Universidad de San Andrés

Departamento de Economía

Licenciatura en Economía

Do football crowds matter?

Autor: Axel Jorgensen

Legajo: 20252

Mentor: Martin Rossi

Victoria, 23 de noviembre 2015

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Do football crowds matter?

Axel Jorgensen*

Abstract

This paper studies the extent to which crowd support provides home advantage, using

information from South American football leagues. To do this I exploit a natural experiment arising

from the fact that in 2013 the Argentine football association prohibited the attendance of visiting crowds

into football matches. I use the Uruguayan and Brazilian leagues as controls. The results suggest that

the impact of the crowd on home advantage is positive and significant.

*Student of BA in Economics, Universidad de San Andrés, Buenos Aires, Argentina.

** Many thanks to my mentor Martin Rossi for his patient guidance, Federico Bennett for his useful

comments and my friends and family for their support which helped me get to this long due moment.

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I. Introduction

In sports, the concept of "Home Advantage" implies that the team that plays at home has an

advantage over the visiting team. This home advantage has been attributed to mainly the following four

factors: (i) the team that plays at home has more supporters present encouraging them on, which

motivates the players and helps them perform better; (ii) the fans/crowd can also influence the referee's

decision and make him more likely to rule in favor of the local team; (iii) travel time, distance and form

of transportation for visitors can generate fatigue and stress, especially in different time zones; and (iv)

familiarity with the playing field by the local team can positively influence performance.

Due to multiple incidents of violence between crowds, in July 2013 the AFA barred visiting

supporters from attending football matches of the first Division, National B, First Metropolitan B and C. 1

I take advantage of these changes in regulations in Argentine football to identify the impact of the first

two factors (related to the crowd) in the home advantage.

The change in regulations in Argentine football generated a discontinuity in the relative size of

home crowd and away crowd. From one day to the next, the visiting crowd was reduced to zero and, in

some cases, was entirely replaced by local crowd, since it allowed the football clubs to sell more tickets

to their own crowd due to the additional space.

In principle, it is likely that crowd size is endogenous to team’s performance. Better performing

teams attract larger crowds that in turn may positively influence team’s performance. The change in the

regulations in Argentine football provides a source of exogenous variability in the size of the crowd.

Aside from team’s performance, I also look at the impact of the crowd on the referee's decisions,

using as additional outcomes the number of yellow cards and the number of red cards shown during the

match. I assess the quality/performance of the rivaling teams by using variables such as the difference of

points between them before the match.

1 In July 12, 2013, Javier Jerez, a fan of Lanús, died at Estadio Ciudad de La Plata, while a match was being played between Lanus and Estudiantes de la Plata as local during the 17th date of the Clausura tournament. Due to this incident the Minister of Security of Buenos Aires, Ricardo Casal, announced a ban on visiting public at all divisional football, this decision was subsequently accepted by the AFA (Argentine Football Association) and Aprevide (Agency for Prevention of Violence in Sport).

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Home Advantage has been extensively discussed in literature especially in the field of sports

statistics. There is little doubt this effect exists but it is hard to isolate the specific effects and identify

causality. According to Pollard (2008), “it is not known whether the primary effect of the crowd is to

give an advantage to the home team or a disadvantage to the away team and whether this is conveyed

directly to the players or via referee decisions influenced by the crowd.”

Among these studies there are several that look specifically to evaluate the effect of the crowd.

Ponza and Scoppa (2014) observed teams in the Italian league who share the same home stadium, but

where the ticket and season pass follows the traditional model where it favors the "local" team for that

match. By doing this they manage to control by two factors: the distance, conditions and travel time; and

familiarity with the terrain or playing field, since these factors are the same for both teams. The results

showed that the crowd increases the average goals scored by the locals and the probability of winning

the game.

Agnew and Carron (1994) found a positive relation between "density" of the fans and the Home

Advantage and Pollard (2006) argues that in the 90s, the Home Advantage fell due to a regulation

requiring all stadiums to have grandstand seats instead of allowing them to stand up which allowed for a

smaller crowd.

The literature also presents contradictory results. Several studies make use of the size of the

crowd to assess the impact on the Home Advantage. Pollard and Pollard (2005) compares the first

against the second division of several leagues and find that the magnitude of Home Advantage is very

similar between the two. Similarly, Pollard (1986) and Clarke and Norman (1995) compared the four

divisions of the English league with similar results.

With regard to the distance traveled of the visiting team, according to Pollard (2008) there is one

finding that is consistent: home advantage is reduced in local matches where no travel is involved. For

this particular result, Pollard collected evidence from the South­East professional football tournaments

(Pollard 2007) and specifically on the Turkish football league (Pollard et al. 2007).

In terms of familiarity with the playing field, when a team plays at home, they do so in a stadium

under known field conditions including, for example, the type and quality of the turf and the size and

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weather conditions. This concept has been difficult to prove in the literature but there are interesting

results in some studies comparing matches played on artificial grass courts (Barnett 1993), other courts

side with disproportionate dimensions (Pollard 1986) or even the ball type (Dosseville FE 2007). In

turn, other papers found that familiarity with the climate and altitude have an effect on the Home

Advantage (McSharry PE 2007).

II. Data and Descriptive Statistics

In Argentina, until December 2014 the First Division was composed of 20 professional football

clubs that play two single round­robin tournaments each year: the initial tournament from August to 2

December and the final tournament from February to June. Only one champion was established at the

end of the tournament. The data that was retrieved for this paper dates back from February 2011 to

December 2014. For each match the data includes the match score and the disciplinary sanctions

including penalties awarded and referee’s name.

Since February 2015, a new tournament is being contested by 30 football clubs where 10 clubs

were promoted from the Division “B” joined the first division. Each team plays against all other teams

once. I decided to exclude results from this tournament since changes like this might bias the results.

For Brazil, the “Campeonato Brasileiro Série A” or the “A Series Brazilian Championship”, is

the Brazilian league for professional football clubs. Contested by 20 clubs, it operates on a system of

promotion and relegation with the “Campeonato Brasileiro Série B”. Seasons usually run fromMay to

December, with teams playing 38 matches each (playing each team in the league twice, home and away)

totaling 380 matches in the season.

Finally for Uruguay, the “Primera División” or “First división” is contested by 16 clubs with the

same structure as the argentine league. Beginning mid year with the initial tournament until December

followed by the final tournament held from February to June.

2 Round­robin refers to a pattern or ordering whereby items are encountered or processed sequentially, often beginning again at the start in a circular manner.

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This provides a total of 4,000 observations. I am using the following variables: Win is equal to

1 if the home team wins, and 0 the home team ties or loses. Points home is equal to 3 if the local team

wins, 1 if they tie and 0 if they lose. Goals Home team is the number of goals scored by the local team

during the match. Yellow cards visitor is the number of yellow cards given by the referee to the away

team during the match. Finally, thetotal score differenceis the accumulated difference in points of both

teams before the match (a proxy of the quality of the teams).

All of these three countries belong to the The South American Football Confederation, known as

the “Conmebol”. This confederation is responsible for the organization and governance of South

American football's major international tournaments such as “Copa Libertadores” and “Copa

Sudamericana”. The same rules and regulations apply to all three tournaments and, as it can be seen

from the data description they have very similar format and tournament structure.

Neither Brazil nor Uruguay were affected by the change in Argentine regulation in June of 2013

nor by any similar one during this period that may have affected the crowd size.

Table 1 present the descriptive statistics. There is a positive difference in score between the

home and visitor team, indicating that the matches played as local tend to have more favorable results.

This provides supporting evidence in favor of the hypothesis of the existence of a home advantage. Note

that there is a significantly lower number of observations for the yellow cards since data was only

available starting in 2012 for all the disciplinary sanctions during the match. The data is generously

provided by two sports websites called www.Futbol360.com.ar and www.resultados.com.

Table 1. Descriptive statistics for Argentina, Brazil and Uruguay

Variable Observations Mean Std. Dev. Min Max

Win 4000 0.449 0.497 0 1

Points Home team 4000 1.622 1.298 0 3

Goals Home team 4000 1.403 1.186 0 6

Yellow cards visitor 2280 2.519 1.366 0 9

Total score difference 4000 0.057 8.459 ­43 44

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III. Methodology

I consider a match belongs to the treated group when it takes place in Argentina after the change

in the regulation, implying that the match occurred with no away crowd. The matches from Brazil and

Uruguay are considered non­treated in the entire period of the analysis.

All regressions are estimated using Ordinary Least Squares and include match fixed effect (for

example, a dummy variable that takes a value of one every time Boca Juniors plays against River Plate) in

order to control for distance traveled and field familiarity; and month/year dummies in order to control for

any seasonal effects that might have incidence on the home advantage.

The econometric model is as follows:

Yit= ai + bt + c*Treatmentit + d*TotalPointsDifferenceit + eit

Yit is any of the outcomes of interest for match “i” on time “t” ( Win, Points Difference , Goals Home,

Yellow Cards Visitor)

ai: Dummy for Match “i”

bt: Dummy for Month/Year “t”

IV. Results

The results are shown in Table 2. The regression shows that for treated matches relative to

untreated there is an increase by a factor of 0.09 in the probability of winning in favor of the home team.

This result is statistically significant under robust standard errors but lacks significance when clustered by

match. Regression [2] shows a significant increase of 0.26 in the points scored in favor of the home team

under robust check and clustered by match. The goals scored by the home team also remain statistically

significant even when clustered by match. There is an increase of 0.25 in the goals scored by the local

team. These results suggest that the crowd has a positive effect on the home team, though it may also

mean that the lack of visiting team crowd or excess of home team crowd negatively impacts the visiting

team’s performance.

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Table 2. The impact of playing with no away crowd controlling team’s quality. OLS Estimates.

Dependent variables in first row.

Win Points Home Goals home Yellow cards Visitor

Statistic [1] [2] [3] [4]

Treatment 0.0913 0.255 0.246 0.354

(0.046)* (0.122)** (0.110)** (0.178)**

[0.056] [0.149]* [0.134]* [0.224]

Total Points difference 0.011 0.031 0.017 0.006

(0.002)*** (0.0037)*** (0.003)*** (0.005)***

[0.002]*** [0.0045]*** [0.004]*** [0.007]***

Month/year Fixed effects Yes Yes Yes Yes

Team Fixed effects Yes Yes Yes Yes

Observations 3999 3999 3999 2280

R2 0.473 0.473 0.501 0.560

OLS OLS OLS OLS

Notes: The robust standard errors are shown in parentheses. The clustered standard errors are shown in brackets. *** Significant at the 1% level. ** Significant at the 5% level. * Significant at the 10% level.

In order to assess the influence that the change in the regulation might have had on the referee’s

decision I regress this against yellow and red cards. The number of observations drop significantly 3

when looking at the red cards which may explain why there is no significant effect. Even though the

yellow cards for the home team have a negative coefficient, these results are not statistically significant.

Finally, when looking at the yellow cards for the visitor the coefficient is positive and

statistically significant. There is an increase of 0.35 on yellow cards given to the away team. These

results would suggest that referees are influenced by the crowd whereby a relatively larger home crowd

or by contrast a null visiting crowd makes the referee more permissible towards the home team. This

could be related to the noise the crowd makes when a foul occurs during the match.

3 Most matches end up with no red cards.

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To this purpose, Nevill et al (2002) conducted an experiment where they asked 40 referees to

watch a video­taped game and make decisions on the incidents that occurred during the match. Half the

referees watched the game with the volume turned off and the other half with it turned on. The results

reflect that the referees that watched the match with the volume turned on (with crowd noise) granted

significantly less decisions against the home team. This results support the theory that the referees are

influenced by the crowd noise.

A very similar experiment was carried out by Nevill et al (2012) but with Muay Thai officials

(referees). This result also shows that the crowd noise increased the scores granted by this officials in

favour of the home team. These findings were attributed to effects such as informational conformity and

the use of a noise heuristic.

Finally, in table 3 I evaluate the same regressions but excluding two argentine football clubs

from the database: River Plate and Independiente de Avellaneda. The reason I exclude them from the

sample is that both this teams relegated to the B division during this period. They later promoted back to

the first division one year after relegating. Yet, since this teams are considered two of the biggest

football clubs of Argentina in terms of supporters I want to observe if their absence may have influenced

the results. As seen in the table the results are very similar and still statistically significant under a

robust regression.

V. Conclusion

Home advantage in sports is a well documented fact. However it still remains an unsolved

puzzle. It has been very hard to identify the actual causes for the existence of home advantage and how

it affects the game’s outcome. According to the literature, the main mechanisms seem to be crowd

support’s influence in the players and referee, the distance traveled by the away team and the home

team’s familiarity with the playing field.

In order to try to isolate the effect of the crowd I take advantage of a change in regulation in the

Argentine professional football league in 2013 that prohibited the away crowd from attending the games.

I use the Brazilian and Uruguayan leagues as control leagues since these leagues remained unaffected by

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this prohibition. Using fixed effects for the match between the same teams I am able to control for field

familiarity and distance traveled.

The results suggest that the crowd’s support has a strong and significant impact on the players

since there is an increase in the amounts of goals scored by the home team. It also suggests that the

referee is influenced by the crowd since there is a positive and significant increase in the amount of

yellow cards sanctioned to the away team.

As behavioral economics proposes, these results further help demonstrate that individualsare

influenced by social and emotional factors and that this has consequences on performance and outcomes,

whether it is in sport or in business.

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VII. References

Agnew, G. A., Carron, A. V. Crowd effects and the home advantage. Journal of Sport

Psychology 1994.

Barnett V, Hilditch S. The effect of an artificial pitch surface on home team performance in

football (soccer). J R Statist Soc A 1993.

Clarke SR, Norman JM. Home ground advantage of individual clubs in English soccer.

Statistician 1995.

Dosseville FEM. Influence of ball type on home advantage in French professional soccer.

Percept Mot Skills 2007.

McSharry PE. Altitude and athletic performance: statistical analysis using football results. BMJ

2007.

Myers, T. , Nevill, A. & Al­Nakeeb, Y. The Influence of Crowd Noise upon Judging Decisions

in Muay Thai. Advances in Physical Education. 2012.

Nevill AM, Balmer NJ, Williams AM. The influence of crowd noise and experience upon

refereeing decisions in football. Psychol Sport Exerc 2002.

Pollard R. Home Advantage in Football: A Current Review of an Unsolved Puzzle. J Sports Sci

2008.

Pollard R. Home advantage in soccer: a retrospective analysis. J Sports Sci 1986.

Pollard R. Worldwide regional variations in home advantage in association football. J Sports Sci

2006.

Pollard R, Pollard G. Ventaja de ser el equipo local en fútbol: una reseña de su existencia y

causas. Rev Int Fútbol Ciencia 2005.

Pollard R, Seckin A. Why is home advantage in South­east Europe the highest in the world?

12th European Congress of Sport Psychology 2007.

Ponza M., Scoppa V. Does the Home Advantage Depend on Crowd Support? Discussion Paper

2014.

Seckin A, Pollard R. Home advantage in Turkish professional soccer. J Sports Sci Med 2007.

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VI. Appendix

Table 3. The impact of playing with no away crowd controlling team’s quality. OLS Estimates.

Dependent variables in first row. Without River Plate and Independiente

Win Points Home Goals home Yellow cards Visitor

Statistic [1] [2] [3] [4]

Treatment 0.108 0.294 0.262 0.408

(0.05)** (0.129)** (0.117)** (0.19)**

[0.06]* [0.305]* [0.141]* [0.238]*

Score Difference (Total) 0.011 0.062 0.018 0.006

(0.001)*** (0.007)*** (0.004)*** (0.005)

[0.002]*** [0.009]*** [0.004]*** [0.007]

Month Fixed Effects Yes Yes Yes Yes

Team Fixed effects Yes Yes Yes Yes

Observations 3656 3656 3655 2112

R2 0.479 0.489 0.507 0.56

OLS OLS OLS OLS

Notes: The Huber­White robust standard errors are shown in parentheses. The clustered standard errors are shown in brackets. *** Significant at the 1% level. ** Significant at the 5% level. * Significant at the 10% level.

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Table 4. The impact of playing with no away crowd controlling team’s quality on disciplinary

sanctions. OLS Estimates. Dependent variables in first row.

Yellow cards

home Yellow cards

visitor Red cards

home Red cards

visitor

Statistic [1] [2] [3] [4]

Treatment ­0.138 0.355 ­0.077 0.355

(0.176) (0.178) (0.055) (0.178)

[0.221] [0.224] [0.07] [0.224]

Score Difference (Total) ­0.011 0.033 ­0.002 0.033

(0.005) (0.013) (0.002) (0.013)

[0.007] [0.017] [0.002] [0.017]

Month/year Fixed effects Yes Yes Yes Yes

Team Fixed effects Yes Yes Yes Yes

Observations 2280 2280 2280 2280

R2 0.458 0.563 0.509 0.563

OLS OLS OLS OLS

Notes: The Huber­White robust standard errors are shown in parentheses. The clustered standard errors are shown in brackets. *** Significant at the 1% level. ** Significant at the 5% level. * Significant at the 10% level.

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