE fares after switching models before making such a risky decision.

CHAPTER II

THEORY

Substitution Effect vs. Income Effect

If there is a significant crossover between fans of the UFC and WWE, one must wonder how the announcement of the WWE Network will affect UFC’s pay-per-view revenues. The economic concepts of substitution effect and income effect will become key in answering this question. Rational consumers maximize their utility by selecting combinations of goods and services that gives them the most utility and is bound by their particular budget. Damon Martin (2014) of Fox Sports explained two opposing arguments in a column comparing UFC’s and WWE’s subscription services: “One argument says that the WWE changing its format to a price point where fans can watch every pay-per-view out there for only $9.99 a month would somehow make people less apt to pay $50 to watch a UFC show. The other side of the argument could be the WWE exiting the pay-per-view model in many ways opens up doors for fans to instead spend their money on the UFC.” The first argument represents the substitution effect being greater than the income effect: fans who recognize that WWE is offering a far superior value will be less prone to continue paying a high price for one UFC event due to the fact that they are comparable substitutes. They will optimize their utility by consuming a greater amount of WWE content which will be both be more accessible and considerably cheaper once the Network is introduced. The second argument represents the income

9 effect outweighing the substitution effect: fans who have freed up cash from reduced spending on WWE will be more willing to spend that extra money on UFC pay-per- views. In this scenario, consumers are able to optimize their utility by consuming more of both products due to the price drop of just one of the products. Another benefit the

UFC may see in the future is less competition for advertising on cable, as cable companies will be less likely to continue advertising as heavily for WWE pay-per-views.

The question is whether, and by how much, one effect will be stronger than the other.

The values of consumers, expressed visually by the shapes of their indifference curves, will help answer this question. My model will attempt to measure whether UFC’s and

WWE’s products are close substitutes in the eyes of consumers by measuring the effect on UFC pay-per-view revenues based on each event’s proximity to WWE pay-per-view events. If WWE pay-per-views appear to have a strong negative effect on UFC pay-per- view revenues when they are close in proximity, this would suggest that the market sees the two products as close substitutes. The closer the two products are seen as substitutes in the eyes of the marketplace, the stronger the substitution effect should be given

WWE’s dramatic decrease in price. If the substitution effect is indeed stronger than the income effect, the UFC’s pay-per-view numbers, and thus its revenues, will likely continue to decline. Figure 2.1 and Figure 2.2 present two extremes: the case where UFC and WWE’s products have zero substitutability and the case where the two products are perfect substitutes:

FIGURE 2.1 FIGURE 2.2

ZERO SUBSTITUTABLITY; PERFECT SUBSTITUTABILITY; WWE PRICE DECREASE WWE PRICE DECREASE

In the first case, only the income effect is present when WWE dramatically drops its prices. Because the two products are not substitutes at all, consumers purchase more of both. In the second case, consumers’ indifference curve envelops their budget constraint, meaning they are indifferent between any amount of UFC and WWE entertainment on the a-a line. After WWE drops its prices, these consumers will only purchase WWE events and completely stop purchasing UFC events (point b on the graph) because both products are the same in the eyes of the consumers. Reality lies in between these two extremes: the two products are imperfect substitutes. The degree of substitutability between the two products will dictate the magnitude of the substitution effect and whether or not it is stronger than the income effect. A stronger degree of substitutability will lead to a stronger substitution effect and thus a stronger negative impact on UFC pay-per-view revenues. My model will attempt to measure whether the two products are

11 substitutes in consumption, and this will shed light on what kind of impact UFC’s pay- per-view revenues will experience after the WWE Network becomes available.

Introducing Game Theory

A game theoretic approach can help explain both WWE and UFC’s motives and decisions. As rivals, both companies wish to dominate the market, often at the expense of the other. Because WWE and UFC offer two products that are somewhat substitutable, each company must sometimes make decisions based on the other’s previous and expected future choices. This may include the decision to lower the bottom line in the current year in order to capture a greater share of the market and raise revenues in future years. WWE recognizes that the Network will lower profits in 2014; CFO

George Barrios wrote, “We expect the network will reduce OIBDA and net income in

2014 as the initial ramp in subscribers and revenue is not likely to be sufficient to offset both the foregone pay-per-view revenue and the incremental, direct expenses associated with a network launch, such as programming, marketing, customer service and content delivery costs.” Despite this, the company is making a huge gamble by offering

WrestleMania, by far their largest and highest grossing event each year, as the very first pay-per-view to be aired on the Network. This is clearly an attempt to earn as many

Network subscribers as possible upon the launch date, but it is one that will certainly cannibalize their own pay-per-view revenue considerably. In 2012, a consumer could purchase all twelve WWE pay-per-view events that year for $549.88; the same consumer will be able to access twelve pay-per-view events for under $120 upon the launch of the

Network. WWE is perhaps expecting the substitution effect detailed above to outweigh the income effect, lowering UFC’s pay-per-view revenue as well as their own. Even

12 though WWE is intentionally lowering their revenue for this year, they are potentially making other forms of entertainment relatively less attractive, particularly UFC, by making them relatively more expensive than before. Given that both the UFC and WWE provide combat-oriented entertainment and previously operated under a similar pay-per- view structure, UFC may be the first form of entertainment to suffer from this substitution effect. Consumers may stop buying UFC pay-per-views and instead choose to subscribe to the WWE Network, giving WWE a higher percentage of the market share for those who consume combat-oriented entertainment. This could, while placing them at a worse position in the upcoming period than they are in during the current period, maximize their potential future benefits. The following decision tree illustrates WWE and UFC’s decision-making with regards to their pay-per-view model:

FIGURE 2.3

WWE VS. UFC DECISION TREE: NETWORK OR PAY-PER-VIEW

As previously mentioned, the success or failure of the WWE Network depends on consumer preferences, as would a similar UFC-style network which drastically reduces

PPV prices. WWE made the initial decision to switch over from a pay-per-view model to the Network because their predictions as to how the market would react gave this decision a higher value of expected utility than keeping the pay-per-view format would have. UFC is the second mover in this game; they anticipate a higher expected utility from their current pay-per-view model than from switching to a subscription-based service as WWE has done. While neither company can predict the market’s reaction to a subscription-style service perfectly, it is clear that WWE believes they have more to gain from moving away from pay-per-view than the UFC believes they have; this could be because WWE has a smaller share of the pay-per-view market and also because WWE is taking on less of a risk due to their other lucrative sources of revenue, such as television rights contracts.

WWE’s decision to completely change their pay-per-view model demonstrates the company’s belief that consumers will be receptive enough to their Network that the benefits outweigh the opportunity costs of not charging $45 for a single pay-per-view;

UFC’s decision to keep their current model show that they do not share these beliefs. It could be the case that the UFC believes making such a move would be appropriate at a later date. My model will measure the UFC’s performance in the pay-per-view market over time. If the trend suggests UFC is continuing to gain popularity throughout time while other variables are held constant, the company may wish to continue using their current pay-per-view model. However, if the trend suggests that the company’s pay-per-

14 view revenues are lowering as a result of time, they may be wise to adopt WWE’s network model sometime in the future.

CHAPTER III

LITERATURE REVIEW

While the field of sports economics continues to grow, very little research has attempted to measure the factors that determine UFC pay-per-view buy rates. The vast majority of studies have used attendance as a measure for demand for sports; buy rates have the advantages of a virtually unlimited supply and an (almost) constant price, making them an even more desirable dependent variable than attendance. Unfortunately for sports economists, major sports in the United States are, for the most part, not sold on pay-per-view. The UFC, being one of the few sports promotions that generates most of its revenue through pay-per-view sales, makes itself an easier company to analyze.

Tainsky, Salaga and Santos (2013)

Tainsky, Salaga and Santos (2013) aimed to measure the effects of certain variables on UFC buy rates from 2001 to 2011 with an OLS regression. Their model, which achieved an R2 value of .6336, found that the most significant factors were the positive trend variable, whether a championship was defended and in which weight class, the betting odds of the main event, promotion leading up to the fight through The

Ultimate Fighter, as well as the presence of well-established champions and “stars”

(defined as all current and former UFC champions in any weight class) at a particular event. The positive trend variable indicated that with each passing month, the UFC

16 would sell 5,789.92 additional pay-per-views. Since the dataset ended in 2011, this variable explains a positive, linear relationship between buy rates and time, which is understandable given that the conventional wisdom in 2011 was that the company was becoming more and more popular. My model will attempt to explain the trend as a quadratic function; since the dataset is more recent, one would expect that perhaps the trend is decreasing or perhaps even negative. It will also measure the trend in days rather than months in order to be as precise as possible. The model’s findings that the presence of championship fights on a particular event is unsurprising; fans are more willing to pay to see fighters who are considered the best as well as fights where something is at stake.

The betting odds variable, which used Las Vegas odds to measure the uncertainty of a particular fight, found that fans were more willing to pay for main-event fights where the outcome was perceived to be more uncertain. The remaining variables explain that consumers are more willing to purchase events featuring fighters they with whom they are more familiar.

Watanabe (2012)

Nicholas Watanabe (2012) first attempted to measure the factors that determine demand for UFC pay-per-views from 2001 to 2012. Using an OLS regression, his model achieved an R2 of .6631 and found some interesting results: first, the price variable turned out to be positive, violating traditional economic theory that demand decreases as price increases. While this initially appears surprising, it quickly becomes apparent that the model suffers from the lack of a trend variable. As UFC’s popularity dramatically increased throughout the period included in the dataset, the price of its pay-per-views also rose. The model falsely supports the idea that the rise in price is responsible for

17 increased pay-per-view buys, whereas the passage of time coinciding with a dramatic increase in the sport’s popularity is a much more reasonable explanation for increase in buy rates. Other dubious results included the extremely high coefficient for featherweight (135-pound weight class) title fights, which conflicts with the conventional wisdom that larger fighters attract a larger audience. One explanation is that featherweight championship fights are more likely than championship fights in heavier weight classes to be featured on an event but not as the main-event. Thus, featherweight championship fights may appear to be more popular than they are because they appeared on events where another fight was the driving force behind those particular events’ sales.

Again, the model suffers from poor specification that makes the coefficients of each variable a poor representation of reality. My model will correct for this by identifying not only the presence of championship fights but their placement on an event’s card.

This study also aimed to find the importance of an event’s timing by measuring the number of days between events as well as occurrences such as events held on holiday weekends and Super Bowl weekend. One would assume that events spaced farther apart will sell more pay-per-views because two events taking place in close proximity may force consumers to choose one over the other. Although Watanabe’s model found no significance surrounding the timing of shows in relation to each other, my model will also attempt to measure the effect of timing; however, my model will also include variables measuring the impact of surrounding events’ success on a particular pay-per- view. In other words, it will measure whether consumers base their decision to buy a particular event today on whether they bought the most recent event and whether they plan on buying an upcoming event in the future. One would assume that a highly

18 successful pay-per-view will harm the sales of the next pay-per-view because some consumers were forced to choose which one they would prefer to buy.

My model aims to learn from the lessons and mistakes of Tainsky et al. and

Watanabe. It will attempt to determine pay-per-view demand by analyzing a variety of factors included in the aforementioned studies such as the presence of championship fights and timing differences. It will also include new variables, such as the number of days each event is removed from the next WWE event. This will attempt to measure how much of a crossover exists between the UFC audience and the WWE audience, and it will form the basis for this thesis’ discussion of WWE’s decision to move to a subscription- based service and UFC’s decision to continue using the traditional pay-per-view model for the foreseeable future. This discussion will contribute to our general understanding of shifting consumer preferences in a digitized age with many forms of cheap entertainment options at our fingertips.

CHAPTER IV

METHODOLOGY

Data Selection

My model aims to determine the numerous factors that affect UFC’s pay-per-view buy rates, paying particular attention to the trend in buy rates from 2006 to 2013 as well as WWE’s overall effect on UFC’s buy rates. The Trend and Trend2 variables will measure the effect of time on UFC’s and WWE’s pay-per-view revenues. The Same

Weekend dummy variable will measure the effect of WWE’s pay-per-view business on

UFC’s pay-per-view revenues. The remaining independent variables will control for those variables by eliminating potential omitted variable biases. Using the model’s results, this thesis will analyze the UFC’s and WWE’s decisions regarding their business models. This analysis will help contribute to our understanding of consumer preferences between subscription based entertainment services and their “pay once, watch once” counterparts.

Data for UFC and WWE pay-per-view buy rates was gathered from weekly issues of the Wrestling Observer Newsletter (f4wonline.com), other relevant UFC data was gathered from mixed martial arts websites sherdog.com and tapology.com, and other relevant WWE data was gathered from wwe.com and cagematch.net.

The model will implement a seemingly unrelated regression (SUR) system to measure the factors that determine UFC buy rates. A seemingly unrelated regression is used when two equations have contemporaneous cross-equation error correlation. We expect the presence of contemporaneous cross-equation error correlation in this case because the two dependent variables rely on two substitute products offered by two rivals in a single market. My model, while primarily focusing on UFC pay-per-view revenue, will also measure the UFC’s impact on WWE’s pay-per-view revenue. The seemingly unrelated regression tool recognizes this correlation and corrects for it.

While many variables from Tainsky et al. (2013) and Watanabe’s (2012) studies will be used, the most notable difference is that my model will attempt to measure revenue as the dependent variables instead of simply measuring pay-per-view buys. In doing so, my model will measure a dollar figure as the dependent variables instead of a figure which is measured in units. This will allow the model to explain the own-price and cross-price elasticity of UFC and WWE pay-per-views, as both companies raised pay-per-view prices at least once during the time period measured in the data set. In this case, an elasticity greater than one would indicate that a price increase had a negative effect on total revenues. An elasticity less than one would indicate that raising the price increased total revenues.a Another important difference is that my model will use the natural log of revenue; this will help reduce skewness present in the distribution of pay- per-view revenues. Using the natural log is appropriate in this case because neither dependent variable contains negative or non-zero values. The full variable names for the

푑푅 푑푄 푃 a = 푄(1 − 휀 ); 휀 = × 푑푃 푑 푑 푑푃 푄

21 two dependent variables will be ln(UFC Revenue) and ln(WWE Revenue). The coefficient values will be multiplied by 100 in order to present them in percentage terms.

My model will include a both a daily trend variable (Trend) as well as the squared values of that variable (Trend2). These variables allow the model to take time into account when measuring pay-per-view revenue from 2006 to 2013; since the UFC went through a period of majorly increasing popularity during this period, it is appropriate to measure the impact time has had on revenues. Since many observers have noted the slowing of this increasing popularity, it is also appropriate to include squared values. If the Trend2 coefficient is negative and significant, this would indicate that the UFC’s pay- per-view revenues are in the process of declining over time. This would lend support to the decision to switch from UFC’s current pay-per-view model to a subscription-based network in the near future, as the opportunity cost of moving away from pay-per-view decreases over time.

The model will also include variables which measure the effect of timing of UFC events. Economic theory would suggest that a consumer with a constrained budget is more likely to purchase two UFC events if they separated by a long period of time than if they are separated by a short one. Since consumers must allocate their limited resources towards goods and services in order to maximize their utility, and since UFC pay-per- view events cost a significant amount of money ($44.95 for standard definition), UFC fans may have to choose between one of two events in a given time period. The longer this time period is, the more likely it is that these consumers have earned more resources with which to distribute to various forms of entertainment, and thus the more likely it is that they will choose to purchase both events. Thus, variables that measure the number

22 of days since another pay-per-view occurred ln(Days Since UFC) as well as the number of days until another pay-per-view will occur ln(Days Until UFC) are included in the model. Variables which measure the revenue of previous and upcoming pay-per-views

(ln(Previous UFC Revenue) and ln(Next UFC Revenue)) are also included. Using the same economic theory, fans who purchased the most recent pay-per-view, as well as fans who plan to purchase the pay-per-view in the next period, are less likely to allocate their budgets to buying a pay-per-view today. Thus, theory states that a pay-per-view held today will raise more revenue if the previous (and next) pay-per-view raised a particularly low amount revenue than if it raised a high amount. Corresponding WWE variables are also included in the second part of the seemingly unrelated regression

(ln(Days Since WWE), ln(Days Until WWE), ln(Previous WWE Revenue), and ln(Next

WWE Revenue)).

As Tainsky et al. demonstrated in their study, pay-per-views are more likely to be successful if consumers are uncertain about the outcome in the most important fight of that particular event, as uncertain outcomes are more exciting. Main Betting Odds and

Co Betting Odds are two variables which measure the level of uncertainty of the two main fights occurring during a particular event. These two fights are most likely to sell the event itself; as such, they are the most valuable. The two variables use Las Vegas betting odds (collected from tapology.com) in order to measure the general public’s level of uncertainty heading into an event; higher values for these variables represent lower levels of uncertainty, and thus theory states that these variables should have a negative relationship with pay-per-view revenue.

Tainsky et al. attempted to measure the value of having “stars” compete on a particular pay-per-view event. The study confirmed the commonly held belief that consumers are more likely to purchase an event if it features competitors with whom the consumer is familiar. As measuring superstardom is perhaps the most difficult variable to quantify, yet perhaps among the most important in determining pay-per-view revenue, my model will include a number of variables that attempt to quantify a competitor’s familiarity with the general UFC audience. Main Title Defenses and Co Title Defenses will measure the number of championship defenses a current champion in either the main event or the co-main event has heading into a particular show. If there is no champion present in either of these fights, the value “0” will be used. A higher number of championship defenses should correspond to a higher level of familiarity with the fans; this, in turn, should result in higher levels of revenue for a particular event. Main

Champs and Co Champs will simply measure the number of champions and former champions present in the main event and co-main event of a particular show. These are ordinal variables with a minimum value of “0” and a maximum value of “2.” Those who have won championships inside the UFC at one point in their career are more likely to have a higher level of familiarity with UFC fans, so these variables should have a positive relationship with revenue.

The amount of advertising and “hype” leading into an event should theoretically be directly related to the amount of revenue that event raises. Two dummy variables will measure the impact of extraordinary advertising for UFC pay-per-views. TUF Coaches represents events where two competing “coaches” of opposing teams on the UFC’s reality show, The Ultimate Fighter, fight each other. While The Ultimate Fighter’s

24 primary purpose is to introduce new fighters to the promotion, it also serves to promote an upcoming fight between two well-known fighters who coach opposing teams of relatively newer fighters. Since this includes more than a dozen weekly hour-long episodes on basic cable, it advertises the coaches’ fight much more than a main event fight is normally advertised. Primetime, on the other hand, indicates events which have been advertised with the UFC Primetime television program. Unlike The Ultimate

Fighter, Primetime records the fighters’ training camps and interviews the fighters, as well as their coaches and families, with three 30-minute episodes. Only thirteen events have been advertised using Primetime ahead of time, distinguishing its use from the traditional advertising heading into a UFC event.

Irregularities which could potentially alter the revenue of a particular event were included as dummy variables. Some events have been aired on pay-per-view with a tape delay because they were recorded in foreign countries; since sports fans have traditionally been more eager to witness sports live as they take place, theory holds that these events should raise lower amounts of revenue than events which air live. Delay is used to distinguish these events. 9 p.m. is used to distinguish the eleven UFC events which aired at 9 p.m. ET instead of the traditional 10 p.m. The UFC made the switch to 9 p.m. in

March 2007 before returning to 10 p.m. in December of that year. The fact that UFC switched back to 10 p.m. may indicate that they were raising less revenue when their shows aired at 9 p.m.

Since familiarity with competitors is key to a pay-per-view’s success, two particular individuals are included in the model to measure their impact on UFC’s success. Georges St.-Pierre and Brock Lesnar, the two biggest stars in the UFC during

25 the examined time period, developed levels of superstardom beyond that which other

UFC champions have reached. GSP is an ordinal variable that measures St.-Pierre’s impact on revenue with each consecutive event in which he competes; as there are fourteen observations in the dataset, the values for this variable range from 0-14. As St.-

Pierre’s popularity grew immensely during this time period, this variable should have a direct relationship with revenue. Lesnar, similarly, measures Brock Lesnar’s impact with each of his seven appearances; its values range from 0-7. Lesnar2, a variable which simply squares the values of the previous variable, is used to account for the observation that Lesnar’s pay-per-view numbers lowered after he began to expose more of his weaknesses as his career continued. If this observation holds true, the variable will have an inverse relationship with pay-per-view revenue. Large Main represents events in which the main event was a heavyweight (265 pounds) or light-heavyweight (205 pounds) fight. As these are the two largest weight classes, this dummy variable will control for the commonly held belief that larger fighters are both bigger stars and bigger pay-per-view draws.

UFC Price will represent the price variable for UFC events. At the beginning of this dataset, the price of all UFC events was $39.95. In 2008, the price rose to $44.95.

WWE Price will represent the price variable for WWE events. Prices for WWE pay-per- views rose twice in five-dollar increments from $34.99 to $44.99 during the period captured by the dataset (except for the annual WrestleMania event, which is traditionally priced at $10 more than other pay-per-views). Since the dependent revenue will be revenue rather than buy rates, the price variable will indicate whether the decision to raise

26 the price had a positive, negative, or insignificant effect on total revenue for pay-per-view events.

The final variable for the first part of the seemingly unrelated regression, Same

Weekend, will measure the impact on both WWE’s and UFC’s pay-per-view revenue when a UFC event precedes a WWE event on the same weekend. While UFC and WWE pay-per-views each occur about twelve to fifteen times per year, these events are scattered unevenly. The gap between two pay-per-views held by either company may range from two to six weeks. Since UFC pay-per-views always occur on Saturday evenings and WWE pay-per-views always occur on Sunday evenings, occasionally both events will air on one weekend. As explained above, the timing between two UFC events may impact each event’s revenue because consumers may be forced to choose between two events that are closer together in proximity. Likewise, fans of both UFC and WWE may also have to choose between a UFC pay-per-view and a WWE pay-per-view that are close in proximity. The case where both events occur on the same weekend is the best representation of this phenomenon. My model will measure the effects on both UFC and

WWE pay-per-view revenue when the two events are separated by one day. If revenues are shown to be lower during these events, it would lend credibility to the argument that the two products are substitutes in the eyes of consumers. A greater (negative) impact on revenue would suggest a greater degree of substitutability. This would suggest that the substitution effect discussed in the theory section of this thesis will be greater in relation to the income effect, further lowering UFC’s pay-per-view revenues as a result of

WWE’s dramatic price drop.

The two remaining variables used to measure WWE pay-per-view revenue include WrestleMania and Royal Rumble/Summerslam. The first variable is a dummy variable that indicates when WWE’s largest and consistently most-ordered annual pay- per-view, WrestleMania, occurs. This dummy should have a very significant direct relationship with WWE pay-per-view revenue. The second variable is another dummy which measures when WWE’s “second-tier” annual pay-per-views (consistently raising the second and third-most amount of revenue each year), the Royal Rumble and

Summerslam. Both variables should also be significantly positive, but not to the degree that WrestleMania’s variable should be.

Seemingly Unrelated Regression Model ln(UFC Revenue) = A + β1(Trend) + β2(Trend2) + β3(Days Since UFC) +

β4(Days Until UFC) + β5(Previous UFC Revenue) +

β6(Next UFC Revenue) + β7(Main Betting Odds) +

β8(Co Betting Odds) + β9(Main Title Defenses) +

β10(Co Title Defenses) + β11(Main Champs) + β12(Co Champs) +

β13(TUF Coaches) + β14(Primetime) + β15(Delay) + β16(9 p.m.) +

β17(GSP) + β18(Lesnar) + β19(Lesnar2) + β20(Large Main) +

β21(UFC Price) + β22(Same Weekend) + ε ln(WWE Revenue) = A + β1(Trend) + β2(Trend2) + β3(Days Since WWE) +

β4(Days Until WWE) + β5(Previous WWE Revenue) +

β6(Next WWE Revenue) + β7(WrestleMania) +

β8(Royal Rumble/Summerslam) + β9(WWE Price) +

β10(Same Weekend) + ε

Summary Statistics

Table 4.1 and Table 4.2 provide summary statistics for all variables involved in each part of the seemingly unrelated regression model. There are 101 observations for each dataset.

TABLE 4.1

UFC PAY-PER-VIEW SUMMARY STATISTICS (2005-2013)

Variable Mean Std. Dev. Min Max ln(UFC Revenue) 9.88 0.48 8.75 11.18 Trend 1484.15 795.67 1.00 2814.00 Trend2 2829526.00 2359073.00 1.00 7918596.00 ln(Days Since UFC) 3.29 0.37 2.64 4.34 ln(Days Until UFC) 3.28 0.35 2.64 4.01 ln(Last UFC Revenue) 9.87 0.49 8.75 11.18 ln(Next UFC Revenue) 9.88 0.48 8.75 11.18 Main Betting Odds 576.33 394.34 210.00 2150.00 Co Betting Odds 510.78 320.96 221.00 2500.00 Main Title Defenses 1.52 2.35 0.00 10.00 Co Title Defenses 0.13 0.63 0.00 5.00 Main Champs 1.47 0.52 0.00 2.00 Co Champs 0.68 0.73 0.00 2.00 TUF Coaches 0.09 0.29 0.00 1.00 Primetime 0.12 0.33 0.00 1.00 Delay 0.06 0.24 0.00 1.00 9 p.m. 0.11 0.31 0.00 1.00 GSP 1.04 3.01 0.00 14.00 Lesnar 0.28 1.15 0.00 7.00 Lesnar2 1.39 6.69 0.00 49.00 Large Main 0.50 0.50 0.00 1.00 UFC Price 43.87 2.07 39.95 44.95 Same Weekend 0.14 0.35 0.00 1.00

TABLE 4.2

WWE PAY-PER-VIEW SUMMARY STATISTICS (2005-2013)

Variable Mean Std. Dev. Min Max ln(WWE Revenue) 9.32 0.57 8.60 11.14 Trend 1484.15 795.67 1.00 2814.00 Trend2 2829526.00 2359073.00 1.00 7918596.00 ln(Days Since WWE) 3.26 0.30 2.64 3.89 ln(Days Until WWE) 3.32 0.30 2.64 3.89 ln(Previous WWE Revenue) 9.28 0.46 8.19 11.04 ln(Next WWE Revenue) 9.40 0.61 8.60 11.14 WrestleMania 0.08 0.27 0.00 1.00 Royal Rumble/Summerslam 0.15 0.36 0.00 1.00 WWE Price 43.26 3.84 34.99 54.99 Same Weekend 0.14 0.35 0.00 1.00

CHAPTER V

RESULTS & ANALYSIS

TABLE 5.1

SEEMINGLY UNRELATED REGRESSION RESULTS

Dependent Variable Obs Parms RMSE “R-sq” Chi2 P ln(UFC Revenue) 101 22 0.225 0.777 355.54 0.000 ln(WWE Revenue) 101 10 0.174 0.906 976.52 0.000

TABLE 5.2

LN(UFC PPV REVENUE) AS DEPENDENT VARIABLE

Variable Name Coefficient Std. Err. z-statistic P>|z| Trend 0.0563 0.0231 2.44 0.015 Trend2 -2.6E-05 6.6E-06 -3.95 0.000 ln(Days Since UFC) 15.7826 8.1136 1.95 0.052 ln(Days Until UFC) 5.9725 7.9279 0.75 0.451 ln(Previous UFC Revenue) 3.7413 5.6541 0.66 0.508 ln(Next UFC Revenue) -11.8836 5.5975 -2.12 0.034 Main Betting Odds 0.0039 0.0071 0.56 0.579 Co Betting Odds 0.0027 0.0079 0.34 0.732 Main Title Defenses 8.0214 1.2489 6.42 0.000 Co Title Defenses 8.3624 4.0024 2.09 0.037 Main Champs 12.8103 5.2187 2.45 0.014 Co Champs 13.5316 3.3418 4.05 0.000 TUF Coaches 27.8539 9.2342 3.02 0.003 Primetime 43.2089 8.0324 5.38 0.000 Delay -26.0293 11.6034 -2.24 0.025 9 PM -18.2974 8.2831 -2.21 0.027 GSP 3.5219 0.9754 3.61 0.000 Lesnar 32.2169 9.0333 3.57 0.000 Lesnar2 -3.8929 1.5261 -2.55 0.011 Main Large 26.1225 5.7675 4.53 0.000 UFC Price 0.8278 2.5524 0.32 0.746 Same Weekend -18.9209 7.4539 -2.54 0.011

TABLE 5.3

LN(WWE PPV REVENUE) AS DEPENDENT VARIABLE

Variable Name Coefficient Std. Err. z-statistic P>|z| Trend -0.0220 0.0116 -1.90 0.057 Trend2 4.0E-06 3.2E-06 1.23 0.219 ln(Days Since WWE) 20.6541 8.4298 2.45 0.014 ln(Days Until WWE) -5.9654 8.5790 -0.70 0.487 ln(Previous WWE Revenue) 0.3988 4.3831 0.09 0.928 ln(Next WWE Revenue) 7.3540 4.2666 1.72 0.085 WrestleMania 162.1415 15.2474 10.63 0.000 Royal Rumble/Summerslam 70.1302 5.9778 11.73 0.000 WWE Price 1.1962 1.2960 0.92 0.356 Same Weekend 6.7112 6.0605 1.11 0.268

The seemingly unrelated regression has an R-squared value of 0.777 for UFC pay-per- view revenue and a value of 0.906 for WWE pay-per-view revenue. The higher value for

WWE events is normal because these shows generally have more buy rates (save for the three major shows) compared to UFC events; as previously mentioned, WWE shows will all typically feature the same major stars while stars in the UFC can typically only appear on three events per year.

The model found an initially positive but decreasing trend for UFC events, suggesting that the promotion’s popularity did increase during the time-period captured by the dataset, but its current pay-per-view business is declining. In fact, the trend line suggests that the company is currently in a period of earning considerably less revenue per show than the constant and seems to only be doing worse as time goes on:

FIGURE 5.1

GRAPH OF UFC REVENUE PER EVENT TREND LINE (FEBRURARY 4, 2006 – OCTOBER 19, 2013)

This is consistent with observations made by mixed martial arts journalists; however, the model does not explain if this decline is due to a decrease in UFC’s overall popularity oer consumers’ growing reluctance to pay upwards of $45 for a single event. UFC may change its decision to continue selling pay-per-views the traditional way if numbers continue to decline.

The model did find some significant timing effects: the number of days between events seems to impact the total number of buys as I hypothesized above. An event held today will generate more buys if the number of days since the previous event is greater; this complies with economic theory. Additionally, the revenues of future pay-per-views affect the number of buys for an event held in the current time period. It appears fans will hold off on purchasing an event in the current time period if they anticipate that they will purchase an event in the future, as higher revenues for future events have a negative impact on current pay-per-view revenues.

Betting odds seem to have an insignificant effect on pay-per-view revenues, indicating that fans of the sport will generally not be less likely to purchase a particular event if the main event or co-main event have more predictable outcomes. Star power, on the other hand, plays a major role in determining revenues. The two variables for title defenses and the variables that measure the presence of current or former champions both indicate with significant results that fans will be more likely to purchase an event if they are familiar with the fighters involved and those fighters have displayed the skills to become a champion. Additionally, promoting these fighters is just as important. Events that are advertised either through The Ultimate Fighter or Primetime generate significantly more revenue. It is important to note that these effects would probably be diluted if the UFC attempted to maximize revenue for every single event with these promotional tools. Also, Primetime typically only covers events that feature fighters who are already popular with fans of the sport, so these events would almost certainly generate higher revenues even if there were no Primetime coverage. Airing pay-per-view on a tape delay has a significantly negative impact on revenue, as does airing pay-per- views at 9 p.m. ET instead of 10 p.m. Events featuring larger fighters in the main event will generate more revenue.

Pay-per-view prices have an insignificant impact on total revenues raised by each pay-per-view. This suggests that demand for UFC events is somewhere near 1; although some fans may be willing to purchase an event for $40 but not $45, raising the price of pay-per-views has not had a noticeably negative impact on total revenue. It did not appear to have a noticeably positive impact either.

The variable which measures when UFC and WWE pay-per-views are held on the same weekend indicates that this type of occurrence significantly negatively impacts

UFC revenues. In fact, these UFC events generate 18.9% less revenue than others. This suggests that there is indeed a major crossover between fans of UFC and fans of WWE, and thus the two products exhibit a great degree of substitutability. This suggests that the substitution effect on consumers after WWE’s switch to a digital network will be large.

This will negatively impact UFC’s future pay-per-view revenues which the model indicates are already declining. If UFC’s pay-per-view revenues decline to the point at which WWE’s were, they may have to reconsider the format through which they generate their revenues.

WWE revenues exhibited a significantly negative trend throughout the time period captured by the dataset. Timing effects were also present, as an event held in the current period generates more revenue when the number of days since the previous event is greater. Interestingly, an event held today appears to generate more revenue if an event held in the future generates more revenue. This is the opposite impact displayed by UFC shows. Again, it is important to note the differences between the two products. A UFC fan may opt out of purchasing an event today in order to purchase an event in the future which features an entirely different group of fighters. A WWE fan generally doesn’t make decisions this way because an event held in the future will feature almost the exact same wrestlers as an event held today. Price appears to have little effect on total revenues, suggesting that demand for WWE’s product is also somewhat inelastic.

Interestingly, WWE events held the day after UFC events actually appear to generate more revenue, but the effect is too insignificant to say that with confidence. For

35 whatever reason, the effect on UFC’s revenues is significantly negative while the effect on WWE’s revenues is minimal when both events are held on the same weekend. This does not undermine the assertion that the two products are substitutes to consumers.

CHAPTER VI

CONCLUSION

The model confirmed two important facts regarding UFC’s pay-per-view structure. The first is that revenues for pay-per-views are declining as time progresses.

The second is that UFC’s and WWE’s products, although different in many ways, are substitutes in the eyes of consumers.

While UFC continues to be a leader in the pay-per-view industry, its ability to garner increasing amounts of revenue through that line of business appears to have passed its prime. This could represent a lack of fan interest in the current breed of top mixed martial artists; some have argued that today’s champions, while more athletic and more skilled than champions of the past, are simply not as marketable and lack interesting personalities. It could also be the case that the company’s massive increase in popularity was just a phase. Perhaps the most compelling argument, however, is that consumers are simply less willing to purchase a single event for $45 even if their interest in the product has not decreased at all. With cheaper entertainment alternatives becoming more available as time goes on, it is unsurprising that consumers will simply refuse to continue paying up to $45 for a single event on a television set.

The arrival of the WWE Network will be yet another cheap entertainment alternative which operates by selling relatively cheap subscriptions; unfortunately for

UFC, the product offered by the network appears to be a close substitute for UFC events

(much closer than movies offered by Netflix or television shows offered by Hulu). This will almost certainly instill a substitution effect on consumers, who will be much more willing to pay $10 for a full month of entertainment options than $45 for a show that lasts less than three hours. This will cause consumers to purchase even fewer pay-per-view events, lowering that form of revenue even further than the decreasing trend line predicts.

UFC has laid the groundwork for a potential switch from pay-per-view to a subscription-based service with UFC Fight Pass. Although selling pay-per-views may be the most profitable option right now, the company may be better off by offering all of its events on UFC Fight Pass in the future if revenues continue to decline. When they make this decision will depend on how quickly revenues will continue to decline. This thesis presents a model which supports the hypothesis that a substitution effect resulting from the launch of the WWE Network will only further decrease a revenue stream for UFC that is already decreasing. UFC may soon reach as low as WWE’s yearly revenues sooner than it thinks; at this point, it would be wise to evaluate WWE’s success with the

WWE Network before emulating their model.

If WWE reaches or exceeds the number of subscribers it expects within that time period, it could lend support to the hypothesis that monthly subscription services are becoming a more profitable revenue stream than charging a higher rate for a one-off event. If this is the case, WWE will prove to have made a wise bet in being the “first- mover” in this scenario. It will benefit from having established a contingent of subscribers before UFC Fight Pass is able to. If the company does not reach its target number of subscribers, their decision to switch will likely lead to less revenue than if they had simply remained on pay-per-view. UFC will have the benefit of being able to see

38 how successful the model proves to be for WWE. Dana White and his colleagues are happy to not take the risk themselves. WWE has taken a substantial risk in order to possibly cash in on a major reward. Lower pay-per-view revenues coupled with their strong foothold in revenue streams outside of the pay-per-view industry, particularly cable TV rights, probably gave them more of an incentive to take that risk than the UFC has currently. Because UFC is much more reliant on pay-per-view in comparison to

WWE, it has much more to lose by completely changing that model. Still, the results presented in this thesis suggest that refusing to take a risk in response to a rival’s extraordinary price decrease may prove to be shortsighted on UFC’s part. Should UFC’s pay-per-view revenues decline at an increasing rate, firms in other industries may learn from UFC’s decision by learning to have a more open view of which products are substitutes in consumption. This will allow them to respond effectively when a rival firm takes a large risk by drastically decreasing prices.

APPENDIX

TABLE A.1

VARIABLE DESCRIPTIONS

Variable Name Description Dependent Variable ln(UFC Revenue) Dependent variable: natural log of each UFC event’s pay-per-view revenue ln(WWE Revenue) Dependent variable: natural log of each WWE event’s pay-per-view revenue Trend Trend variable, measured in days UFC; WWE Trend2 Squared trend variable, measured in days UFC; WWE Days Since UFC # of days since the most recent UFC pay-per-view event UFC Days Until UFC # of days until the upcoming UFC UFC pay-per-view event Previous UFC Revenue Previous UFC event’s pay-per-view revenue UFC Next UFC Revenue Next UFC event’s pay-per-view revenue UFC Main Betting Odds Las Vegas betting line odds for main event of UFC each UFC event (higher numbers indicate heavier favorite) Co Betting Odds Las Vegas betting line odds for co-main event UFC of each UFC event (higher numbers indicate heavier favorite) Main Title Defenses Number of previous successful championship UFC defenses for champion heading into main event (if applicable) Co Title Defenses Number of previous successful championship UFC defenses for champion heading into co-main event (if applicable) Main Champs Ordinal variable (0-2); number of current or UFC former UFC champions in the main event

TABLE A.1 – Continued

Variable Name Descrpition Dependent Variable Co Champs Ordinal variable (0-2); number of current or UFC former UFC champions in the co-main event TUF Coaches Dummy variable; indicates when an event UFC contains a fight between opposing Ultimate Fighter coaches Primetime Dummy variable; indicates when an event has UFC been promoted with UFC Primetime program Delay Dummy variable; indicates when an event’s UFC pay-per-view broadcast aired on tape delay in North America 9 PM Dummy variable; indicates when a pay-per view UFC broadcast began one hour before the usual start time of 10 PM EST GSP Ordinal variable (0-14); indicates if an event UFC contains one of George St.-Pierre’s 14 fights within the dataset Lesnar Ordinal variable (0-7); indicates if an event UFC contains one of Brock Lesnar’s 7 fights within the dataset Lesnar2 Ordinal variable (0-49); squared Lesnar variable UFC Main Large Dummy variable; indicates when an event’s UFC main event contains fighters in the 205-lb. or 265-lb. weight class UFC Price Pay-per-view price in North America for each UFC UFC event Days Since WWE # of days since the previous WWE pay-per-view WWE Days Until WWE # of days until the next WWE pay-per-view WWE Previous WWE Previous WWE event’s pay-per-view revenue WWE Revenue Next WWE Next WWE event’s pay-per-view revenue WWE Revenue WrestleMania Dummy variable; indicates the occurrence of the WWE annual Wrestlemania pay-per-view event Royal Rumble/ Dummy variable; indicates the occurrence of the WWE Summerslam annual Royal Rumble and Summerslam events WWE Price Pay-per-view price in North America for each WWE WWE event Same Weekend Dummy variable; indicates when a UFC pay- UFC; per-view event airs one day prior to a WWE WWE pay-per-view event

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