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European Sport Management QuarterlyPublication details, including instructions for authors and subscription information:http://www.informaworld.com/smpp/title~content=t716100711

The Demand for Televised FootballHallvard Johnsen a; Mona Solvoll aa The Norwegian School of Management - BI,

Online Publication Date: 01 December 2007

To cite this Article Johnsen, Hallvard and Solvoll, Mona(2007)'The Demand for Televised Football',European Sport ManagementQuarterly,7:4,311 335

To link to this Article: DOI: 10.1080/16184740701717048URL: http://dx.doi.org/10.1080/16184740701717048

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ARTICLE

The Demand for Televised Football

HALLVARD JOHNSEN & MONA SOLVOLL

The Norwegian School of ManagementBI

ABSTRACT This paper investigates the demand for televised football games. Itexamines how factors specific to television on the one hand and factors specific tothe football game on the other hand, influence the viewing figures of televised football.In our case we are analysing viewing figures for football matches from the Norwegiantop division shown on the Norwegian public service channels NRK1 (financed bylicence fee) and TV2 (financed by advertising) in the period 19982007, and viewingfigures for football matches from the Danish top league on the Danish commercialcable and satellite channel 3' in the same period. The purpose of the analysis is toidentity (a) the motivation of different segments of viewers to watch televised football;and (b) potential scheduling practices of different television companies based on factorsthat influences viewing preferences. Findings suggest that the viewer ratings of televisedfootball are dependent on factors related to scheduling than by football interests among

the audience. Ultimately, the study supports the theory of audience segmentation forpublic service broadcasters and commercial channels. Most viewers on public servicebroadcasters watch programs, also football games, driven by general viewing habitsand scheduling strategies, while the smaller audience on a commercial channel is morelikely to select programs based on presumed interests for the game.

Introduction

Although football has always been regarded as a good form of entertain-ment, both on television and live, nobody can guarantee the quality of a

game due to the uncertainty of both outcome and of quality of performance.While traditionally spectators tend to have accepted the variation of qualityin live matches, the television industry constantly attempts to reduce theuncertainty in entertainment value that follows the nature of sport. This isarguably true for traditional public service broadcasters as their main groupof audience is largely not particularly interested in football, except that thegame should be interesting and entertaining. At the opposite end, themajority of the audience with pay-per-view channels are dedicated football

Correspondence Address: The Norwegian School of Management

BI, Nydalsveien 37, N-0484 Oslo,Norway. Email: [email protected]

ISSN 1618-4742 Print/ISSN 1746-031X Online # 2007 European Association for Sport ManagementDOI: 10.1080/16184740701717048

European Sport Management Quarterly,

Vol. 7, No. 4, 311335, December 2007


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fans whose interest in the game is less dependent on outcome uncertaintyand quality of performance.

The reduction of uncertainty in entertainment value and a successfuldelivery of a televised football match are depended on at least three aspects:factors specific to the sport itself, factors related to a specific broadcastersscheduling practices and factors related to the quality of the televisioncoverage. The production of televised football will not receive any attentionin this paper, although we agree with Whannel (1992) that television canadd entertainment value to a game by, for instance, judicious highlights,action replays, interviews, the use of multiple cameras and good commen-tary. In this paper we address the two former aspects by employing viewerfigures as a proxy for the demand for televised football. First, we ask whatfootball specific factors drive viewing interest for football on different typesof channels. Second, we are investigating how different scheduling strategiesmay affect the viewing figures and how these scheduling strategies may differ

between public service broadcasters and commercial cable channels.The rest of the paper is organized in four main sections. We first introduce

our double case study and relate it to different models of broadcasting.Secondly, we introduce studies on scheduling and how audience interestsmay vary according to the type of broadcaster. We also consider existingliterature on factors influencing the attendance figures for spectator sportwhich also can be applied for viewing figures. In the third section we outlinethe methodology of the case studies and present the integrated results of theanalysis. The paper concludes with a discussion of the theoretical andempirical contributions of the study.

The Case Studies

By looking at viewing figures for football matches transmitted on a state-owned public service channel (the Norwegian NRK 1), a commercial publicservice channel (the Norwegian TV2) and a commercial cable company (theScandinavian 3' in Denmark), the main point in this paper is that thedegree of football interest does not single-handedly explain the demand fortelevised football. We intend also to show that the type of television channelinfluences and reflects the demand for television sport because these

channels have different audience segments. In our analysis we onlyinvestigate public service broadcaster versus commercial cable channels.However, for arguments sake, we include one other type of channel in ourtheoretical claim, the pay-per-view model.

While sport, particularly football, has been a favourable content forbroadcasters since the early 1960s, profound changes in the broadcastingindustry (such as deregulation, digitalization, globalization, etc) have guidedthe emergence of a number of different broadcasters which all struggle forthe rights to broadcast sport. The degree of viewers motivation for watchingfootball varies from very interested to not interested in football. The twomain groups of audiences form the foundations of different types oftelevision channels, as these have widely different objectives. A pay

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television channel wants to maximize its number of subscribers, while acommercial free-to-air channel wants to maximize its number of viewers incertain segments in order to maximize advertising revenue. A public servicebroadcaster wants to maximize its numbers of viewers subject to satisfyingits licence criteria, which regulate the content of the channel.

Public Service Broadcasters

Today, most European viewers have a wide range of channels available tothem. In most European countries there is a state run public servicebroadcaster financed by a licence fee. These broadcasters, such as NRK 1in our case, have generally large viewing audiences made up by severaldifferent segments of the population. We can therefore expect higherviewing figures for a football game shown on a public service channelsuch as NRK 1. However, as all the audience segments are present in the

universe of a public service broadcaster, the less interested audience segmentis usually in a majority. This makes the channels able to apply a mixedstrategy in content and scheduling.

The public service broadcasting landscape is completed by one or severalcommercial enterprises financed by advertising. These often have a mono-poly on national coverage, but also have to meet certain requirementsconcerning programme choice. ITV1 in Britain, Danish TV2, NorwegianTV2 and Swedish TV4 are all examples of these types of channels. Often,these channels have identical viewing shares with the state broadcastersmain channel, varying slightly between countries (Barkho, 2005). From

1996 to 2006, NRK 1s market share has varied from 43% to 36%, whileTV2s market share has been between 29% and 32%.

Commercial public service broadcasters, such as TV2, have many of thesame advantages as state-owned public service broadcasters in terms ofpenetration and a mixed scheduling strategy, hence also the attraction oflarge audiences. Such channels often find national football an idealprogramme as it often attract larger audiences, while at the same timebeing domestically produced and fitting with the channels desire to be partof a countrys social fabric. In a survey conducted by UPC/Cablecom for2006 in 13 European countries (although neither in Denmark nor Norway),

26% of consumers preferred a national public service channel while 4%preferred national commercial channels. Of foreign channels, 20% preferreda public service channel while 16 preferred a foreign commercial channel.However, 34% did not have any preference to which channel they preferred.Yet, one might argue that commercial public service broadcasters sufferalong the quality dimension, as commercial breaks tend to annoy the viewersand disturb the television experience.

Commercial Cable Channel

Channels transmitted by cable or satellite have lower viewer penetrationthan public service broadcasters, rarely reaching more than 60% or 70% of

The Demand for Televised Football 313


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the households in a market. For example, the Scandinavian televisionchannel TV3 (Viasat), reaches 62% of households in Norway, 66% inDenmark and 73% in Sweden (Nordicom 2006). The channel in our study,TV3', reaches 64% of the Danish population (TNSGallup.dk). The actualviewer share is generally much lower than for public service channels, about6%12% for TV3 weekly in the different Scandinavian countries (Barkho2005). However, in a given week in Denmark, Week 15 2007, 38% hadwatched a programme on any of commercial broadcaster Viasats three free-to-air cable and satellite channels, while 21% had watched a programme onTV3'. In the same week, 79% of the population had watched a programmeon the commercial public service broadcaster TV2 while 78% had watched aprogramme on the state run public service broadcaster DR1 (TNSGal-lup.dk). When football is shown on a small commercial channel, the numberof casual viewers is much lower than if a game is shown on a public servicechannel, but higher than if a game is shown on a pay channel. The viewers

who tune in to watch on such a channel are more genuinely interested onfootball and cannot be described as causal viewers.

Pay and Pay-Per-View Channels

Viewers can only watch pay-TV games by buying a subscription package. Itis not possible to buy these games individually from the pay-TV channel,thus it is a form of single bundling (Varian, 1993). Usually, the viewer has tocommit himself to buy the package for a minimum of 12 months or more.Only the very dedicated viewer is willing to pay such amounts in order to

watch football on television. A marginal supporter of a specific club, i.e., asupporter whose interest is not strong enough to outweigh the cost of a pay-TV subscription, is very unlikely to buy a pay-TV subscription package.Arrangements such as pay-per-view or subscription channel have meantbetter opportunities for adapting to individual preferences such as a highinterest for particular football matches or teams. Important indicators forhaving a favourite channel might also be the quality of the production, thesport presenter or the amount of live sport.

Media Theory Approach: User-centred and media-centred perspectives

The commonly used explanation for the high viewing rating of televisedfootball is the popularity of the sport itself. In essence, this explanationcorrelates with the user-centred perspective that emerged in media studies inthe early 1970s which assumed that the viewers are goal-oriented andattempt to achieve their goals through rational media use (Katz et al., 1974).Based on this perspective, one could argue that viewers have actively anddeliberately chosen to watch football in order to satisfy some psychologicaland/or social expectations related to football specific factors. The perspec-tive suggests that engaged audiences relate to television content in aninstrumental way.



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According to Ang (1991) one major criticism of the uses and gratifica-tion perspective is its view that the media is functional to people and maythus implicitly offer a justification for the way the media is currentlyorganized. The amount of football coverage on television, the rise of paysports channels and the broadcasters expensive competition for footballrights are merely related to football-specific needs and interests in theaudience. The critical argument of Ang (1991) suggests that an additionalmedia-centred perspective should expand the user-centred model. Viewingrating is not only driven by the audiences instrumental use of mediacontent as the audiences motivation for watching television is also based onrituals and habits. The media-centred perspective relates television to theaudience by suggesting that television helps shape individuals motivationsand needs for watching programs, and therefore their media use becomestheir ritual. Rubin and Windahl (1986) have proposed a synthesis of theuser-centred and the media-centred perspectives in their uses and depen-

dency model. A user-centred perspective suggests that the viewers choose,in a rational and instrumental way, to watch a specific program inaccordance with their preferences. The media-centred perspective, on theother hand, suggests that the viewers choice is less based on rationaldecisions but rather on habits. In regard to the football viewers, we suggestthat an instrumental and rational television use is contingent on theaudiences strong interest for the game, while a habitual media use ismore dependent on the television specific factors.

Drawing on Merkel (1994) for segments of the football audience and theuses and dependency model of Rubin and Windahl (1986), at least three

groups of audience emerge depending on their interest for football: Fanshave high football attention and usually support one club strongly.However, their strong interest in one club also creates an interest in theresult of competing clubs. As television viewers, fans are regarded as activeand involved viewers that select their programs and channels in a rationaland purposive way. Fans have a relatively inelastic vertical demand bothwith respect to quality (results) and disutility (price and other factors) andare the segment with the highest willingness-to-pay (or purchase as therelationship between price and demand has proved ambiguous for football).Fans are the target group both for pay-per-view transmission as well as

regular pay television subscriptions.The supporter segments demand for football is more elastic with respectto quality and disutility than the fan segment, and its willingness to pay forthe product is thus lower than for the fan segment. These viewers aremoderately interested in football, and their viewing patterns may consist of amix of rational choices and habits. They tend to support one specific club,but with less intensity than the fan and their interest is thus likely to be moredependent on results. They may not be willing to wait for the match to betransmitted delayed, but they may accept a certain disruption of the qualityin terms of commercial breaks. Of these two effects, the quality dependentdemand is more thoroughly in evidence than the different aspects of ourdisutility factors. Given the quality dependent demand, supporters are less



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likely to subscribe to pay television channels. Instead, they are easier to reachthrough free-to-air channels.

In the same manner, games on free-to-air television make it possible forthe third segment, the consumers to watch the game. These viewers are lessinterested in football, but will watch TV in a ritualistic and occasionally waywhich requires passive and non-selective participation. However, it ispossible that this segments interest for football is so sensitive that it ismost efficiently reached when games are shown on public service broad-casters. We assume that most viewers belong to the last category, while thesegment of fans forms the smallest category.

The ability to attract large audiences coincides with football clubs desireto reach as large an audience as possible with at least some of their games inorder to appear attractive to sponsors as well as increase press coverage.When a game is shown on a public service channel, the game will be watchedby all three segments discussed above: fans, supporters and consumers. The

consumer segment will always be the biggest one for any type of program ona public service broadcasting channel. The implication is that it is thepreferences of the least interested consumers that will be of main interest tothe public service broadcaster. When commercial cable channels show afootball match, the viewers are to large extent active football fans andsupporters. Thus, these games are watched by a segment with a pre-definedinterest for football, although the reach is greater than in the case of paytelevision.

Scheduling Practices as Television Specific Factors

In addition to different audience segmentations, we assume that differenttypes of broadcasters, such as public service broadcasters, commercial cablecompanies and pay-per-view channels, apply different sets of schedulingstrategies in order to draw and hold its audiences. The increased competitionbetween broadcasters and the stronger influence from the advertisingindustry have made broadcasting companies aware of the strategicadvantages scheduling may provide. As argued by John Ellis (2000), theschedule is the locus of power in television, the mechanism wherebydemographic speculations are turned into a viewing experience (p. 26).

Scheduling has hardly been studied academically and until recently beentaken for granted by those working in television itself (Ellis, 2000).However, the use of scheduling practices has expanded, also among publicservice broadcasters (Coppens & Saeys, 2006; Ellis, 2000; Hujanen, 2002;Ytreberg, 2002). Major sporting events have gone from manifested mediaevents (Dayan & Katz, 1992) or traditional slots to everyday activities intwo manners. Firstly, they do not interrupt the normal flow of broadcastingand our lives in the same monopolistic way as a few years ago. Secondly, theamount of sport on television has increased to a level where televised sport ismore of a routine watch and less like an event.

Today, most scholars approach scheduling as an instrumental, rationalscience based on audience research in order to reduce uncertainty in



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audience orientation. Information about demographic groups forms a basisthat guides the scheduling practices. A schedule contains inscribed assump-tions about everyday life, the annual pattern of seasons and events,traditional habitual slots and assumptions about what the competitorsmight do (Ellis, 2000). In this paper we wish to focus on how channelsconstruct a schedule based on grids related to the season of the year, the dayof week and the time of day. The aspects of competition from otherchannels programs and uncertainty due to demands on leisure time ingeneral and from other media will not be addressed.

In a schedule there are at least three different levels. Firstly there is theregular season schedule in which the summer season traditionally hasgenerated fewer viewers. Longer football seasons, however, may provideopportunities to generate the revenues that clubs and sponsors seem todemand and to help the broadcasters in filling slots as the regular TV seasonwinds down in the summer. Then there is the scheduling of the week and

day. When football on television was a media event, the game usually startedat the same time every week although the actual kick-off time differedbetween countries (usually Saturdays at 4 pm). Today, as an ongoing flow ofcontent, games are transmitted on any day in the week, from late noon tolate evening. If a broadcaster can gather the same share and type of audienceregardless of the day of the week and the time of day, this would enhance theflexibility of the schedule and strategic advantages for the broadcaster.

Seasonal Factors

The first factor that influences viewing figures is the seasons of the year. Thetable below shows average viewing hours in eight different weeks in differentparts of the year in Norway and Denmark from July 2006 to April 2007(TNSGallup Norway/Denmark, 2007).

In both countries there are indications that the amount of televisionviewing fluctuates with the seasons. The winter is the best period fortelevision channels followed by autumn and spring. The summer isinvariably a poor time for television channels with fewer viewers than the

Table 1. Weekly average viewing hours (DK and N)

Norway Denmark

Week Hours Minutes Hours Minutes

28 12 1 13 3529 10 58 14 842 18 26 18 2043 18 26 17 475 20 32 19 186 21 35 18 2413 15 38 15 43

14 15 17 17 2



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rest of the year. This is equally true for both public service broadcasters andprivate commercial channels. The general experience is moreover thatautumn has a stronger potential for reaching better ratings than spring, asmany sit-coms, drama series and so forth start their new seasons of showsat the beginning of the autumn.

As the viewers on a public service channels are more habitual and lessselective, we may assume that viewing figures on a public service channelfollow the weekly and annual viewing cycle more closely than on a smallerchannel. Hence, our assumption is that public service channels can offermuch higher ratings than other channels but that the scheduling of theprogramme has to be handled more delicately in respect to the yearlyviewing habits. A narrow channel, on the other hand, can offer greaterflexibility with regard to viewing times as its segment is more limited tofootball fans. These are less likely to be casual viewers, but rather rationalviewers who select what to watch based on high motivation and involve-

ment.

Viewing Day

As in the case of seasonal variation, there are differences in televisionviewing depending on the weekday. Weekends are better than weekdays,when people often are occupied with other activities. In 2006, the averagedaily viewing time during the week (from Monday to Thursday), was 134minutes in Norway. On Fridays they spent 153 minutes in front of thetelevision, while on Saturday and Sundays they spent 164 and 179 minutes

on television (SSB, 2006). This pattern has been reasonably stable since theearly 1990s except that Sunday has overtaken Saturday as the most popularTV day.

The question, then, is: To what extent do different types of channelsviewing figures respond to differences in viewing day? The generalassumption is that the broader the audience the more sensitive the channelis to type of day. A football game shown on a public service broadcaster asbroader family entertainment will probably be more dependent on theright programme schedule that is being shown during the weekend than ifthe game is shown on a smaller commercial channel. Dedicated football fans

will choose to watch a TV-match independently on what day of the week thematch is transmitted.

Viewing Time

Most people watch television in the evening, while viewing figures are muchsmaller during the rest of the day. Although there is no universal agreementabout the exact times for the day parts, prime time television is generallybetween 20.0023.00, Monday through Saturday, and 19.0023.00 Sunday.This is also the case for Norwegian broadcasters. As the table belowsuggests, the period 20.0023.00 has the highest ratings at any given week of



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the year 2006, closely followed by the period earlier in the evening(TNSGallup Norway, 2007). On average, the period 20.0023.00 scored34% on the ratings, while the period 19.3020.00 scored 28%. Comparable

statistics for Scandinavian television viewers overall show the same pattern(Barkho, 2005).

Summing up, we have identified two main television specific variables thatmay influence the viewing figures for televised football. In addition to typeof channel, the scheduling practices can be categorized in three subcate-gories; time of the year, week day and time of the day. In general, we expectviewing figures for football games to follow the overall pattern of alltelevision viewing. Games on public service broadcasters generate moreviewers than games on channels with lower penetration and on channels notfree of charge. Games during the summer season are believed to have lower

viewing figures than games broadcasted in the spring, winter and autumn.Furthermore, games that are shown on the most popular television times,such as Sunday night, are assumed to generate higher viewing figures also forfootball games. Similarly, evening games are believed to have higher viewingfigures than games shown during the day, because a greater number ofpeople watch television in the evening than in the afternoon.

Sport Studies: The demand for spectator sport

There exists a rich literature on demand for spectator sport (see Downward

& Dawson, 2000 or Borland & MacDonald, 2003, for an overview).Usually, demand has been analysed in terms of attendance figures. However,there is every reason to believe that many of the sporting and team specificvariables that have been applied in such studies are equally applicable to astudy of television ratings. In addition to television factors, three broadcategories of factors influencing demand have been identified (Downward &Dawson, 2000): sporting factors, competition factors and demographic/cultural factors. Firstly, we have sporting considerations. Clubs that performbetter tend to generate higher interest than clubs that perform poorly. Bysporting factors we mean within-season factors that affect the actualstanding of a club in a league. There are several measures that have been

Table 2. Day part ratings for Norwegian television viewers

Time 06000900 09001500 15001830 18302000 20002300 23000200

Week 5 3.1 7.9 15 35.3 40.4 11.4Week 11 3.4 8.3 13.3 32.3 38.8 9.9Week 17 2.8 4.5 9.6 27.3 36.3 11Week 26 1.2 2.9 8.7 21.4 27.2 10.6Week 32 1.4 3.8 8.2 21.3 27.1 9.4Week 38 2.6 4.2 9.2 27.6 35.6 9.6Week 44 2.8 4.9 11.7 32.2 37.6 9.6Week 51 2.9 6.7 11.4 26.2 31.8 12.8



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used, such as table position, points behind top team as well as form variablessuch as points amassed over the latest three games and so forth. Forrest et al.(2005) found in their study of English football on Sky Sport that there was apreference for games involving the bigger teams Liverpool and ManchesterUnited. Johnsen (unpublished) found that the pay channel Canal Pluspreferred to show local derbies from Stockholm, Gothenburg and the regionof Skane in their coverage of Swedish football, while Norwegian publicservice channels had a preference for games involving the bigger clubs, inparticular Rosenborg in their coverage of Norwegian football. In allcountries, there was a clear case of selecting what is considered the mostattractive clubs in the league. Findings suggest that demand is positivelycorrelated to sporting success, although when attendance is used a proxy fordemand, naturally the fortunes of the home team is much more decisive thanthose of the away team. When games are shown on television, there is reasonto believe that demand is more equally a function of both the home teams

and the away teams performances.However, as explained by Whannel (1992), while there are clearly

aesthetic pleasures in merely watching a sport performance, the real intensitycomes from identifying with an individual or team as they strive to win(p. 200). This argument points to that competitive balance is believed to havea positive impact on demand. Competitive balance has arguably attractedmore attention from scholars than any other single demand variables instudies on demand for spectator sport, but still the findings remain somewhatinconclusive. As far as television ratings are concerned, Forrest et al. (2005)did find a significant correlation between competitive balance and viewing

figures, although their construct for measuring competitive balance alsoincluded a variable for sporting performances. Thus, it was not entirely clearwhether their findings were due to sporting or competitive factors. At gamelevel, which is our level of analysis, uncertainty of outcome, expressedthrough betting odds or the difference in points between the two teams havebeen the most common measure, although findings have largely beeninconclusive for uncertainty of outcome at match level.

Thirdly, demographic factors matters. Clubs from more populous areastend to attract a higher number of spectators than clubs from smaller townsand rural areas. As such they are also more likely to dominate leagues and

win trophies. Indeed, in almost every country in Europe, football isdominated by clubs from the bigger cities. When employed, one has tendedto find a correlation between population size and attendance figures. Interms of television ratings, it is noticeable that all teams actually face thesame market, often a national market, and no club enjoys as such a biggermarket than other clubs. Instead, we must assume that clubs from morepopulous areas also have a greater number of fans and supporters. As such,they have an advantage over clubs from smaller towns even although theyoperate in the same television market.

Fourthly, cultural factors also matter. Clubs with a proud history tend tobe more popular than clubs without a history, even if they hail from the



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same city. Fans and supporters are attracted by success and clubs that winmany trophies will thus have created a bigger market than less successfulclubs. Similarly, games between rivals tend to generate a higher level ofinterest than other games. Such games may be local derbies, but the rivalrymay also be based on other factors. The Real MadridBarcelona fixture is anexample of a rivalry that is not based on geographical proximity, whileCelticRangers in Glasgow has sectarian overtones that marks it out frommore conventional city derbies in other places.

We believe these factors can be applied usefully also to explain demandfor televised football games, and will do so in our subsequent analysis. Thesecategories can not only be applied to attendance figures, but also ontelevision viewing figures. As was noted by Merkel (1994) consumers have adifferent set of characteristics than for example fans. Consumers areprobably less concerned about the actual teams that are playing and moreinterested in watching the sporting-wise most successful clubs. Hence,

sporting considerations may dominate a strategy of selecting games on thebasis of club size for a public service broadcaster wanting to maximize itsviewing figures.

One effect is that the interest may largely be club-specific. It is usual thatpeople with an expressed interest in football are fans of one particular teamand that they want to watch that club. Hence, for the television channel itmay be preferable to shown the clubs with the biggest number of fans andpay less attention to sporting matters. Fans of other clubs may tune in towatch games for sporting reasons as their interest in one club also makethem interested in the league as a while, but the less interested supporters

may not sit down and watch a game without their favourite team.

Research Question

So, we have identified two types of variables that may affect viewing figuresfor football games at different types of channels: scheduling (seasonalvariation, viewing day and viewing time) and football specific variables(sporting factors, competitive factors, demographic factors and culturalfactors). An illustration of the factors influencing the viewing figures oftelevised sport in our cases of public service broadcasters and a commercial

cable channel is given in the figure below.Our research question is therefore focused on what sporting specificfactors and scheduling strategies would influence the motivation for watch-ing football on different types of television channels. Although there aredifferences between NRK 1 and TV2 in terms of financial sources, we havegrouped them in one category as both are targeting a broad and hetero-geneous audience and operate under a public service broadcasting remit. Allthree types of broadcasters apply scheduling strategies in terms of viewingtime, viewing day and seasonal variation. A football game is peculiar astelevision content as it is relatively straightforward to quantify itscharacteristics. As noted in the literature review, a game can be quantified



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according to the sporting strength of the two teams, the competitiveness ofthe game as well as the demographic and cultural factors inherent in botheach club separately and the actual game itself.

Demographical speculations in our literature review suggest that peoplesinterest in football divide them into three main groups of viewers: fans,supporters and consumers. Given that a smaller proportion of the vieweraudience on the public service channels are committed football fans, theirinterest is more elastic and sensitive to other considerations such as therhythm of everyday life and demands of leisure time in general. Hence,

programme scheduling matters more to games shown on public servicebroadcasters than other types of channels. We therefore hypothesize thatpublic service channels are more sensitive to variations in schedulingpractices than other types of channels, but that all channel types aresensitive to viewing time. These arguments give us the following hypotheses:

. H1: Public service channels are more sensitive to variations in seasons(spring, summer and autumn) than other types of channels.

. H2: Football games that are shown in the weekends (Friday to Sunday)have higher viewing figures than games shown Monday to Thursday,especially for public service broadcasters.

. H3: Football games that are shown in the evening ought to have muchhighest viewing figures than games shown in the afternoon, irrespective oftype of channel.

In regard of the relationship between different types of broadcasters andfootball specific factors influencing the demand for televised sport weoperate with two assumptions. Firstly, the broader the audience, the lessimpact one segment has on total demand. Hence, fans of any given team willmore likely be in a minority in this setting. Even big clubs rarely control thefootball segment, and in the case of public service broadcasters transmis-

sion, it is reasonable to assume that the neutrals always constitute the

Viewing figures for TV- football on PSB and commercial cablechannel

Football specific factors Scheduling specificfactors

Sporting factors

Competitivefactors

Demographicfactors

Cultural factors

Viewing day

Seasonal variation

Viewing time

Figure 1. Sporting and television factors influencing viewing figures



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majority. As such, it seems unlikely that public service broadcaster will showgames based on choice of clubs.

Instead, there is reason to believe sporting achievements matter the mostwhen games are shown on public service broadcasters. As the majority ofviewers are club neutral, there is reason to believe they will rather want towatch games between teams that do well sporting-wise. Often, indeed mostof the time, the biggest clubs are also the most successful sporting-wise, butit need not be the case all the time. When there is a deviation, viewing figuresmay be higher on public service broadcaster if sporting considerations aregiven priority. We therefore assume that public service channels are morelikely to select games based on sporting criterions rather than criterionsrelated to clubs.

Given our assertion that fans and supporters constitute a larger part of theaudience for games shown on a narrow channel, it follows that we alsobelieve viewing figures on such channels are more closely related to the

demographic and cultural factors of the clubs. On public service broad-casters we believe such factors matter less as the broad audience ofconsumers is indifferent to the nature of each club and are more likely towatch games based on the sporting merits of the two clubs in action and thedegree of competitive balance. Thus, we want to test the followinghypothesis:

. H4: Public service channels viewer ratings are likely to correlate morestrongly with sporting and competition criterions than is the case for acommercial cable channel.

.

H5: A commercial cable channels viewer ratings are likely to correlatemore strongly with demographic and cultural factors than is the case forpublic service broadcasters.

The Analysis

In our analysis we are considering viewing figures for football games fromthe Norwegian top division Tippeligaen shown on Norwegian public servicechannels NRK 1 and TV2 in the period 19982007, a total of 212 games. Inthe period 19982005 these games were shown in equal numbers on the twochannels, while TV2 has had exclusive rights since the 2006 season. In thesame period, football games from the Danish top league Faxe Condi Ligaen/SAS Ligaen (the league changed sponsor in 2001 and subsequently its name)were shown on the commercial cable and satellite channel 3' in Denmark.In total 468 games were shown on 3' from 19992007. In order to be ableto compare the coefficient sizes of the variables in the two samples, werandomly selected 212 games from the Danish sample. Running identicalanalysis on the two samples we want to compare findings in viewing figuresand discuss how they are related to scheduling and football specific factorsas discussed above. Our analysis was carried out in the following order;descriptive analysis, factor analysis, residual analysis and by a regression

model.



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Descriptive Analysis

Firstly, we made sure that our variables were normally distributed. We didso by examining the skewness (less than one) and kurtosis (less than two) ofour non-dummy variables. Given that we wanted to compare two samples, it

was desirable that our variables had the same characteristics in the twosamples. For that reason, one variable was removed from our analysis as itwas normally distributed in one sample but not in the other. Variables thatwere normally distributed in both samples were kept, while variables thatwere not normally distributed underwent the usual log transformation toensure normality. Variable definitions for viewing figures of NRK 1, TV2and Channel 3' are presented in the table below.

The descriptive statistics for TV audience (thousands) is given in the tablebelow. The Norwegian channels showed 212 matches while the Danishchannel broadcasted 458 matches in the given period. In general, the

Norwegian public service channels draw more viewers than the Danishcommercial cable channel. On average, NRK and TV2 had 458,000 viewersdistributed on 212 matches while 3' had 141,000 viewers divided on 458matches. However, in the Norwegian cases, the variation between maximumviewers (938,000) and minimum viewers (148,000) are much bigger than inthe Danish case. For channel 3', the viewing figures are more stable,particularly when comparing Sunday night and Saturday afternoon. Herethe gap consists of only 252,000 viewers.

We notice that the Danish fans and supporters also have the opportunityto select from fewer days as the vast majority of the matches were shown onSunday and Saturday afternoon. In Norway, matches have been distributedthroughout the week at several different times, although almost half of thematches have been broadcasted on a Sunday night.

For both types of channels, the viewer ratings are generally high on aSunday. Also, Sunday night draws the highest figures for both types ofchannels compared to other time slots, while in the Norwegian cases Sundayevening and Sunday night are quite similar.

Factor Analysis

Our first five independent variables are so-called latent constructs made by

several variables. A principal component analysis was conducted in SPSS13.0. Following Hair et al. (1998)Hair et al. (1998a) factor analysis isconducted to summarize information from a number of variables into anew set of factors with a minimum loss of information (p. 95). In our case,we want to identify underlying structures within different categories ofvariables in order to reduce the number of variables in our regressionanalysis. We suspect that the variables concerning information about ourteams demographic and historical strength will reveal a pattern ofcorrelation, as will our sporting parameters for both the home and theaway teams. Our principal component analysis with VARIMAX rotation

revealed the components shown in the table below.



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Table 3. Variable definitions

Outcome uncertaintyOU1: The number of points the home team is behind the top teamthe number of points the

away the away team is behind the home team.

OU2. The number of points per game played the home team is behind the away teamthenumber of points per game played the away team is behind the top teamOU33. (OU1'1)* The number of points the home team is behind the top team'the number

of points the away the away team is behind the home team.OU4: (OU2'1)* The number of points per game played the home team is behind the away

team'the number of points per game played the away team is behind the top team.

Home teams demographic and historical strengthVariables to represent population in home teams catchments area and home teams number

of seasons in the top division for 5 years and 10 years.

Home team sporting performanceVariables to represent points last 3 games for home team, goals last 3 games for home team

and points behind for home team.

Away teams demographic and historical strengthVariables to represent population in away teams catchments area and away teams number

of seasons in the top division for 5 years and 10 years.

Away teams sporting performanceVariables to represent points last 3 games for away team, goals last 3 games for away team

and points behind for away team.

Game played Saturday and Sunday afternoonDefined as kick- off before 1900.

Game played Saturday and Sunday eveningDefined as kick- off at 1900 or later.

Game played on weekdaysMondayThursday, regardless of kick off.

Total weekly television viewingAudience estimates for televised matches as listed in TNS Gallup Norway/Denmark.

Spring, summer, autumn1 March to 20 June, 21 June to 29 August and 30 August to 10 December.

Seasons (19982007)Dummy variables to represent the season a fixture took place.

Games played during the World Cup or Summer OlympicsDummy variables to represent the period of other great sporting events.

The Copenhagen Derby (Danish sample)A dummy variable set equal to one for fixtures between Bro ndby and Ko benhavn in

Copenhagen.

The Oslo DerbyA dummy variable set equal to one for fixtures between Lyn Oslo and Valerenga in Oslo.

Rosenborg (Norwegian sample)A dummy variable set equal to one for fixtures including Rosenborg, the dominating team in

the period.



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We see from the table above that five distinct components emerge in bothcases. In both cases component one illustrates how different measures foroutcome uncertainty co-vary reflecting different aspects on outcomeuncertainty. If we had applied all four measures separately we would mostlikely have experienced severe multicollinearity. By applying this constructfurther, we avoid any multicollinearity while at the same time using aconstruct that captures the different aspects of outcome uncertainty. We find

that the two constructs are somewhat different, but still deem theseconstructs acceptable to capture outcome uncertainty in the two samples.Component 2 captures demographic population variables for the hometeam. As we can see, this variable correlates strongly with the number ofseasons a club has spent in the top division in the last ten and five yearsrespectively. We do find that there is a very strong correlation between thelatter two, while the population variable is fluctuating more. Component 3shows the same relationship between the same variables for away teams withsimilar outcome. Component four shows how our three within-seasonsporting variables for the away team correlate to each other. The two

indicators for form, points and goals last three games correlate stronglywhile the indicator for points behind top team correlate less strongly withthe construct. This reflects how all teams go through good and bad spellsduring the course of a season. Component 5 shows the same relationshipbetween the sporting variables for the home team. In addition, there is asixth component that detects some correlation between variables that weonly find in the Norwegian data set. For that reason we will omit from oursubsequent analysis.

This allows us to carry out our regression analysis with a smaller numberof variables. At the same time we retain the same number of dimension ofteam specific and sporting considerations that may affect demand. We arenow ready to carry out ordinary least squares regression analysis of the two

Table 4. Descriptive statistics for TV audience (millions)

Norway: PSB channels N MeanStandarddeviation Maximum Minimum

Average viewer ratings all games: 212 458 152.5 938 148Games Saturday afternoon 50 308 99.6 599 148Games Saturday night 21 375 103.9 703 185Games Sunday afternoon 15 459 174.6 661 185Games Sunday night 98 544 116.3 938 284Games on weekdays 29 473 129.5 675 185

Denmark: commercial cableAverage viewer ratings all games: 458 141 56.1 424 39Games Saturday afternoon 125 112 36.6 257 39Games Saturday night 3 113 27.1 139 85Games Sunday afternoon 210 166 56.6 414 49

Games Sunday night 8 178 41.3 253 133Games on weekdays 114 124 54.2 424 52



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Table 5. Principal component analysis

DENMARK

Component

1 2 3 4 5 1 2

Points last 3 games for home team 0.88 Goals last 3 games for home team 0.83 Points behind top team home team (x) (0.52Points last 3 games for away team (0.81 Goals last 3 games for away team (0.75 Points behind top team away team (y) 0.73

Population home team 0.61 0.5Home team season in top div last 10 yrs 0.94 0.9Home team season in top div last 5 yrs 0.92 0.9Population away team 0.72 Away team season in top div last 10 yrs 0.94 Away team season in top div last 5 yrs 0.91 Uncertainty of outcome 1* 0.99 0.56 Uncertainty of outcome 2** 0.52 0.97Uncertainty of outcome 3*** 0.95 Uncertainty of outcome 4**** 0.99 0.93


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data sets at hand. We have identified our team specific variables in the factoranalysis and in addition we have our scheduling and trend variables outlinedin the regression equation above.

A note is required concerning our cultural variables. We have added onesuch variable for the Danish sample, namely the game between Bro ndby andKo penhavn. We suspect that this game is greater than its two parts and thatthere is an added interest that is not captured by our team variables from thefactor analysis. In our Norwegian data set we have added two variables. Onevariable is a dummy for the Oslo derby between Valerenga and Lyn Oslo,following the same logic as for the Copenhagen derby. The second variableis a dummy for Rosenborg. Their domination of the Norwegian game hasbeen so total that we suspect that the variables that captures demographicand historical strength does not fully capture the success achieved byRosenborg in the period 19982007. Of the 10 full seasons under scrutiny,Rosenborg won the league on nine occasions. In Denmark the period has

been dominated by Bro ndby and Ko benhavn but not to the same extent ashas been the case with Rosenborg in Norway. For example, both provincialoutfits Herfo lge and Silkeborg won the league in the period 19982007.

Residual Analysis

We appreciate that there may be factors that have not been accounted for inour model, most prominently counter scheduling strategies from competingchannels, but also variables such as the weather or the occurrence of otherbig events which may effect demand in a fluctuation manner that our model

cannot control for. We ran a residual analysis and produce studentizedresiduals which were inspected to detect outliers. Observations with anabsolute residual value of greater than 1.85 were then deleted from thesecond analysis. We found 11 observations in the Norwegian sample withstudentized residuals greater than 1.85 and 13 observations in the Danishsample.

The Regression Model

The second run of the regression model produced the following values for

our two samples on the remaining observations and obtained the followingvalues (Table 6).Both samples produced a satisfactory fit with an adjusted R-squared of

62.4% for the Danish sample and a high 76.3% adjusted R-squared value

Table 6. Sample values

Model Adjusted R square Std. error of the estimate

Durbin-Watson statisticStudentized residualB1,85000 (Selected)

Denmark 0.624280371 32.07731417 2.001681701

Norway 0.763141482 69.85841259 2.227220938



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for the Norwegian data set. The DurbinWatson statistic is close to two forboth samples, ruling out the possibility of serious autocorrelation in our twosamples (Gujarati, 1993, pp. 390295). The variance inflation factor wasused to determine the existence of multicollinearity and we deemed ourfindings to be satisfactory as most had a value lower than two and nocontinuous variables had a value greater than four. Turning our attention toour actual findings, Table 7 shows the values obtained for our sets ofvariables.

As we are comparing across samples, we are primarily interested inpercentage change caused by each variable. We will therefore use thestandardized Beta, taking necessary caution with the use, as a proxy of thischange. Along with the t-value and the B values this will be used to compareour findings. Let us go through our stated hypothesis and see how they standup to empirical scrutiny.

.

H1: Public service channels are more sensitive to variations in seasons(spring, summer and autumn) than other types of channels

We find that the variable total weekly television viewing correlates stronglywith public service broadcaster viewer interest. A one hour increase in weeklytelevision viewing results in 17,000 extra viewers for a football games on aNorwegian public service broadcaster, while the corresponding figure for aDanish cable channel was 4.975. There is also a significant difference int-values (4.639 versus 2.939) and the indication is that there is a strongercorrelation between overall viewing patterns and interest for televisedfootball on a public service channel than on a commercial cable channel.

However, we also find in both our samples that spring games attracthigher viewer ratings than the summer and the autumn. This might suggestthat the interest for football is higher during the spring for all types ofviewers. Our findings suggest that there is a fall in public service broad-casting viewer interest in autumn in the Norwegian league of 13.6% (with at-value of 3.429), while there is a fall in the summer period of 10.9%,although with a t-value of 1.89 the latter observation is not significant at the95%-level. One reason for this might be that there is a greater interest at thestart of the football season, but that this interest falls during the season. Inthe Danish league there is a fall in viewer interest in summer and autumn

compared to spring, but this reduction is not statistically significant for anyof the seasons.

Thus, we find support for our hypothesis that viewer interest is moresensitive to variations in seasons on public service broadcasting channelsthan on cable channels, but it is only in autumn that the difference issignificant and this runs contrary to our assertion that the summer period isthe low point for televised football other than the decrease already countedfor in total weekly viewing.

. H2: Football games that are shown in the weekends (FridaySunday) havehigher viewing figures than games shown MondayThursday, especiallyfor public service broadcasters.



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Table 7. Coefficients from Denmark and Norway, N0199 (Denmark) and N02

DEN Comparison

Variables B Beta T Den/Nor B

(Constant) 74.621 2.354 B, X 259Outcome uncertainty 0.815 0.015 0.330 B, B 9HomeDemHist 7.483 0.141 2.823 , 12AwayDemHist 6.714 0.130 2.785 , 10HomeSporPer 2.313 0.045 0.967 , 3AwaySporPer (9.437 (0.182 (3.375 , 2S9899 (24.810 (0.098 (1.754 (106S9900 (46.209 (0.191 (3.615 (78S0001 (11.592 (0.070 (1.167 46S0102 (1.463 (0.009 (0.143 (47S0203 18.035 0.105 1.833 (9S0304 38.929 0.249 4.012 (55S0405 17.511 0.126 1.946 (56S0506 4.384 0.031 0.495 2Weekly TV viewing 4.975 0.183 2.939 B, B 17Saturday afternoon (59.561 (0.509 (5.105 B, B (200Saturday evening (62.224 (0.117 (2.368 B, B (189Sunday afternoon (4.792 (0.045 (0.411 B, B (73Weekday (28.430 (0.234 (2.286 B, (60Summer (9.828 (0.064 (0.903 B, B (37Autumn (6.608 (0.063 (1.231 B, B (43WC/Olympic Games (28.207 (0.075 (1.575 B, B (97

Copenhagen Derby 84.719 0.350 7.425Rosenborg 70Oslo Derby 66


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Sunday evening (defined as kick-off at 19.00 or later) is the best time slot forboth cable channels and public service broadcasters. However, weekdays arebetter than Saturdays for both types of channels. While Saturday generally isa very good day for television viewing, it has proved less for live footballcoverage. While there is a 14.6% decrease in viewing figures using thestandardized Beta as our measure for weekday games compared to Sundayevening on the public service broadcasters, the corresponding decrease is39.5% when games are moved to Saturday evening. Both findings aresignificant at the 95% level and they are also statistically different from eachother.

For the cable channel, our findings are less conclusive due to few gamesbeing played Saturday evenings. The limited material we have suggest thatthere is a fall in viewer interest when games are moved to Saturday eveningand that this reduction in viewing figures is greater than when games areshown on weekdays.

Comparing Sunday afternoon to Saturday afternoon, we find that oncable there is also a significant difference between the two days. While thereis no statistically significant difference between Sunday evenings and Sundayafternoon interest, games on Saturday experience a fall of 50.9%. On publicservice channels, the difference is comparable, only with the difference thatgames played on Sunday afternoon attract significantly fewer viewers thangames played Sunday evening with a fall of 13.6%. Games played onSaturday afternoon have a decrease of 58.6% and this figure is significantlylower than the Sunday afternoon games.

So, our findings suggest that there is every reason to further segment the

weekend into individual days as Sundays outperform Saturdays. Also, whileSunday evening is the preferred slot for both types of channels, thepercentage in number viewers is more marked for a public service broad-caster than a commercial cable channel. This evidence lends support to ourassumption that the viewer segments are much more heterogeneous on apublic service broadcaster than on a commercial channel.

. H3: Football games that are shown in the evening ought to have muchhighest viewing figures than games shown in the afternoon, irrespective oftype of channel.

We find this to be true for public service channels, as the games shown onSunday evening have significantly higher viewing figures than games playedon Sunday afternoon. On average 72,000 fewer viewers chose to watch anafternoon kick-off on Sundays compared to evening games. On Saturdays,interest is lower in general, but we also find that there is a difference betweengames shown on Saturday evening and Saturday afternoon, but thisdifference is not statistically significant.

For games shown on cable channels, we do not find a significantdifference between Sunday afternoon and Sunday evenings games in termsof viewer interest. Also for the Saturday games the difference is notsignificant, but we would have to treat this comparison with extremecaution anyway because of the few observations of games played Saturday



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night. So, we find that public service broadcasters experience a difference inratings due to evening kick-off on Sundays. On Saturdays, evening kick-offshas a more limited effect.

For cable channels we cannot find any significant differences in viewerinterest caused by evening kick-offs instead of afternoon games. Hence, theindication is that cable channels are more flexible with respect to kick-offtimes, while public service channels depend more on the Sunday night kick-off to generate the largest audiences.

. H4: Public service channels viewer ratings are likely to correlate morestrongly with sporting and competition criterions than a commercial cablechannel.

Of the four constructs we developed to capture viewer interest based onsporting performance only one is significant; the sporting performance of theaway team in the Danish league (with a t-value of -3.375). While the

indication is that the better the away team does the higher is the viewerinterest, this runs counter to our hypothesis. One possible explanation maybe that because viewer figures are modest for a cable channel, the fans andsupporters of away team that do not travel to away games may constitute alarge enough group of people to make a significant difference in viewingfigures. The corresponding group of fair-weather supporters for the hometeam may then possibly prefer stadium attendance.

The Norwegian figures may also be influence by the variable specificallyfor Rosenborg, which is highly significant with a t-value of 6.289 and a Betaof 24%. Still, it is noteworthy that there is no variation caused by the

sporting fortunes of other teams. This may indicate that the public servicebroadcaster viewers preferences are not determined by the actual results ofthe teams. We do find that the outcome uncertainty construct is insignificantat the 5% level in both samples.

. H5: A commercial cable channels viewer ratings are likely to correlatemore strongly with demographic and cultural factors than is the case forpublic service broadcasters.

We find that the values for the home and away teams demographic andhistorical strengths are higher in the commercial cable channel case than

when games are shown on public service broadcasters. The difference is notlarge enough to be statistically significant at the 95% level, but there is stillsome indication that these variables matter more when games are shown ona commercial cable channel. The four variables are all statisticallysignificant, but the t-values are greater in the commercial cable channelmodel. Thus, our findings do lend us limited but not conclusive support forour hypothesis.

We also find that our cultural variables are significant. The Copenhagenderby between Bro ndby and Ko benhavn attracts on average 84,000 extraviewers to the screen on cable, and is the single most significant variable witha t-value of 7.425. In the public service broadcaster sample, we found thatthe Oslo derby attracts 66,000 extra viewers and that the correlation is



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significant at the 95% level with a t-value of 2.187. However, moresignificant is the unique position of Rosenborg in the Norwegian data. Theteams presence on the screen increased viewing figures by 70,000. Thisfigure was highly significant with a t-value of 6.289. It is noteworthy that itseems possible for teams to appeal to a mass audience through the sheerforce of their name. However, our findings suggest that in general the nameof the clubs is more decisive on a commercial cable channel than on a publicservice channel.

Conclusion

In this paper we have tired to identify factors specific to football and factorsspecific to program scheduling practices that influence viewing figures forfootball games shown on public service broadcaster channels and on privatechannels.

Of the football specific factors, we found limited support for ourhypothesis that demographic and historical factors are more important onprivate channels than on public service channels. This suggests that the fanelement is more important for viewing figures on private channels where agreater share of the viewers are fans and supporters who discriminate morestrongly between the different clubs. Outcome uncertainty does not appearto play a more important role for public service channels than for thecommercial channel. It sounds unlikely that outcome uncertainty does notinfluence viewer interest more strongly, and further explorations are neededin this area. We still believe that the large group of casual viewers on public

service channels are more interested in an open and exciting game than in thedemographical and historical factors of the teams performing.

In general, our analysis has offered support to the notion that strategicscheduling is an influence on demand for the TV audience. The traditionaluser-centred assumption that football interest among the audience drives thedemand for televised football receives little support in our study. The lowratings for Saturday afternoon may suggest that football does notautomatically draw together a large group of viewers, but that football, asother programs, are dependent on the best time slot both in the week and inthe day, which is Sunday evening.

While we do find fluctuating viewing patterns caused by schedulingstrategies, these effects are significantly stronger on public service channelsthan on private channels. We therefore believe that the audience of a privatechannel is less affected by when a football transmission is scheduled than theaudience of a public service channel. In other words, the audience segmentsof a private channel (in our case fans and supporters) is less dependent onmedia specific factors than the large and heterogeneous audience of a publicservice channel. The audience segment for a public service broadcaster hasnot the same, strong preference for what programs to watch, as the fans andsupporters have, making it easier for a public service broadcaster to guidetheir audiences needs and preferences and, thus, their behaviour. Thissegment is therefore largely governed by viewing habits created by the



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television schedule, as suggested by the media-centred perspective. They arelikely to watch a football game on Sunday evening as this is their primetelevision time and prime television day.

Summing up, it seems that private channels with limited viewing figuresare more dependent on showing popular football clubs with many fans andsupporters in order to attract viewers, than public service broadcasters. For apublic service broadcaster to maximize its viewing figures, schedulingstrategies in terms of season, week day and time slots play a more decisiverole than types of games. This suggests that the viewers have differentmotives for watching games on a public service broadcaster than on aprivate channel. For a private channel content is decisive while for publicservice broadcaster timing is everything. Our main conclusion differssomewhat from the main mantra in the television industry nowadays, thatcontent is king. The right content is king on private channels, but timing iseverything for public service broadcasters.

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