Choking under pressure: the independent and interacting effects of audience and running score on the outcome of penalty kicks

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Choking under pressure: the independent and interacting effects of

audience and running score on the outcome of penalty kicks 

Name: Hakan Atici

Student ID: 10808655

BSc: Economics and Business Administration

Faculty: Economics and Business

Supervisor: Dhr. drs. R. (Rob) van Hemert Date of completion: Tuesday, 27th of June, 2017

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Statement of Originality

This document is written by Hakan Atici who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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1. Introduction

The quarter final of the World Cup 2006 was played between England and Portugal. After extra time the score was still equal, so a penalty shootout was needed to decide which team would continue their journey in this prestige tournament. After the penalty shootout, which Portugal won, the coaches of both countries agreed that scoring or missing a penalty is just a matter of luck. Luis Felipe Scolari, former coach of Portugal and winner of the World Cup of 2002 said that “they have played a wonderful match with ten men and we have to congratulate them. The penalties are always a lottery.” (The Guardian, 2006).

But is that really true? Past research has shown that many factors influence the outcome of a penalty kick. A supportive home crowd for example, how illogical it may sound, can have a

negative influence on the performance of a sports team. This because supportive audience can create an unintended form of pressure which consequently can disrupt the automatic process of performing a specific task, in this case a penalty kick (Wallace, Baumeister and Vohs, 2005; Dohmen, 2008). Furthermore, one can argue that penalties taken when you’re one goal behind will be missed more frequently relative to penalties taken when to score is equal. Jordet (2008) found that during penalty shootouts players will miss a penalty more frequently when missing a penalty would lead to losing the match (negative valence) than when it would lead to winning the match (positive valence). Translating this theory to penalties during regular playtime, it would mean that scoring an equalizer can arguable be seen as more stressful than scoring for a one goal lead. The momentousness of failure in the form of still being one goal behind has a stronger negative impact on the outcome of a penalty kick than the momentousness of success in the form of having a one goal lead (Wallace et al., 2005; Tversky and Kahneman, 1992).

Despite these interesting findings, there has never been looked at the outcome of combining those two theories on a larger scale. Therefore, the purpose of this study is to investigate the

relationship between the home and away crowd on performing a penalty kick and how the running score influences this relationship. This research will focus on penalties from season 2008-2009 until 2015-2016, taken by players from the Dutch Eredivisie, English Premier League, Italian Serie A and Spanish Primera Division. The data consists of 3281 penalties and will be analyzed through descriptive statistics and logistic regressions.

The second paragraph of this paper consists of theories that will be the fundamental building blocks of this research. The third paragraph contains the method section which includes information

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about the used data and how variables are measured. In the fourth paragraph the analyses and results can be found. In the fifth and last paragraph the overall conclusions will be discussed.

2. Theoretical framework

2.1 Choking under pressure

The importance of a penalty kick can create a form of pressure for the penalty taker. Missing a penalty kick under conditions which increase the importance of the penalty kick is the consequence of a player that choked under pressure. Choking under pressure can therefore be seen as a

phenomenon that is referred to as “performance decrements under circumstances that increase the importance of good or improved performance” (Baumeister, p. 610, 1984).

There are many factors one can come up with that can increase the importance of a certain situation. Audience and competition are two of them which are discussed by Wankel (1972) and Baumeister (1984). Jordet (2007) confirmed that competition creates pressure during penalty shootouts. He found that decisive penalty kicks in a penalty shootout would increase in the chance of choking under pressure. Dohmen (2008) explained that audience is another factor that can increase the likelihood of missing a penalty kick due to pressure. In this research the focus lies on the independent and interacting effect of these two common causes of pressure in a competitive environment.

2.2 Audience

Baumeister (1984) researched how audience in general created pressure and what kind of effect it had on the performance of a specific task. He concluded that people do choke under pressure through audience. But ask any football player if he prefers to play at their home stadium of at any other stadium and the answer you will most likely get is at their home stadium. Professional athletes have more success at their home stadium and plausible explanations for this are motivational

factors, travel time and referee biases (Courneya and Carron, 1992; Nevill and Holder, 1999). Interestingly, Dohmen’s (2008) findings about 3619 penalties taken in the German Bundesliga suggest that penalties taken by home teams are relatively more missed than penalties taken by away teams. Home teams converted 73.59% of the penalty kicks into a goal and 7.54% of their penalties were missed through choking under pressure. Away teams on the other hand scored 75.53% of their

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penalties and only missed 5.57% through choking under pressure. All the other missed penalties were saved by the goalkeeper.

Even though these findings are related to penalties taken in Germany only, there is many evidence that choking through home crowd occurs frequently throughout many sports and other countries. Baumeister and Steinhilber (1984) for example found that in baseball’s World Series and in basketball’s NBA Championship the performance of home teams decreased relatively more than the performance of away teams as the competition progressed and more decisive games were played. The same pattern was found by Wright and Jackson (1991) for the British Open Golf Championship. From the first to the final round of the tournament the performance of British golfers showed a more declining line than the performance of golfers from other countries. The reasoning behind these theories is that a supportive crowd can interrupt automatic and instinctive mechanisms during the performance of a complex task, like in this case taking a penalty kick (Baumeister, 1984; Wallace et al., 2005).

Research on the effect of home and away crowd on the performance of a penalty kick on a large scale has not been done. Although Dohmen (2008) finds that home teams miss a penalty kick relatively more frequently than away teams, his findings are related to the German

Bundesliga. As described earlier, I will look at a larger scale to penalties taken at the Dutch Eredivisie, English Premier League, Italian Serie A and Spanish Primera Division from season 2008-2009 until season 2015-2016. Altogether, the theories described above suggests that penalties taken by home teams will be missed relatively more than penalties taken by away teams. Therefore, my first hypothesis is:

H1: Teams who play in front of a home crowd will miss a penalty kick relatively more frequently than teams who plays in front of an away crowd.

2.3 Competition

Competition may be defined as a situation where one is competing with each other for the same outcome. Referring to taking a penalty kick, this means that scoring a penalty can contribute to winning the game, which is the outcome every team wants to achieve. A penalty kick can also be interpreted as an one-on-one competition between the penalty taker and the goalkeeper. According to Wankel (1972), rivalry is a motivational factor and has been linked with an increasement of arousal. Baumeister (1984) confirms this assumption and further assumes that pressure through

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rivalry is at its highest when one is imperceptible behind. However, one’s performance will not be affected when the competition is superiorly better, because practically one has already lost the contest: pressure through rivalry will then abate (Baumeister, 1984; Seta, 1982).

Jordet (2008) also confirms this theory by analyzing the outcome of twenty penalty shootouts of the FIFA World Cup. His results showed that players will miss a penalty more

frequently when missing a penalty would lead to losing the match (negative valence) than when it would lead to winning the match (positive valence). Jordet (2008) found that negative valence penalty kicks had a scorings percentage of 61.8% and that positive valanced shots had a scorings percentage of 92.0%. Neutral valenced shots, penalty kicks with a non-direct decisive outcome, had a scorings percentage of 73.7%.

Translating these findings to a penalty kick during a match, it would mean that penalty kicks that are rewarded when a team is imperceptible behind in score are considered as negative valenced penalty kicks, because missing these kind of penalties means that a chance of decreasing the

likelihood of losing is wasted. Penalty kicks that are rewarded when the score was equal are considered as positive valenced penalty kicks, because scoring these kind of penalties means that you can create a lead in score which increases the chance of winning the match. This means that players will miss a penalty more frequently when their team is one goal behind (negative valence) than when the score is equal (positive valence). Therefore, my second hypothesis will be:

H2: Players will miss a penalty more frequently when their team is one goal behind than when the score is equal.

Furthermore, there is a reason to believe that the running score influences the relationship between the home and away crowd and outcome of a penalty kick. The running score can influence the mood of the crowd, which consequently can influence the performance on the football pitch. Baumeister and Steinhilber (1984) argued that a supportive crowd would create more pressure than an unsupportive crowd. Dohmen (2008) confirmed this theory by concluding that home teams choke more under pressure than away teams. Combing this theory with the valence theory by Jordet (2008) gives the implication that a negative valenced shot strengthens the negative relationship between audience and the outcome of a penalty kick more than a positive valenced shot. The pressure in this case is derived from two sources, which increases the likelihood of choking under pressure. Thus, my third and last hypothesis is:

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H3: The running score influences the relationship between the audience and the outcome of a penalty kick in such way that negative valenced shot strengthens this relationship more than a positive valenced shot.

3. Methodology

3.1 Design, sample and procedure

In this paragraph the methods used to conduct this research and the way of collecting the data will be discussed. Because this research will build upon current knowledge, it may be considered as a deductive one. My data consist of 3281 penalty kick taken between 2008 and 2016 in the Dutch Eredivisie (n = 723), English Premier League (n = 747), Italian Serie A (n = 961) and Spanish Primera Division (n = 850). The data from these penalties were assessed through

www.tranfermarkt.com and were collected by seven fellow students and one supervisor. During the data collection, valuable information such as penalty taker, running score and home and away team were collected to provide the right measuring unit for every variable.

3.2 Measurements

The independent variable home and away crowd was assessed and measured by looking at which team is taking the penalty and at which venue the game took place. The moderating variable running score was assessed from the mutual score at the time when the penalty was rewarded. When the team taking the penalty kick was one goal behind (e.g. a running score of 1-2), the

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mutual score was -1. Penalty kicks that are rewarded when the mutual score was -1 are considered as negative valenced penalty kicks, because missing these kind of penalties means that a chance of decreasing the likelihood of losing is wasted. When the score was equal (e.g. a running score of 1-1), the mutual score was 0. Penalty kicks that are rewarded when the mutual score was 0 are considered as positive valenced penalty kicks, because scoring these kind of penalties means that you can create a lead in score which increases the chance of winning the match. This means that only penalties where the mutual score was -1 or 0 at the moment when the penalty was rewarded are useful for this research, because these mutual scores are most representable for the decisiveness of a penalty shootouts. Furthermore the performance of the penalty kick was measured by looking if the penalty taker scored the penalty.

3.3 Analyses and predictions

In this research I will analyze three models. The first two models will only test main effects and will analyze how the home and away crowd and the running score independently influence the outcome of a penalty kick. My third model will also test these two main effects but will additionally test one interaction effect, namely the interacting effect of the running score on that relationship between the home and away crowd and the outcome of a penalty kick.

Descriptive statistics and binary logistic regression will be used to analyze these three model. For my first model, I expect that a home crowd has a more negative direct relationship with the outcome of a penalty kick than an away crowd does (prediction 1.1). Furthermore I expect that a mutual score of -1 has a more negative relationship with the outcome of a penalty kick than a mutual score of 0 (prediction 1.2). For my third regression model, I expect to find a negative interacting effect of independent variable audience and the moderating variable running score on the outcome of a penalty kick (prediction 2). This negative interacting effect should be at its strongest when the combination of a home game and a negative valenced shot occurs. This means that a negative valenced shot strengthens the negative relationship between the crowd and the outcome of a penalty kick more than a positive valenced shot.

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4. Results

4.1 Descriptive and univariate results

Home and away crowd. The theories described by Baumeister and Steinhilber (1984), Wright and Jackson (1991) and Dohmen (2008) indicate that home teams will miss a penalty more frequently than away teams (H1) due to interruptance of automatic mechanisms during the performance of a complex task. Table I shows that out of all the 3281 recorded penalties, 2042 were awarded to home teams and 1239 to away teams. Home teams converted 1612 of their penalties into a goal and away teams converted 944 penalties into a goal. Home teams reached a scorings percentage of 78.94%, which is higher than the scorings percentage of 76.19% of the away teams.

The same patterns are also shown when looking at the scorings percentages of home and away teams with only a mutual score of -1 and 0 at the moment the penalty was rewarded. In this case, 1227 penalties were rewarded to home teams and 798 to away teams. Home teams scored 967 penalties and away teams scored 615 penalties. Home teams reached a scorings percentage of 78.81% whereas away teams reached a scorings percentage of 77.07%.

These findings contradict the findings of Dohmen (2008), who found out that German teams miss a penalty more frequently when playing a home game. Because of my large sample size, the found differences in scorings percentage and the fact that scorings percentage show the same pattern in both situations, it gives the indication the first hypothesis will be rejected.

Mutual score. According to Jordet (2008), negative valence shots would be missed more than positive valenced shots. This would mean that penalties with a mutual score of -1 will be more missed than penalties with a mutual score of 0 (H2). Table II shows that out of the 659 penalties

Table I. Descriptive analysis of home and away crowd on the outcome of a penaltykick

All mutual scores n n-scoring %-score

Home 2042 1612 78,94%

Away 1239 944 76,19%

Total 3281 2556 77,90%

Mutual scores -1 and 0 n n-scoring %-score

Home 1227 967 78,81%

Away 798 615 77,07%

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which were rewarded when the mutual score was -1, 505 penalties were converted to a goal

(76.56%). This percentage is higher for penalties with a mutual score of 0 (n = 1363, 78.87%). This is in line with the findings of Jordet (2008). A penalty during regular time however can never reach the decisiveness of a penalty kick in a penalty shootout. Table III shows the scorings percentages of penalties taken in the last 10 minutes of the regular playtime. This is done in order to replicate the decisiveness of a penalty kick during a penalty shootout. This table shows that out of the 115

penalties which were rewarded when the mutual score was -1, 90 penalties were converted to a goal (78.26%). This is higher than the scorings percentages of penalties with a mutual score of 0 (n = 148, 77.70%). This is not in line with Jordet (2008) and gives an indication that the second hypothesis will be rejected.

Table II. Descriptive analysis for mutual score and their relationship to the outcome of a penalty kick.

Mutual score n n-score %-score

-5 3 3 100,00% -4 19 11 57,89% -3 82 67 81,71% -2 249 184 73,90% -1 659 505 76,56% 0 1363 1075 78,87% 1 590 465 78,81% 2 217 168 77,42% 3 73 57 78,08% 4 17 13 76,47% 5 4 4 100,00% 6 3 3 100,00% 7 1 0 0,00% 8 1 1 100,00%

Table III. Descriptive analysis for mutual score (>80th minute) and their relationship to the outcome of a penalty kick.

Mutual score (>80th minute) n n-score %-score

-1 115 90 78,26%

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Interacting variable: crowd and mutual score. The theories described by Baumeister and

Steinhilber (1984), Dohmen (2008) and Jordet (2008) gives the implication that a negative valenced shot strengthens the negative relationship between audience and the outcome of a penalty kick more than a positive valenced shot. Table IV shows that most of the penalties were rewarded to the home team and that home teams convert a penalty more frequently to a goal than away teams. When a team is behind in score and plays an away game, the percentage of scoring a penalty decreased with 5.92%. This pattern is also noticeable when a team has a a lead in score, because the percentage of scoring a goal from a penalty kick in this case decreased with 6.78% at away games. On the other hand, when the score is equal, the percentage of scoring a penalty increased with 1.58% when playing an away game. This is applicable for all of the penalties as well as penalties where the mutual score was -1 and 0 at the moment when the penalty was awarded. The percentages do differ a bit, but reflect in general the same movement of scoring percentage.

The results also partially contradict the theories of Baumeister (1984) and Wallace et al. (2005). They argued that a supportive crowd can interrupt automatic and instinctive mechanisms during the performance of a complex task. Table IV gives indications that this is not the case. Because of the fact that the scoring percentages at an equal score deviate the most in comparison with the scoring percentages in other cases, a mutual score of 0 is set as the reference group for the upcoming multivariate logistic regression analysis.

Interacting variable at competition level: crowd and mutual score. At competition level, the percentages of scoring a penalty kick show in general the same patterns as described above. Table

Table IV. Descriptive analysis of the interacting effect of the audience and mutual score on the outcome of a penalty kick

All mutual scores n-home (% of scoring) n-away (% of scoring) Difference in % Behind in score 505 (78,57%) 510 (73,92%) -5,92%

Equal score 881 (78,43%) 482 (79,67%) 1,58% Lead in score 657 (79,97%) 246 (74,49%) -6,78%

Mutual scores -1 and 0 n-home (% of scoring) n-away (% of scoring) Difference in % Behind in score (-1) 354 (77,68%) 314 (73,25%) -6,05%

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V shows that for almost every competition the percentage of scoring a penalty decreased when a team plays an away game in combination with a mutual score of -1. Penalties taken in the Dutch Eredivisie and English Premier League show the same pattern as shown in table IV. Scoring percentages in the Italian Serie A and Spanish Primera Division on the other hand do show a

deviating pattern. The scoring percentage of penalties taken in Italy show an increasement for teams behind in score and playing an away game. Table V furthermore shows that away team in the Spanish Primera Division perform worse than home teams, regardless of the running score. Although the decreasement is at its lowest when the score is equal, the Spanish competition is the only one who showed a negative difference for a mutual score of 0.

4.2 Multivariate analyses

A logistic regression analysis was performed with the outcome of a penalty kick as dependent variable and home and away crowd as well as mutual score as independent variables. I classified

Table V. Descriptive analysis of the mutual score on the outcome of a penalty kick on competition level.

Dutch Eredivisie Home Away Difference in %

Behind in score 79,46% 75,56% -4,91%

Equal score 78,97% 80,68% 2,17%

Lead in score 78,65% 72,86% -7,36%

English Premier League Home Away Difference in %

Behind in score 83,93% 71,19% -15,18%

Equal score 78,57% 79,37% 1,02%

Lead in score 79,47% 73,47% -7,55%

Italian Serie A Home Away Difference in %

Behind in score 73,91% 74,56% 0,88%

Equal score 77,22% 81,29% 5,27%

Lead in score 81,58% 74,58% -8,58%

Spanish Primera Division Home Away Difference in %

Behind in score 78,81% 74,44% -5,54%

Equal score 77,63% 76,34% -1,66%

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the 3281 penalties in two categories according to their mutual score at the moment when the

penalty was rewarded. Only mutual scores of -1 and 0 are used in this logistic regression analysis in order to replicate the decisiveness of a penalty shootout. Furthermore the interacting variable crowd and running score was added to investigate the moderating effect. In total 2022 penalty kicks were analyzed and this model does not significantly predicted the outcome of a penalty kick (chi-square = 1.293, df = 1, p = 0,255). This model explained between 0,3% and 0,4% of the variance in outcome of a penalty kick.

Although non-significance, table VI shows that an away crowd is more negatively related to the outcome of a penalty kick than a home crowd: model 1.1 (β = -0.096, ns.), 2 (β = -0.083, ns.) and 3 (β = -0.075, ns.). This is in line with the descriptive analyses of the outcomes described in table I, which showed a small difference in scorings percentage between a home team and an away team. My findings contradicts the findings of Dohmen (2008), Baumeister (1984) and Wallace et al. (2005). This means that my first hypothesis is rejected.

The running score at the moment of penalty kick does not significantly influence the

outcome of a penalty kick. Although non-significance, the logistic regression analysis did show that a mutual score of -1 has a negative impact on the outcome of a penalty kick in comparison with a mutual score of 0. These findings are in line with the positive and negative valence theory of Jordet (2008). Due to non-significance, my second hypothesis is rejected.

Furthermore, table VI shows what kind of effect the interacting variable crowd and mutual score has on the outcome of a penalty kick. Although the effect is at its strongest when a

combination of an away game and negative valenced shot occurs (β = -0.436, p = 0,030), model 4 shows that a negatively valenced shot strengthens the negative relationship between the crowd and the outcome of a penalty kick. Therefore my third hypothesis is accepted.

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5. Discussion

5.1 Summery

The purpose of this study was to investigate the direct effect of the home and away crowd and running score and the interacting effect of those two variables on the outcome of a penalty kick. I did not find support for my first hypothesis (H1), which stated that home teams will miss a penalty more frequently than away teams. My results show that the audience during a football match does not have any significant independent effect on the outcome of a penalty kick. This contradicts the findings of Dohmen (2008). The difference in outcomes of my study and the study of Dohmen (2008) can be explained by the fact that Dohmen (2008) only studied penalties taken in Germany from 1963 until 2004. Because of the fact that his study focused on only penalties taken in Germany, it is possible that his findings are only applicable for German teams. He also included penalties from a long time ago. It is plausible that scoring percentages of penalties showed a different pattern in the past than in recent years. Because of the fact that my results are based on

Table VI. Multivariate logistic regression results for the relationship between crowd, mutual score on the outcome of a penalty kick.

Model 1.2 Model 1.2 Model 2 Model 3

Variable Categories β β β β

Crowd Home Ref. Ref. Ref.

Away -0,096 -0,083 -0,075

Mutual Score 0 Ref. Ref. Ref.

-1 -0,130 -0,119 -0,077

Crowd / Mutual score Home / 0 Ref.

Away / 0 Ref.

Home / -1 Ref.

Away / -1 -0,436*

* p < 0,05

Notes:

Model 1.1 shows the independent effect of the crowd on the outcome of a penalty kick. Model 1.2 shows the independent effect of the mutual score on the outcome of a penalty kick.

Model 2 shows the independent effects of the crowd and the mutual score together on the outcome of a penalty kick. Model 3 shows the independent effects of the crowd and mutual score and the interacting effect of those two variables on the outcome of a penalty kick.

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penalties taken in the recently eight completed football seasons of four different countries, I consider the outcomes of my study more generalizable than the outcomes of the study of Dohmen (2008).

There was also not enough evidence to conclude that any mutual score at the moment of a penalty kick has a significant effect on the outcome of the penalty kick, which resulted in rejecting my second hypothesis (H2). This is not in line with the positive and negative valence theory described by Jordet (2008). These difference in findings is probably explainable by the fact that Jordet (2008) researched penalties taken in a penalty shootout and that I researched penalties taken in regular time of a football match. In a penalty shootout, there will be situations where scoring or missing a penalty kick will lead to winning (positive valence) or losing (negative valence) the football match with 100% certainty. It is difficult to translate this theory to penalties taken in regular time of the match, because it is always theoretically possible that the opponent can score at least one goal after the penalty is taken. Penalties taken at the end of the match will be logically more decisive than penalties taken at the beginning of the match, but will never reach the level of decisiveness of penalties taken in a penalty shootout. Although the increased form of decisiveness, table III showed that penalties with a mutual score of -1 had a higher scorings percentage in the last 10 minutes than in the match as a whole. This is probably explainable by the fact that more

experienced or skilled players will takes these kind of penalties to decrease the chance of missing. The results did show a significant interacting effect of the variables crowd and running score on the outcome of a penalty kick. According to previous studies, it was expected that a mutual score of -1 would have a negative effect on the relationship between audience and the outcome of a penalty kick (H3). The multivariate logistic regression analysis results showed that this is the case. Therefore the third hypothesis is accepted. Interestingly, the described theories suggested that a combination of a home game and negative valenced shot would would lead to a significant lowered chance of scoring a penalty kick. My analysis showed that this is only the case with negative valenced shots at away games.

Interesting observation which deserves mentioning is the fact that Jordet’s (2008) findings are all based on football games played at the FIFA World Cup. This means that practically every team plays an away game with exception of the host county. Jordet (2008) did found a decline in performance when a penalty kick was negatively valenced. Because of the fact that Jordet (2008) only observed away teams, which implicates that there is no reference group, it is impossible to compare these findings with home teams.

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5.2 Limitations

This study has a number of possible limitations that restrict the generalizability of my results. One of them is the lottery-part of taking a penalty kick. In the utopian situation where all variables are perfectly measured, there is still a chance the calculated outcome of a penalty kick will not occur. This is the consequence of the error term, which contains many forms of good or bad luck such as still scoring badly shot penalty kicks or missing a penalty even though the goalkeeper chose a different side to dive as described by Chiappori, Levitt and Groseclose (2002). In the modern day football community, this is the fundamental argument for saying that the outcome of a penalty kick is the same as the outcome of a lottery ticket. This part of a penalty kick is not measurable and therefore nobody knows how much of the outcome depends on this variable.

Another limitation of this study is that I presume that missing a penalty is the result of a player that chokes under pressure, which is logically not always the case. Other variables, such as the quality of the goalkeeper, the state of the pitch, the weather and of course luck as described here above will contribute to the result of a penalty kick. This is probably the reason why my

multivariate logistic regression model only explained 0.3% to 0.4% of the variance in the outcome a penalty kick.

5.3 Recommendation for future research

For future research I recommend that penalties from other countries and continents are included in the data set to secure more generalizability. My model only explained 0,3% to 0,4% of the variance in the outcome a penalty kick, which is very low. To minimize the effect of the error term and to explain more percent of the variance in the outcome, it is recommended to research more factors that can create pressure, such as monetary incentives (Baumeister, 1984) and the quality of the goalkeeper. Considering a penalty kick as a one-on-one competition between the goalkeeper and the penalty taker, it would be interesting to take the quality and experience of the goalkeepers into account.

5.4 Practical applications

For football managers it is important to replicate the situations which significantly increases the likelihood of a football player that chokes under pressure. Training under these circumstances can make a football player feel familiar with these kinds of pressure, which only will help the player in

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performing well. For business managers, my result implicate that audience in the form of monitoring on itself should not significantly lead to a lowered performance.

5.5 Conclusion

The analysis conducted in this research showed that home or away crowd does not have a significant influence on the outcome of a penalty and that the running score does not have a

significant influence on the outcome of a penalty kick. However, the combination of an away game and a mutual score of -1 will lead to a significant decreasement in the chance of successfully converting a penalty kick into a goal.

As my results show, it contradicts the theory that the outcome of a penalty kick is comparable to the outcome of a lottery ticket. Therefore, I have to disagree with Luis Felipe Scolari, one of the greatest manager of modern football. A non-measurable variable in the form of good or bad luck will definitely have an effect on the outcome of a penalty kick, but saying that scoring or missing a penalty kick is just a matter of luck is oversimplified thinking and is contradicting with scientific findings of this and past researches.

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6. Bibliography

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performance under pressure: The home field disadvantage in sports championships. Journal of personality and social psychology, 47(1), 85.

Chiappori, P. A., Levitt, S., & Groseclose, T. (2002). Testing mixed-strategy equilibria when players are heterogeneous: The case of penalty kicks in soccer. American Economic Review,

1138-1151.

Courneya, K. S., & Carron, A. V. (1992). The home advantage in sport competitions: A literature review. Journal of Sport and Exercise Psychology, 14(1), 13-27.

Dohmen, T. J. (2008). Do professionals choke under pressure?. Journal of Economic Behavior & Organization, 65(3), 636-653.

Jackson, J. (2006). Players will not blame Rooney, says Gerrard. The Guardian. Retrieved on 26 april, 2017. https://www.theguardian.com/football/2006/jul/02/worldcup2006.sport13 Jordet, G., Hartman, E., Visscher, C., & Lemmink, K. A. (2007). Kicks from the penalty mark in

soccer: The roles of stress, skill, and fatigue for kick outcomes. Journal of Sports Sciences, 25(2), 121-129.

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Nevill, A. M., & Holder, R. L. (1999). Home advantage in sport. Sports Medicine, 28(4), 221-236. Seta, J. J. (1982). The impact of comparison processes on coactors' task performance. Journal of Personality and Social Psychology, 42(2), 281.

Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and uncertainty, 5(4), 297-323.

Wankel, L. M. (1972). Competition in motor performance: An experimental analysis of motivational components. Journal of Experimental Social Psychology, 8(5), 427-437. Wallace, H. M., Baumeister, R. F., & Vohs, K. D. (2005). Audience support and choking under

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Wright, E. F., Jackson, W., Christie, S. D., McGuire, G. R., & Wright, R. D. (1991). The home- course disadvantage in golf championships: Further evidence for the undermining effect of supportive audiences on performance under pressure. Journal of Sport Behavior, 14(1), 51.

Choking under pressure: the independent and interacting effects of audience and running score on the outcome of penalty kicks