THE IMPACT OF FORMULA ONE RACE VICTORIES ON TEAM MAIN SPONSOR'S STOCK MARKET

RETURNS: AN EVENT STUDY.

By

Marc Haakma2184869

A thesis submitted to the Faculty of ECONOMICS AND BUSINESS

in partial fulfilment of the requirements for the degree of BACHELOR OF SCIENCE IN BUSINESS ECONOMICS

UNIVERSITY OF GRONINGEN

Thesis supervisor: prof. dr. L.J.R. Scholtens

AbstractThe purpose of this study is to investigate the effect of Formula One race victories by racing teams on

the stock market returns of the main sponsor of those teams. To investigate this, an event study is

conducted, covering 11 main sponsors over 212 races during 1998-2013. In general, it can be

concluded that Formula One race victories have a positive, insignificant impact on the stock market

performance of the main sponsor. However, the conducted sensitivity analyses show positive

significant effects for main sponsors of the Ferrari team, for races held outside of Europe and for

tobacco company main sponsors.

Words used: 4379 June 2014

Introduction

Formula One is one of the most popular motorsport brands in the world, yielding a global

television audience of 450 million viewers during the 2013 season.1 Primarily, commercial

sponsorship was restricted in the sport, and cars would display their national colours instead. As

expenses increased, automobile related company sponsors pulled out of the sport (Foster, 2013). In

1968, sponsorship restrictions were lifted, which caused commercial sponsorship to become the

backbone of the sport (Peters, 2012).

Pope (1998) defines sponsorship as "the provision of resources by an organisation; the

sponsor, directly to an individual, authority or body; the sponsee, to enable the latter to pursue some

activity in return for benefits contemplated in terms of the sponsor’s promotion strategy, and which

can be expressed in terms of corporate, marketing, or media objectives." This definition clearly

demonstrates that both the sponsor and sponsee might benefit from sponsorship.

Based on the abovementioned sponsorship definition, the main sponsor of a Formula One

team could be defined as the sponsor that is primarily responsible for the resource provision to a

particular Formula One team. Each team enters two cars per race, which have to be presented in

substantially the same sponsorship layout 2, which, inter alia, includes a clear presentation of the logo

of the team's main sponsor. A victory in a Formula One race could therefore generate positive

publicity for the team's main sponsor, as its brand image is being linked to success. Consequently, this

could result in higher sales and thus an increase in future cash flows (Cornwell et al., 2001). Based on

this line of reasoning, investors can re-evaluate the company in a positive manner, as an expected

increase in future cash flows increases the company's value through an increase in the stock price,

which reflects the time- and risk-discounted present value of all future cash flows (Bhagat et al.,

2002). Moreover, an increase in unsystematic risk occurs, due to the increase in return that is caused

by an event that does not affect the market as a whole.

According to the semi-strong form of the efficient market hypothesis, current market prices

fully reflect all publicly available information (Fama, 1970). Therefore, only an unanticipated event

can cause a change in the price of a stock (Horsky and Swyngedouw, 1987).

As the outcome of a Formula One race cannot be predicted with certainty, it is considered an

unanticipated event for the stock market. However, due to team specific performance factors such as

driver talent and car specifications (Eichenberger and Stadelmann, 2009), a certain outcome could be

expected. A practical estimator for expected race outcome can be derived from the qualification race

that takes place on the day before the actual race on Sunday, which takes into account these variables.

____________________________________1 Source: The F1 Times (www.f1times.co.uk/news/display/0847)2 The 2013 FIA Formula One Sporting Regulations 2013 (www.argent.fia.com)

2

As pole position starters account for approximately 55% of the wins during the research

period, it can be stated that a pole position victory can be regarded as expected, and a non-pole

position victory as unexpected.3 In the upcoming sensitivity analysis section, this assumption will be

tested.

To analyse the impact of Formula One race victories by a team on the stock market returns of

the main sponsor of the respective team, an event study is conducted. In light of this research problem,

the following research hypotheses are formulated:

H0: No significant positive abnormal stock returns occur for the main sponsor after a race victory;

Ha: Significant positive abnormal stock returns occur for the main sponsor after a race victory.

On the basis of the research findings, investors could decide whether or not to anticipate on

the magnitude of potential value enhancing observed abnormal returns.

Literature

Prior research with regard to the relationship between stock market returns and performance in

motorsport events can be described as focused and insufficiently conclusive. Cornwell et al. (2001)

analyse 28 winning sponsors and 232 non-winning sponsors over 28 Indianapolis 500 races, from

1963 to 1998. They find no evidence that winning the Indianapolis 500 leads to statistically significant

increases of sponsoring company's share prices. In contrast, a statistically significant positive

abnormal return (8.24%) is found for one sponsor that had a clear link to the consumer automotive

industry.

Mahar et al. (2005) find no statistically significant link between race and stock performance,

by analysing the overall sample of 831 companies that were the main sponsor of each car for the 2002-

2003 NASCAR season. However, a weak but significant relationship is found between race and stock

performance for business to consumer companies (0.041%) and for companies in the automotive

industry (0.040%), the latter result being in conformance with Cornwell et al. (2001).

Fidahic and Schredelseker (2011) focus on the car manufacturers of the teams rather than team

main sponsors. By analysing 53 races during the 2005-2007 seasons, they find that for the three

analysed car manufacturers, race victories yield statistically insignificant abnormal returns.

____________________________________3 Based on information from the data set, it can be concluded that during 1998-2013, 157 of the 283 races were

won by pole position qualifiers.

3

A study conducted by Dussold and Sullivan (2001) examines 39 companies that were the main

sponsor of racing teams that took part in the 34 races of the NASCAR Winston Cup 2001 season.

They find that this group of companies realised statistically significant positive abnormal returns

(0.002%) on the trading day after the races in which their sponsored team appeared. While

participation is found to have a significant effect, winning a race is not.

To pursue relevant results, which optimally reflect the frequently changing Formula One

regulations, 212 Formula One race victories during 1998-2013 are analysed, a more recent period of

analysis in comparison with abovementioned prior research. Most of this research is conducted on

popular motorsport events in the United States, such as the NASCAR series and the Indianapolis 500.

In comparison, the results in this paper are applicable in a more general setting, due to its greater

scope, as Formula One is a worldwide phenomenon. This study focuses on non-automotive sponsoring

exclusively, and therefore complements Fidahic and Schredelseker (2011), who focus on the teams'

car manufacturers instead.

Data

The analysed period starts in 1998, as this marks the end of the successful historical teams

Renault and Williams, and the re-emergence of Ferrari and McLaren, which are still main competitors

as of today.4 To obtain optimal recent results, 2013 marks the last year of the analysed period, as this

is the most recently completed Formula One season. In this period, 283 Formula One races were held.

The selection criteria used to arrive at the final sample, are as follows:

The team must have a main sponsor;

The main sponsor must be publicly traded;

Total return information of the particular stock must be available on DataStream.

The final sample consists of 212 races. Victories in these races are spread amongst eight teams, which

were sponsored by 11 main sponsors in total during 1998-2013, as Table 1 illustrates.

____________________________________4 Source: www.race-database.com

4

The data set constructed from the abovementioned motivation and requirements, consists of

qualification and race results for each race 5, more specific race details (team, circuit and event date) 6

and main sponsor names.7 Stock price information for both individual stocks and the benchmark index

is derived from DataStream. In addition, DataStream is used to link sponsor and company names, to

allow company and industry analysis. For both the benchmark and the individual stocks, a total return

index is used, reflecting the reinvestment of dividends.

Methodology

To examine the effect of a victory in a Formula One race on the stock market return of the

winning team's main sponsor, event study methodology is used. Brown and Warner (1980) state that

the abnormal return for a given security in any time period t is defined as the difference between its ex

ante expected return and its ex post observed return.

____________________________________5 Source: www.formula1.com6 Source: www.statsf1.com7 Source: www.allf1.info

5

Main sponsor company Race victories Sponsored teamAltria Group 88 FerrariBritish American Tobacco 1 HondaCompaq Computers 5 WilliamsHewlett-Packard 5 WilliamsHSBC HDG. 1 StewartImperial Tobacco GP. 41 McLarenING Groep 2 RenaultJapan Tobacco 18 RenaultPetronas Dagangan 5 Mercedes, BMW SauberPhilip Morris INTL. 12 FerrariVodafone Group 34 McLaren

Table 1: Breakdown of the sample of main sponsors and the victories achieved by their respective sponsored teams.

The ex post, continuously compounded, observed return for each individual security i at time

t, Rit, is calculated as follows:

Rit = ln (Pit / Pit-1) (1)

where

Pit is the security price at time t;

Pit-1 is the security price at time t-1.

MacKinlay (1997) uses the market model to generate ex ante expected returns. This model

will also be applied in this paper, as it provides the best estimation by taking into account the specific

alphas and betas of the stocks in relation to the market proxy, the benchmark (Anderson-Weir, 2010).

Alpha is the excess stock return for a particular sponsor, in comparison with this benchmark. Beta is a

measure of volatility, measuring how much a particular sponsor's stock return changes when the

benchmark return increases by 1%. The S&P 500 is used as the benchmark in this paper, including the

500 largest companies in the U.S. by market capitalisation, covering ten industries and thereby

approximately 80% of the US economy.8 This wide coverage is preferred, as companies from different

industries are examined in this paper. Moreover, as all companies in the sample are multinationals, its

focus on large companies is a suiting one.

To increase the power of the event study, a fairly large estimation window is used, as this

yields a large sample of returns over which the parameters in the model can be estimated. Based on a

364 day year, the subtraction of 104 weekend days and an estimated ten stock market holidays 9

consequently leads to the estimation period of 250 days; [-250,-1]. Similar estimation windows are

used by MacKinlay (1997) and Campbell et al. (2010). As Formula One races are held on Sundays, the

day after the race is marked as the event window; [0], and therefore labelled as "day 0", designating

the first trading day after the event. It is assumed that this is a sufficient time period for the market to

capture and process the event information, as the results are made public through multiple means of

modern communication as soon as the race has finished. In conjunction with the fact that potential

effects of the race results cannot be anticipated on by investors, cumulative average abnormal return

calculations are deemed to be unnecessary. Dussold and Sullivan (2003) suggest using a small event

window, to minimise the likelihood of confounding events occurring in the event window, thus

increasing the power of the event study.

____________________________________8 Source: www.us.spindices.com 9 Source: www.nyx.com/holidays-and-hours/nyse

6

The ex ante expected return for each individual security i at time t, Rit, according to the market model

is calculated as follows:

Rit = i + iRmt + it (2)

where

Rmt is the observed return for the market index at time t;

it is the zero mean disturbance term;

❑̂i =

∑−1

−250

( R¿−μ̂ i )(Rmt¿−μ̂m)

∑−1

−250

(Rmt−¿ μ̂m)² ¿¿ (3)

❑̂i = μ̂i−❑̂i μ̂m (4)

The ❑̂i and ❑̂i parameters of the model are estimated by carrying out an ordinary least squares

regression, based on the observed [-250,-1] estimation window input for Rmt and Rit.

Based on the abovementioned return formulas, the model dictates the following formula for

abnormal returns:

AR it = Rit - ❑̂i - ❑̂iRmt (5)

Based on this methodology, average abnormal returns, AR t, are computed:

ARt = 1N ∑

i=1

N

AR¿ (6)

In addition to this general result, sensitivity analyses are conducted to compare subgroups within the

total sample. For the sensitivity analyses, the null-hypothesis being tested is that the abnormal returns

of the two groups within the analysis do not significantly differ.

The first sensitivity analysis is based on the distinction between expected and unexpected race

results. As stated before, qualification results are a practical estimator for the actual race outcome, due

to the high percentage pole position wins in the analysed sample. Cornwell et al. (2001) also includes

the winner's qualifying speed as a measure of the level of the market's pre-race expectations of victory.

Taking into account this distinction, the first sensitivity analysis compares the 117 unexpected and 95

expected victories, to analyse potential differences in main sponsor returns.

7

Being the most successful team in Formula One history, also winning one hundred races out of

the total sample of 212 races, Ferrari could be considered the long-time showpiece of the sport. To test

whether returns of Ferrari's main sponsors positively differ from main sponsors of other teams, a

second sensitivity analysis is conducted.

Tobacco companies play a significant role in Formula One, with five out of ten main sponsors

in the sample accounting for 160 of the 212 observed victories. However, as tobacco sponsorship

becomes less visible and more restricted due to newly implemented policies within many jurisdictions

(Dewhirst and Hunter, 2002), it could be expected that tobacco sponsor returns suffer accordingly. To

test whether tobacco main sponsor returns do in fact differ negatively from non-tobacco main

sponsors, a sensitivity analysis is conducted.

Formula One was founded in Europe, and with 120 out of 212 races in the sample being held

there, it could still be considered the sport's main base. However, the sport's geographical scope

expanded significantly during the researched period, and an increasing number of Grand Prix are held

in other continents. To analyse if the main sponsor returns obtained through victories outside of

Europe positively differ from those obtained in Europe, due to potentially saturated European markets,

a fourth sensitivity analysis is conducted on the basis of this geographical distinction.

To test the hypotheses and analyse the significance of the abnormal returns of both the total

sample and the groups within the sensitivity analyses, a parametric and a non-parametric significance

test are used. As this research focuses exclusively on positive abnormal returns, these tests are one-

sided. The abovementioned parametric significance test is also used to analyse the significance of the

difference between two groups within a given sensitivity analysis.

For the parametric test, the student t-test is used. The total sample consists of 212

observations, each consisting of an expected and an observed return. For each observation, these two

values are identified as a pair. To test the null-hypothesis, the following test statistic, t, is used:

t = x−μ0

s /√n(7)

where

x is the sample average of the abnormal returns;

μ0 is the average of the abnormal return, stated by the null-hypothesis;

s is the sample standard deviation of the abnormal returns;

n is the number of observations.

Based on this t-statistic, a p-value is derived to test for significance at the = 1%, 5% and 10% level.

If this value is below a particular statistical significance threshold, the null-hypothesis is rejected in

favour of the alternative hypothesis.

8

The non-parametric Wilcoxon signed-rank test is used, based on the same data set

characteristics as for the student t-test. However, Brown and Warner (1980) state that parametric tests

are based on the assumption that the sample is normally distributed. According to MacKinlay (1997),

non-parametric approaches can therefore be used when such an assumption cannot be assumed.

The sign test used by Campbell et al. (2010) only takes the sign of the abnormal return into account in

computing the test statistic, while the Wilcoxon signed-rank test includes both the magnitude and sign

(Brown and Warner, 1980). It could therefore be argued, that the latter is a more powerful alternative.

The procedure for the Wilcoxon signed-rank test can be summarised as follows. First, the difference

between the observed and expected returns is calculated. A rank is then assigned to the absolute value

of this difference. Based on the original sign of the difference, both the positive and negative sign

differences are summed up, and the smaller of these two values, Ws, is then included in the test

statistic, Z:

Z = W s−¿

n (n+1)4

√ n (n+1 )(2n+1)24

¿ (8)

Based on this Z-statistic, a p-value is derived and a conclusion can be drawn in the same fashion as for

the student t-test.

Results

Table 2 shows a number of important statistical characteristics of the data set. Its negative

skewness (-0.3113) indicates that the distribution is slightly skewed to the left. Moreover, the high

kurtosis (15.4294) shows that the distribution is strongly leptokurtic, indicating that this distribution

does not represent a normal distribution (Brown and Warner, 1980). These two deviations lead to a

high Jarque-Bera statistic (1368.0945), substantiating this non-normality statement.

Observations 212Average 0.0732%Median 0.0000%Minimum -12.2951%Maximum 12.7671%Standard Deviation 0.0199Kurtosis 15.4294Skewness -0.3114Jarque-Bera 1368.0945

9

Table 2: Descriptive statistics of the abnormal returns in the estimation window [-250,-1]; DF= 211.

Table 3 shows positive abnormal returns (0.0732%) for the 212 observations in the event

window. However, based on the findings of the conducted statistical tests, this result is found to be

insignificant at a significance level of 10% or lower. Therefore, the null-hypothesis, that no significant

positive abnormal stock returns occur for the main sponsor after a race victory, should be retained.

Table 3: Significance of observed main sponsor abnormal returns in event window [0], DF= 211.

AR (%) Student t-test;p-value

Wilcoxon signed-rank test;p-value

     Victory (N = 212) 0.0732 0.2961 0.1764

The result tables of the sensitivity analyses are included in the Appendix at the end of this

paper. Table 4 shows the results of the first sensitivity analysis, in which results are split into expected

and unexpected race victories. These expectations are based on qualification race results, with a win

from pole position leading to an expected victory, and vice versa. It can be concluded that both

expected and unexpected victories realise insignificant abnormal returns (-0.0351% and 0.1984%) and

that the difference between the two groups is also insignificant. Therefore, the null-hypothesis should

be retained.

Table 5 shows that a victory by Ferrari leads to positive significant abnormal returns

(0.1906%) at the 5% significance level for the Wilcoxon signed-rank test, while a victory by a

different team yields negative insignificant average abnormal returns (-0.0317%) for both tests. The

abnormal returns of the two groups do not significantly differ, therefore, the null-hypothesis should be

retained.

Table 6 shows that a victory for a tobacco main sponsor yields marginally significant average

abnormal returns (0.1352%) at the 10% significance level, according to the Wilcoxon signed-rank test.

Negative insignificant abnormal returns (-0.1203%) are observed for the non-tobacco main sponsor

group. The null-hypothesis should be retained, as there is an insignificant difference in abnormal

returns between the two groups.

The fourth sensitivity analysis splits the sample into two groups, based on whether the race is

held in Europe or not. Table 7 shows positive marginally significant abnormal returns for victories

achieved outside of Europe (0.2708%) at the 10% significance level, according to the Wilcoxon

signed-rank test. Insignificant negative abnormal returns were found for victories achieved in Europe

(-0.0783%) and victories achieved in Europe (-0.0783%). The null-hypothesis should be retained, as

the difference in abnormal returns between the two groups is insignificant.

10

Conclusion

It can be argued that a Formula One race victory by a team could have a positive effect on the

stock market returns of the team's main sponsor, due to the success being linked to the image of the

main sponsor, therefore generating positive future cash flows. In turn, investors can re-evaluate the

company in a positive manner, as an expected increase in future cash flows increases the company's

value through an increase in the stock price. To test this line of reasoning, an event study was

conducted, covering 11 main sponsors over 212 races during 1998-2013.

The statistical tests conducted in this study, the student t-test and the Wilcoxon signed-rank

test, found no significant average abnormal returns. On the basis of this result, the null-hypothesis

should therefore be retained, as the impact of Formula One race victories by a team on the stock

market returns of its main sponsor is insignificant. This result is in line with the general findings of

Cornwell et al. (2001), Dussold and Sullivan (2001) and Mahar et al. (2005), who also were unable to

find a significant link between race victories and stock performance of the main sponsor. However, all

three studies find significant results for particular subgroups. As these results do not overlap with the

conducted sensitivity analyses in this paper, they are beyond the scope of this paper and will therefore

not be discussed. In addition, the general result from this paper is in line with the findings of Fidahic

and Schredelseker (2011). However, as a sample size of only 53 races is used in their event study, they

suggest that this result should be interpreted with care.

Based on the descriptive statistics regarding the data set, it was concluded that the average

abnormal returns in the event window are not normally distributed in order for parametric tests to

maintain their power advantage over non-parametric tests. As a result, this study assigns more value to

the Wilcoxon signed-rank test results. In contrast to the student t-test, the Wilcoxon signed-rank test

found significant to marginally significant results for particular groups within the conducted sensitivity

analyses.

Significant positive abnormal returns were found for the main sponsors of Ferrari, the value

enhancing effect due to accrued status could serve as a potential explanation for this. However, this

effect is distorted by the result from the third sensitivity analysis; in which marginally significant

results were found for tobacco sponsors. As Ferrari was sponsored by two tobacco companies during

the research period, it is not clear what the role of being a sponsor of Ferrari or being a tobacco

sponsor is in this effect. Nonetheless, the difference between Ferrari and non-Ferrari and the difference

between tobacco and non-tobacco is insignificant. Therefore, the null-hypotheses should be retained;

the abnormal returns of the subsamples within these groups do not significantly differ.

11

The fourth sensitivity analysis observed marginally significant results for races held outside of

Europe. A possible explanation for this is that Formula One is gaining ground in those countries

outside of Europe, where hosting Formula One races is not a well established phenomenon yet. As a

result, greater returns could be realised, due to these new markets. Adversely, the difference in

abnormal returns between the races in Europe and outside of Europe is insignificant, and therefore the

null-hypothesis should be retained.

This paper presents information that could help investors decide whether or not to anticipate

on the magnitude of potential observed abnormal returns that could occur for a main sponsor of a

Formula One team, due to its team winning a race.

Further research could elaborate on this research by increasing the power of the event study

through an increase of the sample size. In addition to computing the abnormal returns for the event

window [0], a larger event window could be used, analysing potential effects on other days than the

event day. In this case, cumulative abnormal returns should be computed. Furthermore, regarding the

overlapping results of the second and third sensitivity analyses, as Ferrari's main sponsors are also

tobacco sponsors, further research could be conducted in an effort to identify the individual effects of

Ferrari sponsorship and tobacco sponsorship.

12

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13

Appendix

Table 3: Significance of observed main sponsor abnormal returns in event window [0], DF= 211.

AR (%) Student t-test;p-value

Wilcoxon signed-rank test;p-value

     Victory (N = 212) 0.0732 0.2961 0.1764

* Significant at the = 1% level;

** Significant at the = 5% level;

*** Significant at the = 10% level.

Table 4: Significance of observed main sponsor abnormal returns in event window [0], on the basis of whether the race victory was expected or not.

   AR (%) Student t-test;

p-valueWilcoxon signed-rank

test; p-value     

Group 1: Expected victory (N = 95) -0.0351 0.4082 0.4822Group 2: Unexpected victory (N = 117) 0.1611 0.2275 0.1042

Difference between groups Student t-test; p-value

0.0002 0.2278

Table 5: Significance of observed main sponsor abnormal returns in event window [0], on the basis of Formula One team: Ferrari versus the other teams.

       AR (%) Student t-test;

p-valueWilcoxon signed-rank

test; p-value     

Group 1: Victory for Ferrari (N = 100) 0.1906 0.1196 0.0457** Group 2: Victory for other team (N = 112) -0.0317 0.4414 0.4286

Difference between groups Student t-test; p-value

0.0003 0.2041

14

Table 6: Significance of observed main sponsor abnormal returns in event window [0], on the basis of sponsor industry: victories for tobacco sponsors versus victories for non-tobacco sponsors.

       AR (%) Student t-test;

p-valueWilcoxon signed-rank

test;p-value

     Group 1: Victory for tobacco sponsors (N = 160)

0.1352 0.1326 0.0974***

Group 2: Victory for non- tobacco sponsors (N = 52)

-0.1203 0.3860 0.3889

Difference between groups Student t-test; p-value

0.0003 0.2769

Table 7: Significance of observed main sponsor abnormal returns in event window [0], on the basis of geographical location: victories in Europe versus victories outside of Europe.

     AR (%) Student t-test

p-valueWilcoxon signed-rank

testp-value

Group 1: Victory in Europe (N = 120) -0.0783 0.3038 0.4760Group 2: Victory outside of Europe (N = 92) 0.2708 0.1341 0.0928 ***

Difference between groups Student t-test; p-value

0.0006 0.1126

Table 8: List of Formula One races that make up the total sample (N=212)

Event Event date Circuit Team Pole Main sponsor Main sponsor company1 15-4-2013 CHN Ferrari No Marlboro Philip Morris INTL.2 13-5-2013 ESP Ferrari No Marlboro Philip Morris INTL.3 27-5-2013 MCO Mercedes Yes Petronas Petronas Dagangan4 1-7-2013 GBR Mercedes No Petronas Petronas Dagangan5 29-7-2013 HUN Mercedes Yes Petronas Petronas Dagangan

             6 19-3-2012 AUS McLaren No Vodafone Vodafone Group7 26-3-2012 MYS Ferrari No Marlboro Philip Morris INTL.8 16-4-2012 CHN Mercedes Yes Petronas Petronas Dagangan9 11-6-2012 CAN McLaren No Vodafone Vodafone Group

10 25-6-2012 EUR Ferrari No Marlboro Philip Morris INTL.11 23-7-2012 DEU Ferrari Yes Marlboro Philip Morris INTL.

15

12 30-7-2012 HUN McLaren Yes Vodafone Vodafone Group13 3-9-2012 BEL McLaren Yes Vodafone Vodafone Group14 10-9-2012 ITA McLaren Yes Vodafone Vodafone Group15 19-11-2012 USA McLaren No Vodafone Vodafone Group16 26-11-2012 BRA McLaren No Vodafone Vodafone Group

             17 18-4-2011 CHN McLaren No Vodafone Vodafone Group18 13-6-2011 CAN McLaren No Vodafone Vodafone Group19 11-7-2011 GBR Ferrari No Marlboro Philip Morris INTL.20 25-7-2011 DEU McLaren No Vodafone Vodafone Group21 1-8-2011 HUN McLaren No Vodafone Vodafone Group22 10-10-2011 JPN McLaren No Vodafone Vodafone Group23 14-11-2011 ABD McLaren No Vodafone Vodafone Group

             24 15-3-2010 BHR Ferrari No Marlboro Philip Morris INTL.25 29-3-2010 AUS McLaren No Vodafone Vodafone Group26 19-4-2010 CHN McLaren No Vodafone Vodafone Group27 31-5-2010 TUR McLaren No Vodafone Vodafone Group28 14-6-2010 CAN McLaren Yes Vodafone Vodafone Group29 26-7-2010 DEU Ferrari No Marlboro Philip Morris INTL.30 30-8-2010 BEL McLaren No Vodafone Vodafone Group31 13-9-2010 ITA Ferrari Yes Marlboro Philip Morris INTL.32 27-9-2010 SGP Ferrari Yes Marlboro Philip Morris INTL.33 25-10-2010 KOR Ferrari No Marlboro Philip Morris INTL.

             34 27-7-2009 HUN McLaren No Vodafone Vodafone Group35 31-8-2009 BEL Ferrari No Marlboro Philip Morris INTL.36 28-9-2009 SGP McLaren Yes Vodafone Vodafone Group

             37 17-3-2008 AUS McLaren Yes Vodafone Vodafone Group38 26-5-2008 MCO McLaren No Vodafone Vodafone Group39 9-6-2008 CAN BMW Sauber No Petronas Petronas Dagangan40 7-7-2008 GBR McLaren No Vodafone Vodafone Group41 21-7-2008 DEU McLaren Yes Vodafone Vodafone Group42 4-8-2008 HUN McLaren No Vodafone Vodafone Group43 29-9-2008 SGP Renault No ING Group ING Groep44 13-10-2008 JPN Renault No ING Group ING Groep45 20-10-2008 CHN McLaren Yes Vodafone Vodafone Group

             46 19-3-2007 AUS Ferrari Yes Marlboro Altria Group47 9-4-2007 MYS McLaren No Vodafone Vodafone Group48 16-4-2007 BHR Ferrari Yes Marlboro Altria Group49 14-5-2007 ESP Ferrari Yes Marlboro Altria Group50 28-5-2007 MCO McLaren Yes Vodafone Vodafone Group

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51 11-6-2007 CAN McLaren Yes Vodafone Vodafone Group52 18-6-2007 USA McLaren Yes Vodafone Vodafone Group53 2-7-2007 FRA Ferrari No Marlboro Altria Group54 9-7-2007 GBR Ferrari Yes Marlboro Altria Group55 23-7-2007 EUR McLaren No Vodafone Vodafone Group56 6-8-2007 HUN McLaren Yes Vodafone Vodafone Group57 27-8-2007 TUR Ferrari Yes Marlboro Altria Group58 10-9-2007 ITA McLaren Yes Vodafone Vodafone Group59 17-9-2007 BEL Ferrari Yes Marlboro Altria Group60 1-10-2007 JPN McLaren Yes Vodafone Vodafone Group61 8-10-2007 CHN Ferrari No Marlboro Altria Group62 22-10-2007 BRA Ferrari No Marlboro Altria Group

             63 13-3-2006 BHR Renault No Mild Seven Japan Tobacco64 20-3-2006 MYS Renault Yes Mild Seven Japan Tobacco65 3-4-2006 AUS Renault No Mild Seven Japan Tobacco66 24-4-2006 SMR Ferrari Yes Marlboro Altria Group67 8-5-2006 EUR Ferrari No Marlboro Altria Group68 15-5-2006 ESP Renault Yes Mild Seven Japan Tobacco69 29-5-2006 MCO Renault Yes Mild Seven Japan Tobacco70 12-6-2006 GBR Renault Yes Mild Seven Japan Tobacco71 26-6-2006 CAN Renault Yes Mild Seven Japan Tobacco72 3-7-2006 USA Ferrari Yes Marlboro Altria Group73 17-7-2006 FRA Ferrari Yes Marlboro Altria Group74 31-7-2006 DEU Ferrari No Marlboro Altria Group75 7-8-2006 HUN Honda No Lucky Strike Britisch American Tobacco76 28-8-2006 TUR Ferrari Yes Marlboro Altria Group77 11-9-2006 ITA Ferrari No Marlboro Altria Group78 2-10-2006 CHN Ferrari No Marlboro Altria Group79 9-10-2006 JPN Renault No Mild Seven Japan Tobacco80 23-10-2006 BRA Ferrari Yes Marlboro Altria Group

             81 7-3-2005 AUS Renault Yes Mild Seven Japan Tobacco82 21-3-2005 MYS Renault Yes Mild Seven Japan Tobacco83 4-4-2005 BHR Renault Yes Mild Seven Japan Tobacco84 25-4-2005 SMR Renault No Mild Seven Japan Tobacco85 9-5-2005 ESP McLaren-Mercedes Yes West Imperial Tobacco GP.86 23-5-2005 MCO McLaren-Mercedes Yes West Imperial Tobacco GP.87 30-5-2005 EUR Renault No Mild Seven Japan Tobacco88 13-6-2005 CAN McLaren-Mercedes No West Imperial Tobacco GP.89 20-6-2005 USA Ferrari No Marlboro Altria Group90 4-7-2005 FRA Renault Yes Mild Seven Japan Tobacco91 11-7-2005 GBR McLaren-Mercedes No West Imperial Tobacco GP.92 25-7-2005 DEU Renault No Mild Seven Japan Tobacco

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93 1-8-2005 HUN McLaren-Mercedes No West Imperial Tobacco GP.94 22-8-2005 TUR McLaren-Mercedes Yes West Imperial Tobacco GP.95 5-9-2005 ITA McLaren-Mercedes Yes West Imperial Tobacco GP.96 12-9-2005 BEL McLaren-Mercedes No West Imperial Tobacco GP.97 26-9-2005 BRA McLaren-Mercedes No West Imperial Tobacco GP.98 10-10-2005 JPN McLaren-Mercedes No West Imperial Tobacco GP.99 17-10-2005 CHN Renault Yes Mild Seven Japan Tobacco

             100 8-3-2004 AUS Ferrari Yes Marlboro Altria Group101 22-3-2004 MYS Ferrari Yes Marlboro Altria Group102 5-4-2004 BHR Ferrari Yes Marlboro Altria Group103 26-4-2004 SMR Ferrari No Marlboro Altria Group104 10-5-2004 ESP Ferrari Yes Marlboro Altria Group105 24-5-2004 MCO Renault Yes Mild Seven Japan Tobacco106 31-5-2004 EUR Ferrari Yes Marlboro Altria Group107 14-6-2004 CAN Ferrari No Marlboro Altria Group108 21-6-2004 USA Ferrari No Marlboro Altria Group109 5-7-2004 FRA Ferrari No Marlboro Altria Group110 12-7-2004 GBR Ferrari No Marlboro Altria Group111 26-7-2004 DEU Ferrari Yes Marlboro Altria Group112 16-8-2004 HUN Ferrari Yes Marlboro Altria Group113 30-8-2004 BEL McLaren-Mercedes No West Imperial Tobacco GP.114 13-9-2004 ITA Ferrari Yes Marlboro Altria Group115 27-9-2004 CHN Ferrari Yes Marlboro Altria Group116 11-10-2004 JPN Ferrari Yes Marlboro Altria Group117 25-10-2004 BRA Williams-BMW No HP Hewlett-Packard

             118 10-3-2003 AUS McLaren-Mercedes No West Imperial Tobacco GP.119 24-3-2003 MYS McLaren-Mercedes No West Imperial Tobacco GP.120 21-4-2003 SMR Ferrari Yes Marlboro Altria Group121 5-5-2003 ESP Ferrari Yes Marlboro Altria Group122 19-5-2003 AUT Ferrari Yes Marlboro Altria Group123 2-6-2003 MCO Williams-BMW No HP Hewlett-Packard124 16-6-2003 CAN Ferrari No Marlboro Altria Group125 30-6-2003 EUR Williams-BMW No HP Hewlett-Packard126 7-7-2003 FRA Williams-BMW Yes HP Hewlett-Packard127 21-7-2003 GBR Ferrari Yes Marlboro Altria Group128 4-8-2003 DEU Williams-BMW Yes HP Hewlett-Packard129 25-8-2003 HUN Renault Yes Mild Seven Japan Tobacco130 15-9-2003 ITA Ferrari Yes Marlboro Altria Group131 29-9-2003 USA Ferrari No Marlboro Altria Group132 13-10-2003 JPN Ferrari Yes Marlboro Altria Group

             133 4-3-2002 AUS Ferrari No Marlboro Altria Group

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134 18-3-2002 MYS Williams-BMW No Compaq Compaq Computers135 1-4-2002 BRA Ferrari No Marlboro Altria Group136 15-4-2002 SMR Ferrari Yes Marlboro Altria Group137 29-4-2002 ESP Ferrari Yes Marlboro Altria Group138 13-5-2002 AUT Ferrari No Marlboro Altria Group139 27-5-2002 MCO McLaren-Mercedes No West Imperial Tobacco GP.140 10-6-2002 CAN Ferrari No Marlboro Altria Group141 24-6-2002 EUR Ferrari No Marlboro Altria Group142 8-7-2002 GBR Ferrari No Marlboro Altria Group143 22-7-2002 FRA Ferrari No Marlboro Altria Group144 29-7-2002 DEU Ferrari Yes Marlboro Altria Group145 19-8-2002 HUN Ferrari Yes Marlboro Altria Group146 2-9-2002 BEL Ferrari Yes Marlboro Altria Group147 16-9-2002 ITA Ferrari No Marlboro Altria Group148 30-9-2002 USA Ferrari No Marlboro Altria Group149 14-10-2002 JPN Ferrari Yes Marlboro Altria Group

             150 5-3-2001 AUS Ferrari Yes Marlboro Altria Group151 19-3-2001 MYS Ferrari Yes Marlboro Altria Group152 2-4-2001 BRA McLaren-Mercedes No West Imperial Tobacco GP.153 16-4-2001 SMR Williams-BMW No Compaq Compaq Computers154 30-4-2001 ESP Ferrari Yes Marlboro Altria Group155 14-5-2001 AUT McLaren-Mercedes No West Imperial Tobacco GP.156 28-5-2001 MCO Ferrari No Marlboro Altria Group157 11-6-2001 CAN Williams-BMW No Compaq Compaq Computers158 25-6-2001 EUR Ferrari Yes Marlboro Altria Group159 2-7-2001 FRA Ferrari No Marlboro Altria Group160 16-7-2001 GBR McLaren-Mercedes No West Imperial Tobacco GP.161 30-7-2001 DEU Williams-BMW No Compaq Compaq Computers162 20-8-2001 HUN Ferrari Yes Marlboro Altria Group163 3-9-2001 BEL Ferrari No Marlboro Altria Group164 17-9-2001 ITA Williams-BMW Yes Compaq Compaq Computers165 1-10-2001 USA McLaren-Mercedes No West Imperial Tobacco GP.166 15-10-2001 JPN Ferrari Yes Marlboro Altria Group

             167 13-3-2000 AUS Ferrari No Marlboro Altria Group168 27-3-2000 BRA Ferrari No Marlboro Altria Group169 10-4-2000 SMR Ferrari No Marlboro Altria Group170 24-4-2000 GBR McLaren-Mercedes No West Imperial Tobacco GP.171 8-5-2000 ESP McLaren-Mercedes No West Imperial Tobacco GP.172 22-5-2000 EUR Ferrari No Marlboro Altria Group173 5-6-2000 MCO McLaren-Mercedes No West Imperial Tobacco GP.174 19-6-2000 CAN Ferrari Yes Marlboro Altria Group175 3-7-2000 FRA McLaren-Mercedes No West Imperial Tobacco GP.

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176 17-7-2000 AUT McLaren-Mercedes Yes West Imperial Tobacco GP.177 31-7-2000 DEU Ferrari No Marlboro Altria Group178 14-8-2000 HUN McLaren-Mercedes No West Imperial Tobacco GP.179 28-8-2000 BEL McLaren-Mercedes Yes West Imperial Tobacco GP.180 11-9-2000 ITA Ferrari Yes Marlboro Altria Group181 25-9-2000 USA Ferrari Yes Marlboro Altria Group182 9-10-2000 JPN Ferrari Yes Marlboro Altria Group183 23-10-2000 MYS Ferrari Yes Marlboro Altria Group

             184 8-3-1999 AUS Ferrari No Marlboro Altria Group185 12-4-1999 BRA McLaren-Mercedes Yes West Imperial Tobacco GP.186 3-5-1999 SMR Ferrari No Marlboro Altria Group187 17-5-1999 MCO Ferrari No Marlboro Altria Group188 31-5-1999 ESP McLaren-Mercedes Yes West Imperial Tobacco GP.189 14-6-1999 CAN McLaren-Mercedes No West Imperial Tobacco GP.190 12-7-1999 GBR McLaren-Mercedes No West Imperial Tobacco GP.191 26-7-1999 AUT Ferrari No Marlboro Altria Group192 2-8-1999 DEU Ferrari No Marlboro Altria Group193 16-8-1999 HUN McLaren-Mercedes Yes West Imperial Tobacco GP.194 30-8-1999 BEL McLaren-Mercedes No West Imperial Tobacco GP.195 27-9-1999 EUR Stewart-Ford No HSBC HSBC HDG.196 18-10-1999 MYS Ferrari No Marlboro Altria Group197 1-11-1999 JPN McLaren-Mercedes No West Imperial Tobacco GP.

             198 9-3-1998 AUS McLaren-Mercedes Yes West Imperial Tobacco GP.199 30-3-1998 BRA McLaren-Mercedes Yes West Imperial Tobacco GP.200 13-4-1998 ARG Ferrari No Marlboro Altria Group201 27-4-1998 SMR McLaren-Mercedes Yes West Imperial Tobacco GP.202 11-5-1998 ESP McLaren-Mercedes Yes West Imperial Tobacco GP.203 25-5-1998 MCO McLaren-Mercedes Yes West Imperial Tobacco GP.204 8-6-1998 CAN Ferrari No Marlboro Altria Group205 29-6-1998 FRA Ferrari No Marlboro Altria Group206 13-7-1998 GBR Ferrari No Marlboro Altria Group207 27-7-1998 AUT McLaren-Mercedes No West Imperial Tobacco GP.208 3-8-1998 DEU McLaren-Mercedes Yes West Imperial Tobacco GP.209 17-8-1998 HUN Ferrari No Marlboro Altria Group210 14-9-1998 ITA Ferrari Yes Marlboro Altria Group211 28-9-1998 LUX McLaren-Mercedes No West Imperial Tobacco GP.212 2-11-1998 JPN McLaren-Mercedes No West Imperial Tobacco GP.

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