TELEVISION DEMAND FOR THE TOUR DE :

THE IMPORTANCE OF OUTCOME UNCERTAINTY, PATRIOTISM AND DOPING

Séminaire DESport March 9, 2012 Paris

Prof. Dr. Daam Van Reeth HogeschoolHogeschool--UniversiteitUniversiteit Brussel, Brussels, Belgium Introduction - Cycling on TV – Literature - Model - Results – Future research

ANALYSING TV VIEWING FOR CYCLING IS USEFUL TO: (1) TEAM SPONSORS

 TV exposure in the TdF is crucial for sponsors of cycling teams:

– Rabobank invested 11 million € in its 2007 professional cycling team while three week TdF exposure (TV and newspapers) is valued at 15 million € (Rabobank, 2007). Introduction - Cycling on TV – Literature - Model - Results – Future research

ANALYSING TV VIEWING FOR CYCLING IS USEFUL TO: (1) TEAM SPONSORS

 TV exposure in the TdF is crucial for sponsors of cycling teams:

– Rabobank invested 11 million € in its 2007 professional cycling team while three week TdF exposure (TV and newspapers) is valued at 15 million € (Rabobank, 2007).

– Because of presumed cocaine abuse, was banned from participating in the 2008 TdF. According to team marketing director Philiep Caryn, his absence could cost the Quick-Step cycling team millions: “ Last year Quick- Step obtained 4 stage victories. These stage victories had a publicity value of two to three million euro .” (De Standaard, 2008) Introduction - Cycling on TV – Literature - Model - Results – Future research

ANALYSING TV VIEWING FOR CYCLING IS USEFUL TO: (1) TEAM SPONSORS WHO REALLY WON THE 2011 ?

Sylvain Chavanel

Nick Nuyens Introduction - Cycling on TV – Literature - Model - Results – Future research

ANALYSING TV VIEWING FOR CYCLING IS USEFUL TO: (1) TEAM SPONSORS WHO REALLY WON THE TOUR OF FLANDERS 2011 ?

TEAM SAXO BANK WON THE RACE FROM A SPORTING POINT OF VIEW (but: team received only 2% of all media attention)

Nick Nuyens Introduction - Cycling on TV – Literature - Model - Results – Future research

ANALYSING TV VIEWING FOR CYCLING IS USEFUL TO: (1) TEAM SPONSORS WHO REALLY WON THE TOUR OF FLANDERS 2011 ?

TEAM SAXO BANK WON Sylvain Chavanel THE RACE FROM A SPORTING POINT OF VIEW (but: team received only 2% of all media attention)

TEAM QUICK-STEP WAS COMMERCIALLY THE MORE SUCCESFUL TEAM

(team received over 10% of Nick Nuyens all media attention) Introduction - Cycling on TV – Literature - Model - Results – Future research

ANALYSING TV VIEWING FOR CYCLING IS USEFUL TO: (2) RACE ORGANIZERS

Is Giro d’Italia Angelo Zomegnan director about to be sacked? (CyclingNews, 2011-06-25) Rumours of Zomegnan’s demise first circulated during the Giro d’Italia dominated by . Italian television was not happy with this year’s race and pointed the finger at Zomegnan, suggesting the extremely tough race route had reduced the appeal of the Giro. Since taking the position of race director, Zomegnan has helped raise the international profile of the Giro d’Italia . The introduction of dirt road sections and testing climbs produced some spectacular racing , especially in 2010.

 Zomegnan was indeed sacked a couple of months later Introduction - Cycling on TV – Literature - Model - Results – Future research

ANALYSING TV VIEWING FOR CYCLING IS USEFUL TO: (3) TV BROADCASTERS

 The sport industry generates added value for TV broadcasters: - More than 70% of the free to air channels achieve a higher market share with sports programs in comparison to its average performance all genres combined. Introduction - Cycling on TV – Literature - Model - Results – Future research

ANALYSING TV VIEWING FOR CYCLING IS USEFUL TO: (3) TV BROADCASTERS

 The sport industry generates added value for TV broadcasters: - More than 70% of the free to air channels achieve a higher market share with sports programs in comparison to its average performance all genres combined. - The market share of Canadian channel “ CBC ” rises to 29,9% when it airs sports from 5% for all its programming. In Belgium, in 2011 the Flemish public channel “ Eén ” dedicated 6% of its airtime to sport programming, recording an average market share of 46,4% versus an overall market share of 31,3%.

Source : Television 2011, International Key Facts, RTL Group Introduction - Cycling on TV – Literature - Model - Results – Future research RESEARCH QUESTIONS

• Research focus: “ What determines TV viewership for (TdF) stages ?” • Specific research questions: – To what extent is TdF viewership driven by scheduling aspects?  Race organizers, TV broadcasters – How relevant is the concept of outcome uncertainty in TdF viewing?  Race organizers – How important is patriotism in watching the TdF?  Team sponsors, TV broadcasters – Does doping affect TV interest in cycling?  TV broadcasters, Team sponsors – Can TdF TV audiences be predicted accurately?  TV broadcasters Introduction - Cycling on TV – Literature - Model - Results – Future research

MY PREDICTION: THE EXPECTED 2011 TOUR DE FRANCE PEAK AND AVERAGE TV AUDIENCE IN FLANDERS

(Remark: bold lines mark range of 1 standard deviation from the predicted value)

1.400.000

1.200.000

1.000.000

800.000

600.000

400.000

200.000

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Introduction - Cycling on TV – Literature - Model - Results – Future research CYCLING AND TELEVISION: A PERFECT FIT

 Cycling is a sport that can only be understood well through access to the media (not in a stadion, (usually) not on a circuit, …) Introduction - Cycling on TV – Literature - Model - Results – Future research CYCLING AND TELEVISION: A PERFECT FIT

 Cycling is a sport that can only be understood well through access to the media (not in a stadion, (usually) not on a circuit, …)  Cycling is an ideal sport to promote tourism (showcase to the world for a city or a region) Introduction - Cycling on TV – Literature - Model - Results – Future research CYCLING AND TELEVISION: A PERFECT FIT

 Cycling is a sport that can only be understood well through access to the media (not in a stadion, (usually) not on a circuit, …)  Cycling is an ideal sport to promote tourism (showcase to the world for a city or a region)  Cycling is not subject to many technical rules or game regulations, which makes it easy to understand (low viewing barriers) Introduction - Cycling on TV – Literature - Model - Results – Future research CYCLING AND TELEVISION: A PERFECT FIT

 Cycling is a sport that can only be understood well through access to the media (not in a stadion, (usually) not on a circuit, …)  Cycling is an ideal sport to promote tourism (showcase to the world for a city or a region)  Cycling is not subject to many technical rules or game regulations, which makes it easy to understand (low viewing barriers)  In spite of its uncertain duration, cycling is easy to fit in existing TV schedules (in Europe, it is an “afternoon filler” and not an “evening prime time contender”) Introduction - Cycling on TV – Literature - Model - Results – Future research CYCLING AND TELEVISION: A PERFECT FIT

 Cycling is a sport that can only be understood well through access to the media (not in a stadion, (usually) not on a circuit, …)  Cycling is an ideal sport to promote tourism (showcase to the world for a city or a region)  Cycling is not subject to many technical rules or game regulations, which makes it easy to understand (low viewing barriers)  In spite of its uncertain duration, cycling is easy to fit in existing TV schedules (in Europe, it is an “afternoon filler” and not an “evening prime time contender”)

 Cycling is probably the sport with the highest number of non-fans watching Introduction - Cycling on TV – Literature - Model - Results – Future research

WHY STUDY THE TOUR DE FRANCE?

 It is the most important and best watched cycling race in the world: - Together with the cobblestones classics Paris-Roubaix and the Ronde van Vlaanderen it is the only cycling race to receive worldwide live coverage. Introduction - Cycling on TV – Literature - Model - Results – Future research

WHY STUDY THE TOUR DE FRANCE?

 It is the most important and best watched cycling race in the world: - Together with the cobblestones classics Paris-Roubaix and the Ronde van Vlaanderen it is the only cycling race to receive worldwide live coverage. - 190 nations had TV images of the 2011 TdF, with 60 channels broadcasting the race live, double the number from a decade ago. - For some stages average audience ranges between 15 and 20 million, total viewers for top mountain stages is between 40 and 50 million. Introduction - Cycling on TV – Literature - Model - Results – Future research

WHY STUDY THE TOUR DE FRANCE?

 It is the most important and best watched cycling race in the world: - Together with the cobblestones classics Paris-Roubaix and the Ronde van Vlaanderen it is the only cycling race to receive worldwide live coverage. - 190 nations had TV images of the 2011 TdF, with 60 channels broadcasting the race live, double the number from a decade ago. - For some stages average audience ranges between 15 and 20 million, total viewers for top mountain stages is between 40 and 50 million. - The TdF is amongst the 10 most watched sports events worldwide (next to the Super Bowl, Champion’s League, Wimbledon, World Athletics Championship, U.S. Masters, and top F1, Motor cycling, Badminton, Basketball and Baseball events). Introduction - Cycling on TV – Literature - Model - Results – Future research WHY STUDY FLANDERS? (… apart from the fact that I live there) Introduction - Cycling on TV – Literature - Model - Results – Future research WHY STUDY FLANDERS? (… apart from the fact that I live there)

TOP 10 SPORTS BROADCASTS FLANDERS, 2011

Source : Television 2011, International Key Facts, RTL Group Introduction - Cycling on TV – Literature - Model - Results – Future research TOP 10 SPORT BROADCASTS PER COUNTRY 2010 (Source: Television 2010, International Key Facts, RTL Group)

Football Cycling American Athletics Boxing Formula Tennis Rugby Hand- Basket- Base- Sumo Biathlon Skating Moto Football 1 ball ball ball wrestling racing

Belgium 4 6 North

Belgium 10 South

France 10

Germany 5 3 1 1

Italy 8 1 1

The 7 3 Netherlands (speed)

Spain 10

Turkey 10

United 5 3 1 1 Kingdom

Japan 1 1 5 1 1 1 (figure)

U.S.A. 9 1

Russia 5 4 1 (ice hockey) Introduction - Cycling on TV – Literature - Model - Results – Future research WHY STUDY FLANDERS?

CYCLING RACES ON VRT (Belgian public channel) (1997-2010)

Races

50

45

40

35

30

25 Races

20

15

10

5

0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 200 9 2010

Over the years, no less than 62 different cycling races have been shown on Flemish public television Introduction - Cycling on TV – Literature - Model - Results – Future research WHY STUDY FLANDERS?

CYCLING RACES ON VRT (Belgian public channel) (1997-2010)

50

45

40

35

30 Races - live Races - summary 25 Races - live & summary Races 20

15

10

5

0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 200 9 2010

Over the years, no less than 62 different cycling races have been shown on Flemish public television Introduction - Cycling on TV – Literature - Model - Results – Future research WHY STUDY FLANDERS?

CYCLING BROADCASTS ON VRT (Belgian public channel) (1997-2010)

400

350

300

250 Races Live broadcasts 200 Calendar days Hours 150

100

50

0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 20089 200 2010

 If we include cyclocross and races on other free channels, there are easily over 200 days of cycling on Belgian TV a year, a figure no other country worldwide can match. Introduction - Cycling on TV – Literature - Model - Results – Future research TOUR DE FRANCE AVERAGE VIEWING FIGURES: FLANDERS versus OTHER COUNTRIES (in millions, 19971997--2011)2011)

4,00

3,50

3,00

2,50

FLA 2,00 FRA

1,50

1,00

0,50

0,00 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 200 9 2010 2011 Introduction - Cycling on TV – Literature - Model - Results – Future research TOUR DE FRANCE AVERAGE VIEWING FIGURES: FLANDERS versus OTHER COUNTRIES (in millions, 19971997--2011)2011)

4,00

3,50

3,00 FLA WAL 2,50 FRA GER HOL 2,00 ITA SPA USA 1,50 AUS NOR GBR 1,00

0,50

0,00 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 200 9 2010 2011 Introduction - Cycling on TV – Literature - Model - Results – Future research

FLANDERS: THE HEART OF TELEVISED CYCLING

Best watched stage 2009 (stage 20, Mont-Ventoux)

Best watched stage 2005 (final stage, Paris)

Source : ViewerTrack reports

With the highest TdF TV-ratings worldwide and in absolute numbers currently more important than the U.S., Great Britain or Australia, definitely a case could be made for choosing Flanders when analysing viewership for live cycling. Introduction - Cycling on TV – Literature - Model - Results – Future research

LITERATURE ON THE ECONOMICS OF CYCLING

• Cycling has not yet been studied extensively in sports economics literature. Recent research is centered around the following themes: – Organisational issues: Rebeggiani & Tondani (2007), Morrow & Idle (2008), Desbordes (2008), Gueguen (2009a, 2009b), Candelon & Dupuy (2010), Benijts, Lagae & Vanclooster (2011), Larson (2011) – Determinants of success: Prinz (2005), Sterken (2005) Cherchye & Vermeulen (2006), Torgler (2006), Schumacher et al. (2006), Rogge, Van Reeth & Van Puyenbroeck (2012) – Cycling dynamics: Hannas & Goff (2005), Bhurruth (2008), Dilger & Geyer (2009), Lybbert et al. (2011)

 And also some research on economic impact, doping, ...

 Baseline: in contrast to what is the case for many other sports, there exists no demand related research for cycling yet ! Introduction - Cycling on TV – Literature - Model - Results – Future research LITERATURE ON SPECTATOR DEMAND FOR SPORT

Two sorts of spectator demand for sport

– Direct sport consumption :  live attendance demand (gate entrance)  long tradition within sports economics with several hundreds of papers published: see Villar & Rodriguez (2008) for an excellent survey  often studied with respect to the impact of outcome uncertainty  less relevant in cycling because of the (still) free nature of direct consumption of the sport

– Indirect sport consumption :  media coverage demand (newspaper, radio, television, Internet)  television audience demand has gained research interest only recently (see further)  highly relevant in cycling (“perfect fit”) Introduction - Cycling on TV – Literature - Model - Results – Future research

LITERATURE ON TV DEMAND FOR SPORT

As a result from the historical focus on direct consumer demand, television demand for sport was at first mainly analysed in relationship to this game attendance, the so- called crowding-out effect of live broadcasts on games.

 American football: Kaemper & Pacey (1986), Fizel & Bennett (1989), Putsis & Sen (1999)  Basketball: Zhang & Smith (1997)  Rugby: Baimbridge et al. (1995), Carmichael et al. (1999)  Soccer: Kuypers (1995), Baimbridge, Cameron & Dawson (1996), Czarnitzki & Stadtmann (2002), Forrest, Simmons & Szymanski (2004), Allan & Roy (2008) Introduction - Cycling on TV – Literature - Model - Results – Future research

LITERATURE ON TV DEMAND FOR SPORT

• Research on TV demand for sport with the use of detailed data on TV audiences really started to grow from 2005 on. – Seminal paper by Forrest, Simmons & Buraimo (2005) on the couch potato audience – Subsequent research in Europe for other soccer competitions: • England: Buraimo (2008), Alavy, Gaskell, Leach & Szymanski (2010) • Germany (national teams): Feddersen & Rott (2011) • Italy: Di Domizio (2010) • : Garcia & Rodriguez (2006), Buraimo & Simmons (2007) • Switzerland (national teams): Nüesch & Franck (2009) • Scandinavia: Johnsen & Solvoll (2007) – In the United States there are studies on typical American sports like: • American Football: Biner (2009) • NASCAR: Berkowitz, Depken & Wilson (2010) Introduction - Cycling on TV – Literature - Model - Results – Future research

The importance of outcome uncertainty on viewership: TV audiences versus attendance

Berkowitz, Car racing With greater uncertainty, fan interest reflected in attendance and viewership Depken & Wilson increases. With less competitive balance, fan interest in TV viewership falls but (2010) attendance is not influenced.

Biner (2009) American TV ratings are determined mostly by close games with possibly strong teams Football playing each other. Stadium attendance is determined by home team’s dominance.

Buraimo & Soccer Unlike their stadium counterparts, who have a preference for outcomes which Simmons (2007) favour their home team, TV audiences overwhelmingly prefer close matches than ones in which the outcomes are more predictable.

 Outcome uncertainty is much more important to TV audiences than to the fans attending a game, the latter usually favouring home team dominance. Introduction - Cycling on TV – Literature - Model - Results – Future research

The importance of outcome uncertainty on viewership: how do TV audiences react ?

Alavy, Gaskell, Soccer Audience fluctuations within matches are significantly affected by the progress of Leach & the game. Fans switch channels away from the game if they find the probability of Szymanski (2010) a draw is increasing, or they switch to and stick with a game that has an exciting result in prospect.

Garcia & Soccer The ex ante attractiveness of a match is the main determinant of the size of the Rodriguez (2006) audience. There is also a strong seasonal component in the evolution of the size of the audience within the football season.

Feddersen & Rott Soccer Demand depends mostly on the type of match and its importance in a (2011) tournament context . Viewers prefer a national team with established star players and high-quality opponents .

 During a game and throughout the season, TV audience changes with the (expected) sportive outcome. Introduction - Cycling on TV – Literature - Model - Results – Future research

The importance of outcome uncertainty on viewership: how do TV audiences react ?

Di Domizio (2010) Soccer More then 90% of variability concerning TV audience can be explained net of uncertainty factors. Variables associated with the closeness of the match are not crucial in determining the TV share.

Forrest, Simmons Soccer Outcome uncertainty is a significant determinant of audience size, but the & Buraimo (2005) magnitude of its impact is modest relative to the prominence of the issue in sports economics.

 Outcome uncertainty only plays a minor role in explaining TV audience. Introduction - Cycling on TV – Literature - Model - Results – Future research

The analysis of TV audiences: studies not primarily focussing on outcome uncertainty

Johnsen & Solvoll Soccer For a private channel content (types of games shown) is decisive, while for public (2007) service broadcaster timing is everything (scheduling strategies).

 For maximizing TV viewership, sportive characteristics as well as scheduling characteristics matter.

Nüesch & Franck Soccer Both the expected game quality based on the proven playing strength of the teams, and (2009) patriotism strongly predict the TV figures. Regarding the TV audiences of national team competitions, the relevant market is not geographically but nationally segmented.

 Patriotism can play an important role in TV viewership too. Introduction - Cycling on TV – Literature - Model - Results – Future research METHODOLOGY

• Data (317 observations) are selected from a larger dataset of almost 2000 VRT cycling broadcasts: – Race: Tour de France – Period: 1997-2011 (all TdF stages) – Region: Flanders – Items: date / stage / channel / duration / audience measures

• Method: OLS regression analysis

• Two models different only in the TV viewership measure used as dependent variable:

 Average audience model (focus in this presentation)  Peak audience model Introduction - Cycling on TV – Literature - Model - Results – Future research AVERAGE vs. PEAK AUDIENCE (Dutch data, Tour of Flanders, 20112011--0404--03)03)

NL 1: Wielrennen ronde van vlaanderen heren 13:34-16:10 16:04 873

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0 13:20 13:30 13:40 13:50 14:00 14:10 14:20 14:30 14:40 14:50 15:00 15:10 15:20 15:30 15:40 15:50 16:00 16:10 16:20 Date: 03-04-11 Introduction - Cycling on TV – Literature - Model - Results – Future research AVERAGE vs. PEAK AUDIENCE (Dutch data, Tour of Flanders, 20112011--0404--03)03)

NL 1: Wielrennen ronde van vlaanderen heren 13:34-16:10 16:04 873 873.000 850 peak 800

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0 13:20 13:30 13:40 13:50 14:00 14:10 14:20 14:30 14:40 14:50 15:00 15:10 15:20 15:30 15:40 15:50 16:00 16:10 16:20 Date: 03-04-11 Introduction - Cycling on TV – Literature - Model - Results – Future research AVERAGE vs. PEAK AUDIENCE (Dutch data, Tour of Flanders, 20112011--0404--03)03)

NL 1: Wielrennen ronde van vlaanderen heren 13:34-16:10 16:04 873 873.000 850 peak 800

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550

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Rating in 000 400

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200 average

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0 13:20 13:30 13:40 13:50 14:00 14:10 14:20 14:30 14:40 14:50 15:00 15:10 15:20 15:30 15:40 15:50 16:00 16:10 16:20 Date: 03-04-11 Introduction - Cycling on TV – Literature - Model - Results – Future research VIEWERSHIP TOUR: data summary

Average Average Average Year Stages duration audience peak audience

1997 22 03:02:02 406,208 588,941

1998 22 03:14:23 417,547 608,973

1999 21 02:59:32 413,706 592,846

2000 21 03:02:28 460,912 657,101

2001 21 03:41:51 431,544 650,919

2002 21 03:30:10 375,548 592,634

2003 21 03:53:26 449,664 724,669

2004 21 03:48:59 401,516 679,330

2005 21 03:18:34 458,612 764,762

2006 21 03:27:21 444,584 747,103

2007 21 03:52:53 498,656 865,676

2008 21 03:40:12 418,916 698,432

2009 21 03:45:53 477,043 795,646

2010 21 03:43:47 566,099 900,082

2011 21 03:45:52 585,873 919,785

Average 03:31:10 453,762 719,127 Introduction - Cycling on TV – Literature - Model - Results – Future research VIEWERSHIP TOUR: data summary

Average Average Average Year Stages duration audience peak audience

1997 22 03:02:02 406,208 588,941

1998 22 03:14:23 417,547 608,973

1999 21 02:59:32 413,706 592,846

2000 21 03:02:28 460,912 657,101

2001 21 03:41:51 431,544 650,919

2002 21 03:30:10 375,548 592,634

2003 21 03:53:26 449,664 724,669

2004 21 03:48:59 401,516 679,330

2005 21 03:18:34 458,612 764,762

2006 21 03:27:21 444,584 747,103

2007 21 03:52:53 498,656 865,676

2008 21 03:40:12 418,916 698,432

2009 21 03:45:53 477,043 795,646

2010 21 03:43:47 566,099 900,082

2011 21 03:45:52 585,873 919,785

Average 03:31:10 453,762 719,127 Introduction - Cycling on TV – Literature - Model - Results – Future research VIEWERSHIP TOUR: data summary

Average Average Average Year Stages duration audience peak audience

1997 22 03:02:02 406,208 588,941

1998 22 03:14:23 417,547 608,973

1999 21 02:59:32 413,706 592,846

2000 21 03:02:28 460,912 657,101

2001 21 03:41:51 431,544 650,919

2002 21 03:30:10 375,548 592,634

2003 21 03:53:26 449,664 724,669

2004 21 03:48:59 401,516 679,330

2005 21 03:18:34 458,612 764,762

2006 21 03:27:21 444,584 747,103

2007 21 03:52:53 498,656 865,676

2008 21 03:40:12 418,916 698,432

2009 21 03:45:53 477,043 795,646

2010 21 03:43:47 566,099 900,082

2011 21 03:45:52 585,873 919,785

Average 03:31:10 453,762 719,127 Introduction - Cycling on TV – Literature - Model - Results – Future research Technical remark: UNDERESTIMATION OF VIEWERSHIP Dutch viewers watching Dutch television = included in Dutch viewing figures

NL 1: Wielrennen 16:58 14:25-17:10 761

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14:10 14:20 14:30 14:40 14:50 15:00 15:10 15:20 15:30 15:40 15:50 16:00 16:10 16:20 16:30 16:40 16:50 17:00 17:10 17:20 Date: 26-02-11 Introduction - Cycling on TV – Literature - Model - Results – Future research Technical remark: UNDERESTIMATION OF VIEWERSHIP Dutch viewers watching Dutch television = included in Dutch viewing figures Dutch viewers watching Flemish television

NL 1: Wielrennen omloop het nieuwsblad 16:58 = not included in Dutch viewing figures and 14:25-17:10 761 not included in Flemish viewing figures 750

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650 BRT1 14:25-17:14 17:02 600 223 220 210

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Rating300 in 000 110 100 250 90 Rating in 000 80 200 70 150 60 50 100 40 30 50 20 10 0 0

14:10 14:20 14:30 14:40 14:50 15:00 15:10 15:20 15:30 15:40 15:50 16:00 16:10 16:20 16:30 16:40 16:50 17:00 17:10 17:20 17:30 14:10 14:20 14:30 14:40 14:50 15:00 15:10 15:20 15:30 15:40 15:50 16:00 16:10 16:20 16:30 16:40 16:50 17:00 17:10 17:20 Date: 26-02-11 Date: 26-02-11 Because only resident viewership is measured , reported viewership is always an underestimation of the real number of people watching the race (impact of international viewers is ignored). Introduction - Cycling on TV – Literature - Model - Results – Future research METHODOLOGY 4 classes of independent variables were determined, based on the model for viewership of live sport TV broadcasts by Johnsen & Solvoll (2007)

Viewing figures for sport

Scheduling specific variables Viewer specific variables

e.g. game characteristics e.g. team/player identification Introduction - Cycling on TV – Literature - Model - Results – Future research METHODOLOGY 4 classes of independent variables were determined, based on the model for viewership of live sport TV broadcasts by Johnsen & Solvoll (2007)

Viewing figures for sport

Sport-related variables e.g. outcome uncertainty

Non sport-related e.g. subsitute activities variables Introduction - Cycling on TV – Literature - Model - Results – Future research METHODOLOGY 4 classes of independent variables were determined, based on the model for viewership of live sport TV broadcasts by Johnsen & Solvoll (2007)

Viewing figures for sport

Scheduling specific variables Viewer specific variables Sport-related variables • Competition schedule • Outcome uncertainty • Game characteristics • Team / player identification • Aesthetics / achievement Non • Substitute activities sport-related • Viewing date & time • Cheating variables • Game place • Group / family affiliation Introduction - Cycling on TV – Literature - Model - Results – Future research

TdF “TRANSFORMATION” OF THE MODEL

Viewing figures for Tour de France stages

Scheduling specific variables Viewer specific variables

Sport-related variables • Stage type • Outcome uncertainty • Patriotism

Non sport-related • Stage date • Substitute activities variables • Stage place • Doping Introduction - Cycling on TV – Literature - Model - Results – Future research

INDEPENDENT VARIABLES

• Stage type impact – The Tour de France consists of different types of stages: • Flat stages  almost no impact on the overall classification • Mountain stages  spectacular and very important to the overall classification • Time trial stages (individual or team)  also important to the overall classification, but less interesting to watch (?) – Analysis of the most and the least watched stages to see what stage type characteristics are relevant Introduction - Cycling on TV – Literature - Model - Results – Future research HIGHEST & LOWEST AVERAGE TV AUDIENCES (up to 2010)

Date Stage Viewers Type of stage

01. 22/07/2010 Stage 17 Pau > 816.066 Mountain stage with top finish

02. 11/07/2010 Stage 8 Station des Rousses > Morzine 801.965 Mountain stage with top finish

03. 21/07/2003 Stage 15 Bagnères-de-Bigorre > Luz-Ardiden 785.986 Mountain stage with top finish

04. 16/07/2000 Stage 15 Briançon > Courchevel 785.528 Mountain stage with top finish

05. 13/07/2003 Stage 8 Sallanches > Alpe-d’Huez 735.163 Mountain stage with top finish

06. 21/07/2001 Stage 13 Foix > St-Lary-Soulan 731.054 Mountain stage with top finish 07. 15/07/2000 Stage 14 Draguignan > Briançon 715.373 Mountain stage

08. 23/07/2007 Stage 15 Foix > Loudenvielle 713.597 Mountain stage

09. 18/07/2006 Stage 15 Gap > Alpe-d’Huez 708.182 Mountain stage with top finish 10. 25/07/2009 Stage 20 Montélimar > Mont Ventoux 704.669 Mountain stage with top finish

287. 02/07/2005 Stage 1 Fromentine > Noirmoutier-en-l’île 252.255

288. 06/07/2003 Stage 1 St.-Denis > Meaux 251.894 Flat stage

289. 07/07/2004 Stage 4 Cambrai > Arras 245.155 Team time trial

290. 10/07/2002 Stage 4 Épernay > Château-Thierry 240.356 Team time trial

291. 08/07/2002 Stage 2 Luxembourg > Saarbrücken 236.861 Flat stage

292. 05/07/2004 Stage 2 Charleroi > Namur 235.518 Flat stage

293. 09/07/2003 Stage 4 Joinville > St.-Dizier 232.018 Team time trial

294. 08/07/2006 Stage 7 St.-Grégoire > Rennes 231.702 Individual time trial

295. 08/07/1997 Stage 3 Vire > Plumelec 227.585 Flat stage

296. 01/07/2006 Prologue Strasbourg 215.488 Individual time trial Introduction - Cycling on TV – Literature - Model - Results – Future research

HIGHEST PEAK TV AUDIENCES (up to 2010)

Date Stage Viewers Type of stage

01. 24/07/2005 Stage 21 Corbeil-Essonnes > Paris 1.264.183 Final stage

02. 29/07/2007 Stage 20 Marcoussis > Paris 1.240.506 Final stage

03. 22/07/2010 Stage 17 Pau > Col du Tourmalet 1.205.947 Mountain stage with top finish 04. 25/07/2009 Stage 20 Montélimar > Mont -Ventoux 1.135.687 Mountain stage with top finish

05. 25/07/2010 Stage 20 Longjumeau > Paris 1.126.344 Final stage

06. 11/07/2010 Stage 8 Station des Rousses > Morzine 1.125.280 Mountain stage with top finish 07. 10/07/2007 Stage 3 Waregem > Compiègne 1.121.872 Flat stage

08. 21/07/2003 Stage 15 Bagnères-de-Bigorre > Luz-Ardiden 1.101.249 Mountain stage with top finish

09. 16/07/2000 Stage 15 Briançon > Courchevel 1.094.023 Mountain stage with top finish 10. 23/07/2007 Stage 15 Foix > Loudenvielle 1.062.623 Mountain stage Introduction - Cycling on TV – Literature - Model - Results – Future research INDEPENDENT VARIABLES

• Stage date – The stage date and day are of importance: • Tour de France broadcasts are in the afternoon  greater viewing potential during weekends than on weekdays • Opening and closing stage: viewer effects? • Greater viewing potential on the Belgian (July 21) and the Flemish national holiday (July 11) because more people are at home Introduction - Cycling on TV – Literature - Model - Results – Future research INDEPENDENT VARIABLES

• Stage date – The stage date and day are of importance: • Tour de France broadcasts are in the afternoon  greater viewing potential during weekends than on weekdays • Opening and closing stage: viewer effects? • Greater viewing potential on the Belgian (July 21) and the Flemish national holiday (July 11) because more people are at home

• The stage place – An analysis of the best and least watched stages also showed an increased viewer interest in stages held on Belgian territory, especially for stages crossing the Northern Flemish region of Belgium. Introduction - Cycling on TV – Literature - Model - Results – Future research INDEPENDENT VARIABLES

• Outcome uncertainty variables were the most difficult ones to determine because of the special nature of the cycling sport. In the final model, the following 3 variables were used: – a dummy variable for “stage interest” (stage uncertainty): third week mountain or time trial stages with (at the start) less than 90 seconds of difference in the GC between top Tour contenders – a variable for “dominance” (Tour uncertainty): number of this year’s TdF stage wins by last year’s TdF winner – a dummy variable for the post Armstrong effect (multi-year uncertainty): all stages in post 2005 TdF Introduction - Cycling on TV – Literature - Model - Results – Future research INDEPENDENT VARIABLES

• Outcome uncertainty variables were the most difficult ones to determine because of the special nature of the cycling sport. In the final model, the following 3 variables were used: – a dummy variable for “stage interest” (stage uncertainty): third week mountain or time trial stages with (at the start) less than 90 seconds of difference in the GC between top Tour contenders – a variable for “dominance” (Tour uncertainty): number of this year’s TdF stage wins by last year’s TdF winner – a dummy variable for the post Armstrong effect (multi-year uncertainty): all stages in post 2005 TdF

• Patriotism was modelled with 3 variables: – a variable counting the number of Belgian riders (still) in the race – a dummy variable measuring the success of Belgian riders (defined as wearing a leader jersey or in competition for a top 10 position ) – a dummy variable for the presence of superstar effects (Boonen-effect) Introduction - Cycling on TV – Literature - Model - Results – Future research INDEPENDENT VARIABLES

As the Tour de France is being shown on a public TV channel, viewing is free and only the opportunity cost of time is relevant when thinking about substitute activities . I considered two possible alternatives for spending time:

• Tour de France viewing could be rivalled by substitute TV programs (sport or other):  only a Wimbledon-effect was found Introduction - Cycling on TV – Literature - Model - Results – Future research INDEPENDENT VARIABLES

As the Tour de France is being shown on a public TV channel, viewing is free and only the opportunity cost of time is relevant when thinking about substitute activities . I considered two possible alternatives for spending time:

• Tour de France viewing could be rivalled by substitute TV programs (sport or other):  only a Wimbledon-effect was found

• Tour de France viewing could be rivalled by the preference for other activities. This is assumed to be strongly related to weather conditions:  If it rains , people stay inside and watch TV  If it is cold , people stay inside and watch TV  If it is warm , people go outside (or not?) Introduction - Cycling on TV – Literature - Model - Results – Future research Temperature vs. TV audience

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INDEPENDENT VARIABLES

• The impact of doping was modelled in a double way. – Short-term doping impact: a dummy variable was included marking each first stage following the release of doping-news in connection with a Tour de France participant (= one-day effect). Introduction - Cycling on TV – Literature - Model - Results – Future research

INDEPENDENT VARIABLES

• The impact of doping was modelled in a double way. – Short-term doping impact: a dummy variable was included marking each first stage following the release of doping-news in connection with a Tour de France participant (= one-day effect). – Long -term doping impact: a dummy variable was included for all stages in the years following a Tour de France that heavily suffered from doping problems, i.e. the years following the 1997 (Fuesta), 2006 (Puerto & Landis) and 2007 (Rasmussen & Vinokourov) Tours. Introduction - Cycling on TV – Literature - Model - Results – Future research

INDEPENDENT VARIABLES

• The impact of doping was modelled in a double way. – Short-term doping impact: a dummy variable was included marking each first stage following the release of doping-news in connection with a Tour de France participant (= one-day effect). – Long -term doping impact: a dummy variable was included for all stages in the years following a Tour de France that heavily suffered from doping problems, i.e. the years following the 1997 (Fuesta), 2006 (Puerto & Landis) and 2007 (Rasmussen & Vinokourov) Tours.

• Remark: Short-term doping impact was also measured for two- or three- day effects, but those dummy’s proved to be insignifcant. Introduction - Cycling on TV – Literature - Model - Results – Future research Results: Isolated explanatory power of the classes of variables

Viewing figures for Tour de France stages

Scheduling specific variables Viewer specific variables 21,4% Sport-related • Outcome uncertainty variables • Stage type 44.0 % • Patriotism 4,8%

Non 11,0% sport-related • Stage date 30.8% • Substitute activities variables • Stage place • Doping 0,4% Introduction - Cycling on TV – Literature - Model - Results – Future research EMPIRICAL RESULTS: explanatory power

• Scheduling variables explain 59% of the viewership variation. The stage type is a decisive factor, but also the day and date are of importance.

• Consequently, already in November when the stage profile of the upcoming TdF is announced, it is possible to predict rather accurately the viewing figures for the TdF which at that moment is still 8 months away.

• Viewer specific variables explain another 16% of variation in viewership, giving the model 75% explanatory power. Introduction - Cycling on TV – Literature - Model - Results – Future research Empirical results: the importance of stage types

Average audience Peak audience 2 2 (N = 317, R A = 0.75) (N = 317, R A = 0.74) Coefficient t-statistic coefficient t-statistic

(Constant) 294,657 13.63*** 580,674 18.10***

Stage type variables (dummy’s) High mountain stage 117,770 8.83*** 107,854 5.45*** Low mountain stage 56,033 2.35** * 67,269 1.90* ** Stagefinish on mountain top 32,231 2.29** * 65,798 3.15*** Individual time trial stage -36,562 -2.37** * -90,507 -3.96*** Team time trial stage -82,810 -3.19*** -177,616 -4.61*** Mountain time trial stage 3,507 0.07 *** 19,628 0.27 *** Introduction - Cycling on TV – Literature - Model - Results – Future research Empirical results: the importance of stage date & stage location

Stage date & stage location variables (dummy’s) July 21 holiday 102,180 4.28*** 142,182 4.01*** July 11 holiday 33,952 1.42 *** 61,561 1,73* ** Opening stage 6,058 0.27 *** -24,101 -0.71 *** Final stage 204,421 10.17*** 297,011 9.96*** Weekday second week 38,826 3.09*** 22,538 1.21 *** Weekday third week 53,415 3.78*** 15,205 0.73 *** First Sunday 59,034 3.14*** 65,742 2.36** * Mid Saturdays 72,324 5.02*** 82,960 3.88*** Mid Sundays 130,235 8.37*** 125,037 5.41*** Belgian North passage 142,613 5.09*** 229,589 5.52*** Introduction - Cycling on TV – Literature - Model - Results – Future research

Empirical results: the importance of outcome uncertainty

Outcome uncertainty variables Dominance -5,498 -1.19 *** 3,792 0.55 *** (number of this year’s TdF stage wins by last year’s TdF winner) Suspense stages 68,263 4.13*** 99,693 4.06*** (dummy for final week mountain stages and time trials stages with less than 90 seconds of difference between top Tour contenders) Post Armstrong period 43,623 4.48*** 136,704 9.46*** (dummy for post 2005 Tour de Frances) Introduction - Cycling on TV – Literature - Model - Results – Future research

Empirical results: the importance of patriotism

Patriotism variables Number of Belgians (still) in 2,606 1.53 *** -3,776 -1.49 *** race

Belgian success 43,366 4.02*** 86,989 5.43*** (dummy for stages with a Belgian rider wearing a leadership jersey or in competition for an overall top 10 placing) Boonen absent 2008 -55,561 -2.86*** -95,034 -3.29*** (dummy) Introduction - Cycling on TV – Literature - Model - Results – Future research Empirical results: the importance of substitute activities

Variables related to substitute activities Rain 47,479 6.25*** 59,849 5.31*** (dummy)

Temperature 70,633 4.01*** 51,022 1.95* ** (dummy for stages on days with temperatures at least 2 standard deviations from the average) Wimbledon -143,978 -3.71*** -103,244 -1.79* ** (dummy for stages on days when Belgian tennis players were playing in Wimbledon) Introduction - Cycling on TV – Literature - Model - Results – Future research Empirical results: the importance of doping

Doping-related variables Short-term doping impact -14,829 -1.26 *** -39,186 -2.24** * (dummy for the first stages following the release of doping -news with respect to a Tour de France participant) Long-term doping impact -20,215 -1.66* ** -10,426 -0.58 *** (dummy for all stages in the years following a Tour de France that heavily suffered from doping problems, i.e. the 1997 (Fuesta), 2006 (Puerto & Landis) and 2007 (Rasmussen & Vinokourov) Tours) Introduction - Cycling on TV – Literature - Model - Results – Future research SO WHAT ABOUT MY PREDICTION?

Average viewing figures: 11% underestimation (526,000 versus 586,000), but first 10 stages are really accurate.

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Average viewing figures: 11% underestimation (526,000 versus 586,000), but first 10 stages are really accurate. Peak viewing figures: 2,5% underestimation (895,000 versus 920,000)

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FUTURE RESEARCH OPPORTUNITIES

• Further refinement of the model: – Better outcome uncertainty variables ? – Impact of long broadcasts? • Comparative analysis: – with Tour de France viewing data from other countries – with viewing data from the other cycling grand Tours – average versus peak audience • Analysis of intrastage viewing patterns • The search for an “ideal” (i.e. viewer-maximisation) stage profile • Analysis of spectator motives (questionnaire analysis) Introduction - Cycling on TV – Literature - Model - Results – Future research VIEWING DATA COLLECTED SO FAR

Flanders Wallonia The U.S. U.K. Spain Italy Norway France Australia Germany (Belgium (Belgium Netherlands North) South) 1997 Stage level

1998 Stage level Global

1999 Stage level Global

2000 Stage level Global

2001 Stage level Global

2002 Stage level Global Global

2003 Stage level Global Global Global

2004 Stage level Global Global Global

2005 Stage level Global Global Global

2006 Stage level Global Global Global

2007 Stage level Stage level Global Global Global

2008 Stage level Global Global Stage level Global

2009 Stage level Global Stage level Global (Stage level)

2010 Stage level Global Stage level Global Global Global Global Global Global Stage level Global

2011 Stage level Global Stage level Global Stage level Global Global Global Global Stage level Global