¿Divide y vencerás? Un modelo para la retransmisión

deportiva OTT en directo.

Divide and Conquer? A Model for Live

OTT Sports Streaming

ARTICLE

University of Florida

Roxane Coche (Mass communication, University of North Carolina) is an associate professor

and the interim chair of the Department of Media Production, Management, and Technology

at the University of Florida. Her priority in research is to better understand the fast-changing

global environment and to capture the relationships among sports, media, and social issues.

rcoche@u.edu

ORCID: https://orcid.org/0000-0003-4100-3059

University of Florida

Benjamin J. Lynn, Ph.D., (Mass communication, University of Florida) is an adjunct instructor at

the University of Florida’s College of Journalism and Communications. His research is focused

on live broadcasting generally and explores social issues in sports broadcasting.

b.lynn@u.edu

ORCID: https://orcid.org/0000-0002-0885-9077

Roxane Coche

Benjamin J. Lynn

OBRA DIGITAL, 24, December 2023, pp. 31-49, e-ISSN 2014-5039

DOI: 10.25029/od.2023.382.24

3232

Divide and Conquer? A Model for Live OTT Sports Streaming.

Abstract

The current study examined if multi-tiered of-

ferings of a sports broadcast (three levels aimed

at new sports fans, traditional sports fans, and

hardcore sports fans) would increase a viewer’s

intention to watch sports. Results reveal one’s

level of sports fandom may increase if broad-

casters implemented a feasible multi-tiered

model of streaming sports based on three

fandom levels, and viewers, even hardcore

fans, like the idea of an introductory broadcast

that explains in more detail the sport they are

watching—perhaps because it could help them

fulll their willingness to consume more sports

through fantasy and betting.

KEYWORDS

Sports; broadcasting; digital media; fandom;

television

Resumen

El presente estudio examinó si un modelo de

retransmisión deportiva en streaming de va-

rios niveles (tres niveles dirigidos a los nuevos

acionados al deporte, a los acionados tra-

dicionales y a los acionados incondicionales)

aumentaría la intención del espectador de ver

deportes a través de una encuesta cuantitativa

de adultos en Estados Unidos. Los resultados

revelan que el nivel de ación a los deportes

podría aumentar si los organismos de radio-

difusión aplicaran este modelo de retransmi-

sión, y que, a los espectadores, incluso a los

acionados fanáticos, les gusta la idea de una

retransmisión introductoria que explique con

más detalle el deporte que están viendo, tal vez

porque podría ayudarles a satisfacer su deseo

de consumir más deportes a través de la fanta-

sía y las apuestas.

PALABRAS CLAVE:

Deportes, Radiodifusión, Medios digitales, Fan-

dom, Televisión.

University of South Carolina

Matthew J. Haught, Ph.D., (Mass communication, University of South Carolina) is a professor in

the Department of Journalism and Strategic Media at the University of Memphis. His research

explores visual communication and technology across a spectrum of uses, from

health communication to sports media.

mjhaught@memphis.edu

RECEIVED: 2023-05-10 / ACCEPTED: 2023-06-27

Matthew J. Haught

1. INTRODUCTION

“If we can get 68,000 to watch an MLS game

in person, why can’t we get 300K to watch at

home?” asked the voice of the Major Soccer

League’s Los Angeles Football Club and tele-

vision anchor, Maximiliano Bretos (2022). Re-

search is scarce on this issue, but we know the

knowledge required to comprehend a sports

broadcast is likely acquired by watching or at-

3333

Roxane Coche, Benjamin J. Lynn, Matthew J. Haught

tending sporting events and/or speaking with

others about sports (Giulianotti, 2015). One

does not simply turn on the television and

suddenly understand a sports broadcast. Yet,

broadcasters assume a viewer can fully process

the information presented, including the rules

of the sport, the language used to describe

the sport, and the graphics presented on the

screen. Uninitiated viewers may not be capable

of mentally processing these various elements,

which could lower their motivation for watch-

ing sports. That matters to traditional sports

broadcasters because it raises questions about

the sustainability of their business models. If

they cannot eectively initiate new viewers,

their audience could drastically decline as old-

er viewers stop watching. In fact, viewers’ aver-

age age for most sports has steadily increased

since the turn of the century (Notte, 2017).

With the rise of esports, which are broadcast

dierently, the fragmentation of audiences gen-

erally, and the COVID-19 pandemic (Buehler,

2020; Hutchins & Boyle, 2017; Lynn et al., 2021;

Steinkuehler, 2019; Takahashi, 2019), tradition-

al sports broadcasters face mounting pressure

to sustain the viewership levels that they once

enjoyed (Buehler, 2020; Reimer, 2021). Aca-

demically, this pressure matters because the

pathway from uninitiated viewer to full sports

fan has not been adequately tested, a gap the

current study seeks to address. Further, re-

cent technological changes allow for new ways

of testing theoretical models of fandom and

sports viewership, which could benet the rise

of under-covered sports, including women’s

sports (Coche, 2016; Cooky et al., 2021) and pa-

ra-sports (Watson, 2020).

This study explores an idea that could help

dene a new theoretical model to rejuvenate

sports fans, and help sports broadcasters turn

a new leaf: what if sports broadcasters pack-

aged their product dierently based on fan-

dom? A newer audience member would watch

a feed containing more explanation so they

have a chance to learn the game, a casual view-

er/fan would watch a feed similar to the tradi-

tional feed, and a “hardcore fan” would watch a

feed with more facts, more jargon, more insid-

er knowledge, etc. As a traditional medium of

mass communication, television does not make

this model possible as everyone must watch

the same content. However, it would be easy to

implement digitally, and at fairly minimal cost.

In fact, oering dierent teams of commenta-

tors has already been done (e.g., Fingas, 2018).

This study uses this concept to test whether

people may be interested in a multi-stream

model based on people’s level of fandom for

live sporting events.

2. CONTEXT: THE FUTURE

OF SPORTS BROADCASTING

Online companies have recently bought broad-

casting rights for big sporting events. Some re-

cent examples include Amazon picking up the

partial rights of the WNBA in the U.S. (Porter,

2021), the bulk of the Ligue 1 rights in France,

some UEFA Champions League matches in

Germany and Italy, or, notably in the full broad-

cast rights of the powerful NFL for Thursday

Night Football in the U.S. (Kayali et al., 2021).

The online giant has become a central power

broker in the global sports broadcasting polit-

ical economy (Kunz, 2020).

In parallel, sports organizations (notably teams

and leagues) have been increasing their dig-

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Divide and Conquer? A Model for Live OTT Sports Streaming.

ital content oers to keep their fans engaged

all year long (Laharie, 2017), with international

soccer governing body FIFA the latest to launch

its streaming service (Forristal, 2022). These

digital-only companies or departments provide

engaging content (Kim & Kim, 2020; Wymer et

al., 2021), competing with television networks

for audience attention. To ght back, television

networks have oered digital content online for

a few years, but online specialists may be bet-

ter placed to take advantage of all digital has to

oer. For instance, though NBC has oered ad-

ditional Olympic coverage online for over a dec-

ade, the network still tailors its online content

for its traditional television broadcast (Sipocz

& Coche, 2019). Online companies are not

restricted by any such “traditional broadcast”;

they can oer something new at a time when

online streaming has become “an important

source of new business opportunities” (Feng et

al., 2020, p. 2).

With technology innovation more rapid than

ever (Winarski, 2019), media professionals and

media scholars have worked to understand and

harness the power new technologies have on

their industry, and better serve their fragment-

ed audience. In American sports, a good exam-

ple from the early 2010s is the creation of the

NFL RedZone channel. On this commercial-free

channel, the football league dissects every

touchdown made in every game and provides

various game statistics to viewers who pay for

the service. It is “constant action,” channel host

Scott Hanson says (cited in Farmer, 2019), and it

caters to those with short attention span (Farm-

er, 2019) all while providing a “football nirvana”

to die-hard fans, fantasy players, and gamblers

(Brown, 2012). With streaming advances over

the past decade, a full channel is no longer

needed to reach (potential) fans. Hence, the

present study examines if multi-tiered oer-

ings of a sports broadcast (three levels aimed

at new sports fans, traditional sports fans, and

hardcore sports fans) would increase a viewer’s

intention to watch sports.

3. LITERATURE REVIEW

Sports broadcasters have historically benet-

ted from the “feeling of presence” (Cummins,

2009, p. 376) one gets watching a game live. In

a nutshell, people who watch live sports may

have the sentiment of being at the stadium or

arena and can also feel less lonely (Cummins,

2009; Kim & Kim, 2020). That is why, Cum-

mins (2009) argues, “content producers and

hardware manufacturers are eager to develop

viewing experiences that facilitate this sense

of ‘being there’ in a mediated environment as

a means of attracting viewers and advertising

dollars” (p. 376). However, the current study’s

authors posit, this may come at the expense of

the understanding of the sport itself, which is

paramount to becoming a fan.

3.1. BECOMING A SPORTS FAN

The concept of sports fandom is not universal

(Gantz & Lewis, 2021). In a seminal study, Gantz

and Wenner (1995) used a binary variable, fans

vs. non-fans to identify sports consumers’ moti-

vations to watch sports. They claried non-fans

still consume sports, but not as much as fans

do and with less interest. This dichotomy was

used in many studies and expanded in others.

For instance, Hull and Lewis (2014) introduced

3535

Roxane Coche, Benjamin J. Lynn, Matthew J. Haught

a third type of fan, “the connected fan” (p. 18),

who emerged thanks to the creation of the

internet, which encourages interaction. Mean-

while, Giulianotti (2015) used two basic oppo-

sitions to create a quadrant to study football

clubs’ fans. He contends fans can be divided

into four types: (1) supporters, who “have in-

extricable biographical and emotional ties to

the club’s ground” (p. 258) almost as if it were

part of their family; (2) fans, who strongly iden-

tify with a club but tend to “have a more mar-

ket-centered relationship to [it] as reected in

the centrality of consuming club products”

(p. 251); (3) followers, who stay updated on a

club’s results and events, but do not identify as

strongly with it—or only for temporary compe-

titions; and (4) âneurs, who may occasionally

watch a club but have “no capacity to secure

personal alignment” with it (p. 259).

Since his inuential 1995 study with Wenner,

Gantz has also continued studying sports fan-

dom. He recently argued fandom is a contin-

uous spectrum and one’s level of fandom can

uctuate throughout their life (e.g., Gantz &

Lewis, 2021), but the question of what moti-

vates people to become sports fans remains.

What gratications do people get from con-

suming sports? The most inuential work on

the topic is Wann’s (1995) Sport Fan Motivation

Scale (SFMS), which is based on eight main con-

structs: aesthetic, economics, entertainment,

escape, eustress, family, group aliation, and

self-esteem. The scale has been tested, used,

and/or adapted by many scholars, including

for studies based on newer technology, such

as the internet, social media, and esports (e.g.,

Coche, 2014; Cushen et al., 2019). Knowing

what motivates people to watch and/or follow

sports is a crucial element for sports managers

and sports broadcasters as their goal is to grow

their audience and keep them loyal (Fortunato,

2008), i.e. have them go from âneur to follow-

er to fan or supporter on Giulianotti’s quad-

rant. It is poignant information for scholars and

industry professionals alike as a call for more

diversity in the media presents an interesting

opportunity for under-covered sports, includ-

ing women’s sports and para-sports, to grow

their audiences.

We know sports broadcasts stimulate audi-

ences’ emotions (e.g., Tamir & Lehman-Wilzig,

2022). However, understanding the sports

experience is “more complex than positive or

negative emotion” (Rogers, 2018, p. 380). In-

deed, sports entertain people, not only through

enjoyable experiences but also “meaningful”

ones:

There are plenty of fans who seem an-

noyed, irritated, or frustrated with their

teams. This might leave some wonder-

ing why would these fans watch the

game if it is so unpleasant. The answer

is that watching the games is not fun

but it is meaningful. Those fans are

deriving value from the sporting event

that does not represent pleasure but

represents a connection to others.

(Rogers, 2018, p. 379)

Of Wann’s eight motivations to watch sports,

broadcasters have a constant and direct in-

uence on only one (entertainment). Indeed,

though the quality of production can inuence

aesthetics, the primary denition of aesthetics

according to Wann (1995) revolves around the

3636

Divide and Conquer? A Model for Live OTT Sports Streaming.

beauty of the sport itself. Group aliation (in-

teracting with friends and/or fellow fans), family

(e.g. spending time with family), and economics

(betting on sports) are personal concepts and

decisions. Self-esteem (feeling good when one’s

team wins), eustress (a positive form of stress

a fan experiences during a game), and escape

(watching sports to forget about whatever

challenge may be happening in one’s life) are

individuals’ feelings, and though sports broad-

casters could inuence them in some cases, it

is unlikely all audience members’ feelings will

be impacted at once. Entertainment, though, is

directly aected by one’s production of sports

because technology, when used right, can help

people enjoy a sporting event more (Rogers et

al., 2017). For example, in the context of a live

sporting event, informative commentary and

graphics can increase an audience member’s

knowledge about the game and/or sport at

hand, and thus their feelings of independence

and competence to understand what they are

watching (Rogers, 2018). According to the uses

and gratications theory (U&G), in this scenario,

an audience member feels gratication thanks

to the eective use of technology.

3.2. USES AND

GRATIFICATIONS

While sports scholars have tried to identify

people’s motivations for consuming sports,

mass communication scholars have attempted

to uncover what motivates someone to con-

sume and/or use media, often through U&G,

which suggests media audiences are active in

gratifying their own needs and wishes (Katz et

al., 1974; Sundar & Limperos, 2013; Tang et

al., 2021). As Katz et al. (1974) explained, U&G

examines “(1) the social and psychological or-

igins of (2) needs, which generate (3) expecta-

tions of (4) the mass media or other sources,

which lead to (5) dierential patterns of media

exposure (or engagement in other activities),

resulting in (6) need gratications and (7) other

consequences” (p. 20). In other words, audienc-

es use media to fulll specic desires/needs.

Rubin (1983) identied ve reasons explaining

adults’ use of television: to pass time, for infor-

mation, for entertainment, for companionship,

and to escape.

The fast-changing 21st-century media land-

scape has created a renewal of U&G scholar-

ship (Lewis et al., 2017), in which audiences are

now “users” thanks to newer, interactive plat-

forms (Sundar & Limperos, 2013, p. 505), and

scholars have been more concerned with bet-

ter identifying what people do with media (Lin

et al., 2018; Spinda & Puckette, 2018; Tang et

al., 2021). Lewis et al. (2017) seem to have been

the rst to examine sports streaming users’ mo-

tivations. They interviewed 38 self-identied us-

ers of services mostly from U.S. major leagues,

such as NFL Game Rewind, NBA League Pass,

MLB.TV, and NHL Game Center. Their study

focused around people who are already estab-

lished sports fans who pay for specic online

streaming services, but streaming sports is not

reserved exclusively for those who pay for such

niche subscriptions. Hence the question at the

heart of this study: can streaming be used to

gratify people’s various needs when watching

sports?

We know enjoyment is the primary gratication

when watching TV or using the internet (Lew-

is et al., 2017; Logan, 2011) and that to enjoy

“sports media, an audience member must rst

have some degree of understanding of the

sport” (Rogers, 2018, p. 380). In other words,

3737

Roxane Coche, Benjamin J. Lynn, Matthew J. Haught

the audience of a sports broadcast cannot

have their needs gratied, if they do not know

the fundamentals of the sport on the screen. In

fact, during the Tokyo Olympics in 2021, Aus-

tralian scholar Dr. Adele Pavlidis summed it up

well in a tweet:

I love how the olympics is so inclusive

in that the commentators don’t always

assume watchers know much about

the sport so they are commentating

and explaining as they go. For me, as

someone with lots of interests besides

watching sport this makes the experi-

ence more exciting

Even though Pavlidis’ research focuses on

sports, she is not an expert in every sport, so

Olympic commentators are instrumental in her

understanding of sports she does not know

well. Thanks to this dierent style of commen-

tating, she is a more satised customer. It fol-

lows she is more likely to be a returning cus-

tomer and perhaps become a loyal consumer,

i.e. a fan (Fortunato, 2018). That understanding

a sport is needed to enjoy watching it is logical,

yet this crucial detail tends to get overlooked,

as people overestimate their capacity to under-

stand even the most popular sports (Lynn et al.,

2021).

3.3. STREAMING LIVE

SPORTING EVENTS

Despite the substantial increase in the produc-

tion of sports content, “live televised sports re-

main at the core of sports broadcasting across

the globe” (Tamir & Lehman-Wilzig, 2022, p. 3).

In fact, 94 of the top 100 telecasts in the U.S. in

2022 were live sports (Karp, 2023). In France,

seven of the top 10 were (Grosskopf, 2022),

and in Spain, only football appears in the top

5 of the most watched telecasts in 2022 (Pal-

co23, 2023). These telecasts were also availa-

ble over the top (OTT) as OTT infrastructures

have become “a major spectating channel for

sports fans” (Feng et al., 2020, p. 1), disrupting

the sports media industry (Bowman, n.d.).

Moreover, the element of liveness has been a

signicant concept in media studies, particular-

ly television studies for almost a century (Ilan,

2021). In today’s media environment, digital

outlets oer live news coverage, including in

sports (Ilan, 2021). Social networks, such as

Facebook and Twitter, were the rst to go after

live streaming of sporting events in the mid-

2010s, but they have since “cooled their inter-

est in becoming sports broadcasters” (Joseph,

2019). However, they still oer OTT sports

content. Facebook seemingly opted to focus

on a pay-per-view model instead of competing

directly with traditional sportscasters (Young,

2021). In essence, as an anonymous sports

executive told Joseph (2019), Facebook wants

“the content around the main event on their

platform, not the event itself.” The famed social

network’s change of strategy has not stopped

Amazon or Apple from getting involved with

the streaming of live sporting events worldwide

(e.g., Kayali et al., 2021; Porter, 2021). Netix

also recently expressed interest in streaming

live sports, though reversed course after the

company lost subscribers and market value in

early 2022 (Gentrup, 2022).

In parallel, sports organizations (leagues,

teams, federations, etc.) started creating OTT

content, essentially cutting out the middleman

to reach their fans (Feng et al., 2020; Wymer

et al., 2021). An early exploratory study about

audiences’ experience with live streaming of

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Divide and Conquer? A Model for Live OTT Sports Streaming.

sports suggests the new medium provides “a

completely dierent spectating environment

for sports fans” (Feng et al., 2020, p. 14). Thus,

those who live stream sports should take ad-

vantage of the current times to implement new

models, especially because people, including

those in the sports broadcast industry, don’t

like change (Coche & Lynn, 2020). This attitude

is why the present study proposes OTT produc-

ers pursue a new model for live sporting events

by oering dierent packages for dierent tar-

get audiences.

3.4. SUMMARY AND PURPOSE

People need to understand a sport to have the

potential to grow from âneur to supporter.

This study proposes to oer audiences three

streaming alternatives based on fandom lev-

el. The video stream targeted toward âneurs

would include more explanations to give view-

ers a chance to understand the game better.

In essence, it would be a beginner’s guide in

the form of a live competition. On the other

end of the spectrum, the stream targeted to-

ward fans or spectators (both of whom know

more about their team and the sport) would

use more jargon and provide in-depth analysis,

skipping basic explanations; akin to an experts’

playbook. Finally, a third stream, similar to cur-

rent traditional broadcasts, would serve as a

bridge between the other two. Such a model

would give OTT producers a chance to meet

their audience where they are at, thus creating

a matching framework benecial for all. Hence,

this research tests whether oering multiple

live sports streams with dierent packaging

styles (e.g., commentary, graphics, etc.) chang-

es people’s intention to watch a sporting event.

Companies involved in the live streaming of

sports must adapt the traditional (television)

product to the online platform to provide the

best experience to their viewers, and perhaps

even expand their audience, especially as view-

ers increasingly cancel cable subscriptions

to turn to online options (Haught, 2022). The

model proposed in the study also oers an in-

teresting opportunity for under-covered sports,

including women’s sports and para-sports, as

they attempt to grow their audiences.

4. METHOD

An online, self-administered questionnaire

was created using Qualtrics and distributed to

adults based in the United States (U.S.) using

Amazon Mechanical Turk (MTurk), which can

provide a moderately representative sample

of the U.S. population (Loepp & Kelly, 2020).

Though results cannot be generalized, “MTurk

is an ecient, reliable, cost-eective tool”

(Mortensen & Hughes, 2018, p. 537) that allows

researchers to improve sample quality over

the traditional college student pools (Loepp &

Kelly, 2020). The survey was pretested with 10

MTurkers before being launched. Each partici-

pant received $1.50 for completing the survey.

4.1. PARTICIPANTS

A total of 429 U.S.-based MTurkers clicked on

the survey, but 114 of them failed one of the

basic attention check questions. Of the 315 re-

maining participants, all completed the survey,

but a visual check revealed two who seemed to

have “atlined” their responses to nish quickly,

so 313 responses were included. Though sam-

ple size calculations (Zhou & Sloan, 2011) using

3939

Roxane Coche, Benjamin J. Lynn, Matthew J. Haught

the U.S. population as the survey’s population

reveal 385 respondents are required to meet

a 95% condence level with a 5% margin of er-

ror, 313 participants allows us to make conclu-

sions with a 95% condence level and a margin

of error of 5.6%. As such, this sample still pro-

vides an interesting foundation as an explora-

tory case study for people’s potential interest in

multi-tiered sports streaming.

4.1.1. DEMOGRAPHICS

Participants came from 40 of the 50 Amer-

ican states. Their age ranged from 18 to 71

(M=35.27, SD=9.41), and the majority was male

(n=186, 59%; female n=122, 39%; non-binary

n=1; prefer not to say n=4, 1%). The sample

was overall more educated than the U.S. popu-

lation with 62% of participants with a bachelor’s

degree (n=194) and another 21% with a grad-

uate degree (n=66). Yet, 47% of participants

(n=148) lived in households making $59,999

or less every year, thus under the U.S. median

household income of $68,703 (Semega et al.,

2020). Another 19% (n=60) were in households

earning between $60,000 and $74,999, and

about a third (n=105, 34%) lived in households

earning $75,000 or more annually. Based on

the median, the participants’ annual household

income is somewhat representative of the U.S.

population. Finally, most participants consid-

ered themselves Caucasian or white (n=240,

76%). An additional 15% identied as Black or

African-American (n=46), 4% as Hispanic or

Latine (n=11), 3% as Asian or Pacic Islander

(n=8), and 2% as Native American or Alaskan

Native (n=6). The last two participants identied

as multiracial or preferred not to disclose their

race. Thus, compared to the U.S. Census, Cau-

casians were overrepresented at the expense

of the Latine and Asian populations.

4.1.2. SPORTS HABITS

Though the survey was open to any U.S. adult,

most participants reported watching live sports

throughout the year. Indeed, only ve (2%)

reported never watching live sports, while 46

(15%) said they watched live sports one to ten

times a year, 64 (20%) once or twice a month, 79

(25%) once a week, 75 (24%) two to three times

a week, and 44 (14%) more than three times

a week. Of the 308 participants who watch live

sports (regardless of frequency), about half

(n=157, 51%) prefer to do so on television while

42% (n=130) prefer to stream them online, and

7% (n=21) have no preference. No sex-based

dierences existed in these habits.

Unsurprisingly, the sample was also skewed

based on sports fandom: on a scale of 1 (“I am

not a sport, not a sports fan”) to 7 (“I am a fan of

at least one sport”), respondents averaged 5.84

with no sex-based dierence (male M=5.90,

SD=1.14, female M=5.78, SD=1.15). Asked

about 10 sports (the ve most popular sports

in the country along with ve less popular

Olympic team sports), participants were more

likely to be fans of football, basketball, baseball,

soccer, and ice hockey (in that order) than vol-

leyball, team handball, eld hockey, curling, and

rugby (in that order). No sex-based dierences

existed in participants’ likelihood to be a fan of

a given sport.

4.2. MEASURES

After screening questions, the survey includ-

ed three sections. First, participants answered

questions about their sports consumption

habits, their fandom of ten sports (listed in the

paragraph above), and statements about their

4040

Divide and Conquer? A Model for Live OTT Sports Streaming.

motivations to watch live sports, adapted from

Wann’s SFMS, on a seven-point Likert scale.

The second section started with a description

of the proposed changes to traditional sports

broadcasting (tailoring the product to people

based on their level of fandom) before respond-

ents rated four statements on a seven-point

Likert scale (from strongly disagree to strongly

agree): (1) If a company starts oering dierent

streams based on knowledge/fandom level,

I will start watching sports I do not know well;

(2) A company oering dierent streams based

on fandom level would enhance my experience

watching sports; (3) If a company starts oering

dierent streams based on fandom level, I will

watch my favorite sports more often than I cur-

rently do; and (4) If a company starts oering

dierent streams based on fandom level, I am

more likely to become a fan of a sport I mere-

ly follow from a distance. Then, for each of the

ten team sports, respondents selected one of

three options they would rather watch: (1) An

introductory broadcast in which the announc-

ers carefully explain the rules of the sport as

I watch the gameplay; (2) A traditional broad-

cast like what I’m used to seeing with announc-

ers who focus mostly on the gameplay and

sometimes explain the rules; or (3) An in-depth

broadcast in which the announcers discuss in

extreme detail the strategies the players/teams

use. The announcers do not explain the basic

rules of the sport unless it is relevant to the

gameplay.

Finally, section 3 focused on demographics. All

three sections included quantitative questions

with variables mostly at the nominal or ordinal

levels, which allows for investigation into the

specic idea of tailoring live sports to the audi-

ence based on their level of fandom.

5. RESULTS

The present study sought to determine if pack-

aging live sports dierently based on people’s

various levels of fandom would change their

intention to watch a sporting event. To answer

this central research question, the present

study used a combination of factor analysis,

ANOVA, and regression.

To begin, nine measures of motivations for

watching sports were classied into two fac-

tors. Measures were rated on a seven-point

scale. Using a Varimax rotation with Kaiser nor-

malization, a factor rotation converged in three

iterations (Table 1). The rst factor had an ei-

genvalue of 3.95 and explained 43.91% of the

variance. It contained motivations of escape

(M=5.12, SD=1.44), nance (M=4.62, SD=2.03),

beauty (M=5.49, SD=1.26), friends (M=4.99,

SD=1.63), self-esteem (M=4.72, SD=1.92), and

family (M=5.25, SD=1.64); as this factor repre-

sented components of sports media consump-

tion associated with one’s identity, the factor

was named Identity (M=.72, SD=.18, α=.85). The

second factor had an eigenvalue of 1.55 and

explained 17.23% of the variance. It contained

three measures of Getting pumped (M=5.54,

SD=1.33), having a good time (M=5.76, SD=1.18),

and entertainment (M=5.83, SD=1.11); as this

factor represented components of sport me-

dia consumption associated with entertain-

ment, the factor was named Enjoyment (M=.82,

SD=.14, α=.70). Both factors were used as moti-

vators for consumption.

4141

Roxane Coche, Benjamin J. Lynn, Matthew J. Haught

FACTOR 1: Identity

Escape .61 .36

Finance .85 -.01

Beauty .46 .44

Friends .77 .17

Self-Esteem .90 .03

Family .70 .32

FACTOR 2: Enjoyment

Get Pumped .28 .72

Good Time .07 .80

Entertainment .04 .78

Table 1

Factor analysis of motivations for watching sports

Note. N = 313. The extraction method was principal

axis factoring with a Varimax with Kaiser Normalization

rotation in three iterations. Factor loadings are in bold.

Respondents were asked if, when watching

one of the 10 sports identied for consump-

tion, they would prefer an introductory broad-

cast, a traditional broadcast, or an in-depth

broadcast. These preferences were analyzed

for relationships to the motivators of Identity

and Enjoyment using a series of ANOVA tests.

Across the 10 sports, signicant preferences

were found in four. Identity-driven fans of soc-

cer [F(2, 310)=5.09, p=0.007], basketball [F(2,

310)=16.75, p<0.001], football [F(2, 310)=12.81,

p<0.001], and baseball [F(2, 310)=8.08, p<0.001]

signicantly preferred the more detailed, intro-

ductory broadcast. Meanwhile, Enjoyment-driv-

en fans of volleyball signicantly preferred

the traditional broadcast style [F(2, 310)=3.15,

p=0.044].

Finally, a regression analysis measured the de-

sire to stream sports more often. Four meas-

ures on a seven-point scale asked about watch-

ing sports. The items were 1. If a company starts

oering dierent streams based on knowledge/

fandom level, I will start watching sports I do not

know well (M=4.91, SD=1.56); 2. A company of-

fering dierent streams based on fandom level

would enhance my experience watching sports

(M=5.24, SD=1.43); 3. If a company starts oer-

ing dierent streams based on fandom level, I

will watch my favorite sports more often than I

currently do (M=5.18, SD=1.55); and 4. If a com-

pany starts oering dierent streams based

on fandom level, I am more likely to become a

fan of a sport I merely follow from a distance

(M=5.12, SD=1.58). These items were summat-

ed into a measure of watching more sports

(M=.71, SD=.19, α=.87).

The regression analysis (Table 2) indicated

three predictors explained 61% of the variance

of the desire to watch more sports with dier-

entiated broadcasts (R

=.61, F(1, 307)=159.80,

p<.001). Specically, Enjoyment (β=.08, p=.035),

Identity (β=.48, p<.001), and the intensity of

one’s sports fandom (β=.27, p<.001) were the

signicant predictors. Ultimately, this nding

indicates people who derive sources of their

identity from sports are most likely to consume

more sports with the enhanced broadcasts,

with people who watch sports for enjoyment,

and people who just watch a lot of sports, also

consuming more.

4242

Divide and Conquer? A Model for Live OTT Sports Streaming.

Variables B SE B b t p

Enjoyment .113 .053 .083 2.12 .035

Identity .487 .069 .475 7.04 <.001

Sports

Fandom

.199 .050 .265 3.98 <.001

Table 2

Beta weights for regression analysis

6. DISCUSSION AND

CONCLUSION

The present study is limited in a few ways. The

use of MTurk as a sampling tool provides a via-

ble, but sometimes slightly skewed, perception

of the general population. Also, sports fans

self-identied their viewing habits, but self-per-

ceptions are often underreported. Further-

more, the study did not dierentiate between

consumption of men’s or women’s sports,

which could be a fruitful avenue for future re-

search as the audience for women’s sports is

growing and changing. Finally, all participants

were adults based in the U.S., so similar explor-

atory research in other markets would be ben-

ecial. Yet, as online companies and sports or-

ganizations increasingly broadcast live sports,

this study contributes to the industry and aca-

demia by exploring viewer preferences for live

sports within the framework of U&G. As an ex-

planatory analysis conducted within the Ameri-

can market, it explores a new way to broadcast

sports to improve audiences’ experience. A

multi-tiered streaming system embraces the

power of digital streaming more fully while

keeping costs lower than what a fully custom-

ized audience experience would require.

Hence, this study still provides valuable insight

for both scholars and industry professionals.

Leading sports communication scholars re-

cently encouraged researchers to conduct

more practical research (ICA, 2020), and this

study responds to this call. Specically, Toni

Bruce said in that panel that an obstacle to

sports communication research is “our failure

to engage directly with those who actually pro-

duce the content that we often spend most

of our time critiquing” (ICA, 2020). This study

directly addresses a major concern of practi-

tioners by providing a potential solution to re-

curring problems scholars have pointed out for

decades, like the aging of the sports audience

(Wakeeld & Bennett, 2018), or the media’s lack

of coverage of women’s sports (e.g., Coche,

2022; Cooky et al., 2021) and para-sports (Wat-

son, 2020). It also contributes to Ilan’s (2021)

call for more research into the signicance of

live television at a time when live sports need a

new model to deliver more value to consumers

(Hall, 2021).

6.1. THEORETICAL

CONTRIBUTIONS

This study oers empirical evidence that one’s

level of sports fandom may increase if broad-

casters implemented a feasible multi-tiered

model of streaming sports based on three fan-

dom levels. This is in line with Rogers’ (2018)

nding that having a basic understanding of a

sport is crucial to enjoying it in the media. In

other words, the current research shows more

spectators’ needs can be gratied if a viable

pathway from uninitiated viewer to full sports

fan were to exist. This also means that a mul-

4343

Roxane Coche, Benjamin J. Lynn, Matthew J. Haught

ti-tiered streaming model may be a viable solu-

tion to resolving some of the “persistent ineq-

uities” that exist in sports media (e.g., women’s

sports and para-sports are rarely covered), an

industry that tends to “actively builds audienc-

es [only] for certain men’s sports” (Cooky et al.,

2021, p. 351). Indeed, an introductory broad-

cast would allow audience members to get

to know a sport and its athletes, which would

make it more likely for them to become fans.

Furthermore, all types of fans preferred the in-

troductory broadcast style providing more de-

tail about the rules of the sport watched, which

was initially thought to be for âneurs, as de-

ned by Giulianotti (2015). Notably, fans of four

of the top ve U.S. sports (football, basketball,

baseball, and soccer) indicated preferring an in-

troductory broadcast with more basic informa-

tion about leagues, players, and rules. Although

this might seem counterintuitive, the authors

deduce three possible explanations: (1) the in-

troductory broadcast is a way to better inform

fans about the intricacies of individual players,

which can be a manifestation of the rise in fan-

tasy sports and sports betting (Kupfer & Ander-

son, 2021), (2) one’s capacity to comprehend a

sports broadcast may be overestimated, con-

rming Lynn et al.’s (2021) conclusion, and/or

(3) audiences may want to connect with others

through sports (Kim & Kim, 2020; Tamir & Le-

hman-Wilzig, 2022): introductory broadcasts

would make communal viewing an accessible

social activity, inclusive of âneurs, followers,

fans and supporters alike.

Though all types of fans were attracted to a

more introductory broadcast, this study’s re-

sults also indicate sports consumers have a

high willingness to consume more sports tel-

evision content. They saw the dierentiated

broadcasts as an added bonus. Though this

model relies on one-way communication dur-

ing the broadcast, it still gives the audience

more control over their media consumption

as they must make a conscious choice among

three options. Hence, audience members are

more active and, according to previous U&G

research, more likely to feel gratied (Lewis et

al., 2017; Lin et al., 2018; Sundar & Limperos,

2013).

6.2. PRACTICAL

IMPLICATIONS

Sports and media professionals can use these

results to create a more educative process to

attract more fans as they attempt to rejuvenate

their aging audiences (Notte, 2017). Indeed, in-

cluding pedagogical tools within sports broad-

casts would give audiences a chance at better

understanding what they are watching, which

will allow for more enjoyment (Cummins, 2009;

Rogers, 2018), hence higher gratication (Katz

et al., 1974; Lewis et al., 2017; Logan, 2011; Ru-

bin, 1984; Tang et al., 2021). Advancing, cost-ef-

fective technologies in on-screen graphics

might be one solution that could be turned on

and o, like closed captioning. Providing such

elements would make the broadcast more

accessible and thus, following Rogers (2018),

4444

Divide and Conquer? A Model for Live OTT Sports Streaming.

more likely to be enjoyed. For instance, football

viewers, unlike in-stadium spectators, can often

see added graphics that help them understand

why a referee called an oside.

Moreover, this study’s results imply sports audi-

ences continue to want more content. Because

mainstream sports remain a major factor for

televised sporting events (Lynn et al., 2021) and

as OTT television and sports streaming contin-

ue to grow (e.g., Wymer et al., 2021), broadcast-

ers and sports professionals should leverage

the multimedia nature of live streaming. Study-

ing the Queensland Maroons’ live streaming on

Facebook, Wymer et al. (2021) concluded the

Australian rugby team did not capitalize on the

service’s capabilities to “engage through shar-

ing, socializing, codeveloping, and learning” (p.

88). The current study suggests broadcasters

have been committing a similar mistake by

treating the live streaming of sport as an ad-

ditional screen or channel rather than an en-

tirely new platform with its own opportunities.

In non-live streaming content, Netix has been

testing ways to make shows and movies more

interactive with “branching technology” (Nee,

2021, p. 1489) that allows viewers to choose

their own adventure. However, the process

is “expensive [...] dicult and challenging” (p.

1489) as it requires writers to write more sto-

ries, and crews to shoot more scenes, both

of which take time and nancial resources. In

contrast, the proposed model for live sports

does not require any more time, and the addi-

tional nancial resources required are limited

to a few crew members (mainly commentators,

graphics, audio) as many positions would be

used for all three streams (e.g., camera oper-

ators, replay, sideline reporter, etc.). Moreover,

a few tweaks and explainers could bring fans

closer to the game by giving them richer knowl-

edge about the gaming experience happening

on their second screens, via fantasy or betting,

which have a “reciprocal relationship” with the

media industry, particularly television (Kup-

fer & Anderson, 2021). A multi-tiered stream-

ing model could thus deeply aect these two

growing industries (Kupfer & Anderson, 2021).

Future research should explore how a mul-

ti-tiered model works in practice.

Ultimately, the time is now for the expansion of

sports viewing options. The addition of tiered

broadcasts would allow for more voices to be

heard in the game, and provide education to

novice sports fans and seasoned fans alike. Par-

ents and grandparents could share in watching

elementary broadcasts with their children and

grandchildren, furthering family traditions of

sports watching while all learn more about the

game.

4545

Roxane Coche, Benjamin J. Lynn, Matthew J. Haught

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Divide and Conquer? A Model for Live OTT Sports Streaming.

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Universidad del Azuay