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Patterson, C.W. (2019)

GOAL SCORING IN EUROPEAN SOCCER
Tournament Structure and Home Field Advantage

Home field advantage is a phenomenon, albeit a declining one, in sport which playing at a home venue gives the home team an advantage which results in a higher winning percentage. A variety of reasons have been given to explain why the phenomenon occurs including the effects of home crowds, the effects of the away team travelling, familiarisation and referee bias. In soccer, home field advantage research is based primarily, almost exclusively, on league tournaments with teams playing one another both home and away. This study investigated 5293 soccer games with the aim of comparing home field advantage as defined as winning percentages, the home edge which estimates the number of goals playing at home is worth, and the first goal between three types of soccer tournaments: leagues, knockout cups, and combined cup competitions.

Home field advantage in sport is defined as home teams winning over 50% of matches and has been an area of research in sport since Morris (1981) first researched the phenomenon with soccer regularly being identified as having some of the highest home team winning percentages (Courneya & Carron, 1992; Jamieson, 2010). Averaging the published home field advantages from domestic leagues in top European nations regularly identifies home field advantage at 60.7% in Belgium, 60.53% (±6.06%) in England, 63.28% (±3.77%) in France, 60.71% (±3.72%) in Germany, 61.87% (±2.83%) in Italy, 59.34% (±2.60%) in the Netherlands, 61.78% (±4.14%) in Portugal, and 63.18% (±3.24%) in Spain (Table 1). It is apparent from reviewing the findings of previous research that as the game has evolved with professionalism, there has been a decline in the winning percentages for the home team. The long-term study of English top division soccer by Pollard (2006b) states a 7.4% decline over a 110-year period while assessing the seasons covered by Sánchez et al.(2009), Lago-Pena et al.(2011) and Leite (2017) highlights the decline in Spanish domestic soccer (Table 1).

In a brief review, Pollard (2008) summarised the main hypothesised reasons given for the home field advantage and the subsequent decline as crowd effects, travel effects, familiarity, referee bias, territoriality special tactics, and specific rule changes, although the rules changes stated have become relatively irrelevant since 1995. While research has attempted to investigate each of these aspects and their relevance on home field advantage, it is more likely that there is an interaction with reasons occurring simultaneously (Pollard, 2006; Pollard, 2008). With the increased professionalism and improvements in transportation networks, travel effects on away team performances are negligible and may reflect in the contradicting evidence regarding travel effects on performance (Clarke & Norman, 1995; Pollard, 2008; Seckin & Pollard, 2008; Oberhofer et al., 2010; Armatas & Pollard, 2014; Almeida & Volossovitch, 2017).

Playing constantly at the same venue allows players to become accustomed to the stadium and its associated facilities which should aid in home field advantage but this may be limited due to visiting players playing more regularly at stadiums whose teams remain a perennial competitors in the leagues. The two situations that have seen significant relationships with home field advantage are the presence of a running track (Dohmen, 2008; Skoppa, 2008; Marques, 2009; Buraimo et al., 2010; Unkelbach & Memmert, 2010; Pollard & Gomez, 2015; Pollard & Armatas, 2017) and the use of an artificial pitch (Barnett & Hilditch, 1993). With the lower attendances and more dispersed density of crowds from the transition to all-seater stadiums, especially when coupled with a running track that moves the crowd further from the pitch, the effect of the crowd may be lessened in the post-Hillsborough era. Regardless, the effect of the crowd is a complex one with the advantage being present even with the smallest of crowd sizes (Pollard & Pollard, 2005; Pollard, 2006a) although whether it is due to size, density, intensity or distance from the pitch, it has an apparent impact on home field advantage.

Table 1. Previous research outlying home field advantage in European soccer leagues

There is a belief that the effect of the crowd may not necessarily present a direct advantage or disadvantage to the home or away teams, respectively, but may benefit the home team through creating a refereeing bias (Pollard, 2008). Reviewing referee’s in-game decisions has shown a bias towards the home team in the frequency of fouls awarded, yellow and/or red cards shown, and the amount of stoppage time added to the end of the game (Nevill et al., 1996; Nevill et al., 2002; Sutter & Koher, 2004; Carmichael & Thomas, 2005; Garicano et al, 2005; Dawson et al., 2007; Seckin & Pollard, 2008; Unkelbach & Memmert, 2010; Riedl et al., 2015). The professionalism and attempted neutrality of referee’s may have limited their influence on home field advantage and this maybe further tempered in future with the evolution and, the appropriate, use of the video assistant referee (VAR) system become more frequent in use and applied properly to in-game decisions which have previously incorrectly favoured the home team. It is not uncommon in soccer for visiting teams to adopt more defensive strategies, sacrificing offence to ensure that they don’t lose matches, accepting the draw and thus “parking the bus” as it is called in soccer jargon, most notable when travelling to a team ranked higher than them in the league system. While there is no conclusive link between tactical approaches and home field advantage, the findings of studies assessing performance variables have noted significantly higher results for the home team in offensive indices (Carmichael & Thomas, 2005; Jacklin, 2005; Tiucker et al., 2005; Rahnama et al., 2006; Lago & Martin, 2007; Seckin & Pollard, 2008; Peñas & Ballesteros, 2011; Armatas & Pollard, 2014). The current study aims to investigate home field advantage from both a results perspective and the game’s first goal in competitions in 13 nations within Europe as well as the UEFA Champions League and Europa League for the 2018/19 season. Rather than comparing leagues in different nations, the study will focus on differences between three types of competitions, league, knockout cup and combined cup through comparisons of home team winning percentages, the mean goals per goal, the number of goals attributed to playing at home, and the percentage of times the home team scores the opening goal of the game.

A total of 5293 soccer matches played in tournaments across Europe for the 2018/19 season was selected as the population sample for the purposed of this study. The nations whose data was collected were identified as those who have had at least one team play in the final of the UEFA Champions League or the European Cup, as it was called prior to 1992 which resulted in 13 nations being selected in addition to the continental tournaments of the UEFA Champions League and its understudy the UEFA Europa League (Table 2). Only tournaments involving the nations league winners from the 2017/18 season was included in this study and in terms of cup competitions, data was collected from the round in which that team entered the competition. The tournaments were divided into one of three categories, a league in which teams played one-another at least twice throughout the season, a knockout cup, where losing a game resulted in elimination from the tournament, and a combined cup, which included both a small league component to determine qualifiers for the knockout phase that follows (Table 2). All data was collected from www.worldfootball.net, and for this study any matches played at a “neutral” venue was excluded from the data sample, with the exception of Tottenham Hotspur who played the 2018/19 season at Wembley Stadium while White Hart Lane was being re-developed into the Tottenham Hotspur Stadium.

Table 2. List of nations and the tournaments within each nation included in the study sample.

Data for each game was inputted into a series of Microsoft Excel spreadsheets (Microsoft Excel 2007; Microsoft Corporation: Redmond, Washington, USA) with the number of goals scored by each team used to identify which match results classification, home win, away win, draw, no score draw the game was accredited to. Additionally, whether the winning team kept a clean sheet, where no goals were scored by the opposition, was identified as was the team which scored first goal of the game.

By separating each tournament, on an individual worksheet initially, the mean number of gaols scored per tournament could be calculated as could the home edge, the number of goals that home field advantage is actually worth to the home team and is calculated through the Solver extension in the Excel spreadsheet software. The calculation of the home edge is a two-stage process with the first stage predicting the home win or loss margin of every game in the tournament using a rudimental home edge value and rating for each team competing in the tournament. The squared difference between the actual home win or loss margin and the predicted one is calculated and the cumulative total square difference for all games within a tournament is calculated. The second stage utilises the Solver extension, to run a series of trials in which the team ratings and home edge values were altered so that the total square error value was minimised (Appendix A).

For analysis, the generic match data for result, team scoring first and whether the team’s managed a clean sheet or not was collated into a single data set for each tournament in addition to the tournament’s mean goals and home edge values. Matches resulting in a no score draw were removed from the sample as no goals were scored during these games. A single factor ANOVA was used to test for any significant differences, determined with a confidence level of 95% (or a p-value <0.05), between the tournament structure for the percentage of games won by the home team, for the calculated home edge factor, and for the mean number of goals per game. If the ANOVA indicated a significant difference within each measure, a series of t-tests directly compared each tournament structure to the other for that variable, utilising the same 95% confidence level as the ANOVA.

Of the 5293 games analysed in the study, 2402 were won by the home team, 1696 were won by the visiting team and 834 ended in a draw with the remaining 361 matches ending in a no score draw and being removed from the sample to isolate only the 4932 matches in which goals were scored. The average winning percentage for home teams in the 13 league competitions was 49.70% (±2.52%) while knockout cup competitions and combined cup competitions resulted in average home winning percentages of 42.77% (±12.88%) and 47.30% (±4.77%), respectively (Figure 1). The single factor ANOVA produced an insignificant difference between the three competition types for home winning percentage. When analysed in terms of winning with or without a clean sheet, significant differences between the three competition types were identified for both winning percentage with a clean sheet and winning percentage without a clean sheet. More games were won by the home side in each competition with a clean sheet, a difference ranging between the combined cup’s difference of 3.48% and the league’s difference of 7.94% (Figure 1).

Figure 1. Winning percentage for the home team based on the tournament structure (L indicates a significant difference with league, K indicates a significant difference with knockout cup, C indicates a significant difference with combined cup)igu1

Analysis of the ANOVAs revealed a significant difference in both the mean goals scored per game and the home edge between competition types. Significantly more goals per game in the knockout cup competitions (1.64) than in either the league (1.35) or the combined cup (1.50) with a significant difference (p-value <0.05) recorded for the comparison between the competition types (Figure 2A). When analysing the home edge for matches played in each competition, the knockout cup registered highest with 0.51 goals, compared to the 0.37 goals for league matches and the 0.36 goals for combined cup competitions. However, despite the ANOVA indicating the significant difference between the home edge values for each of the competitions, none of the post hoc t-test comparisons identified such differences (Figure 2B).

Figure 2. Mean goals per game (A) and home edge (B) for each tournament (* indicates a significant difference identified by single-factor ANOVA; L indicates significant difference to league; K indicates significant difference to knockout Cup; C indicates significant difference to combined cup)

An average of 50% (±20.40%) of matches in league competitions had the opening goal of the game scored by the home team with 37.47% (±15.42%) of league matches being won by the home side after scoring the first goal of the game. The ANOVA result indicated a significant difference between the competition types with the post hoc ttest identifying the only significant difference was between the league and combined cup tournaments (Figure 3). 28.82% (K C) 24.58% (L C) 25.39% (L K) 20.88% (K C) 18.19% (L C) 21.91% (L K) 0 10 20 30 40 50 60 League Knockout Cup Combined Cup Percentage of Games Won Win Percentage - Clean Sheet Win Percentage - Conceded Figure 1. Winning percentage for the home team based on the tournament structure (L indicates a significant difference with league, K indicates a significant difference with knockout cup, C indicates a significant difference with combined cup) Fewer matches in knockout cup and combined cup competitions found the home team opening the scoring (36.84% ±24.37% and 21.94% ±27.93%, respectively) and for matches where the home team scored first and won the match (27.71% ±19.91% and 16.31% ±20.84%, respectively). As with the analysis for the home team opening the scoring, the ANOVA and t-tests identified a significant difference between the league and combined cup competition types for the winning percentage of home teams who scored the game’s first goal (Figure 3).

Figure 3. Percentage of matches where the home team scored first and matches where the home team won after scoring first (* indicates significant difference from single-factor ANOVA; † indicates significant difference between tournament types)

The study aimed to investigate home field advantage in the 2018/19 European soccer season through analysis of differences between matches in leagues, knockout cup, and combined cup competitions. Overall home winning percentages do not differ between tournament types but there were significant differences between tournament types when wins were characterised as winning with or without a clean sheet (Figure 1). Home edge values indicated an insignificant difference between tournament types when the mean goals per game in each tournament was significantly different (Figure 2). A significant difference between league and combined cup tournament types was found in the percentage of games with the home team scoring first and scoring first and then winning the game (Figure 3).

Despite excluding no-score draws from the calculation, the average league home winning percentage was lower than those reported in all previous research studies, except for Carmichael & Thomas’s (2005) study (Table 1). When comparing the findings with the three studies which investigated a single season rather than a collection of seasons (Carmichael & Thomas, 2005; Lago-Peñas et al., 2011; Leite, 2017), only the home field advantage stated in Carmichael & Thomas (2005) was lower than either the related individual league results (Appendix B) or the collated league average found in this study. With Pollard (2006b) stating a decline in home field advantage over 110 years culminating in a 60.7% value for the 1996-2002 period, it could be hypothesised that the findings of this study confirm that in the top European leagues home field advantage is not as strong as it was in the past. That Spain’s La Liga league home field advantage decreased from 61.95% for the 2008/09 season (Lago-Penas et al., 2011) to 61.2% for the 2015/16 season (Leite, 2017) and then onto 47.74% for the 2018/19 season in this study could offer further support as there being a continued decline in home field advantage. Further examination of the findings of Leite (2017) highlights similar declines in Belgium, England, France, Germany, Italy, Netherlands, and Portugal (Appendix B), although this study focused on match points won at home, including draws, rather than games won.

To the authors knowledge, only Pollard (1986) included an analysis of knockout cup competitions, for both the FA Cup in England and the European Cup, prior to its rebranding and reformatting in 1992 as the Champions League, albeit for the seasons played between 1960 and 1984. Whether based on a theoretical points system, applied to the FA Cup, or on the goals scored and conceded, as in the European Cup, both knockout cup competitions recorded a higher home field advantage than the average for all collated knockout cups home field advantage and the individual knockout cup competitions, except for Spain’s Copa Del Rey (Appendix B). No previous study had investigated those cup competitions that included both a league and knockout structure but because of the mixed nature of the competition it isn’t necessarily surprising that this study found home winning percentages to be between the league and knockout cup percentages (Figure 1; Appendix B).

One study investigated home field advantage with a reference to the first goal of a game in a similar method as utilising in this study (Inan et al., 2019). While the findings on the home team scoring first were similar, with England’s Premier League and Italy’s Serie A showing increases as opposed to the decreases seen in Germany’s Bundesliga, France’s Ligue 1 and Spain’s La Liga, the stated percentages differed greatly between the stated percentages of home teams scoring first and winning the game (Inan et al., 2019). The Inan et al. (2019) study calculated the percentage of home teams winning after scoring the first goal as a percentage of the games in which the home team opened the scoring, as opposed to this study which calculated the percentage from the total number of games where a goal was scored, regardless of the team that scored it.

Familiarisation was given as a key reason to explain the highest levels of home field advantage seen in league competitions from previous studies (Pollard, 1986; Courneya & Carron, 1992; Barnett & Hilditch, 1993; Clarke & Norman, 95). It could be argued that it has become a reason for the decline in home field advantage in league competitions with the relatively low turnover in teams being relegated out of and promoted into the leagues each season. The result of this is that players are becoming more familiar with away venues and crowd effects at these stadiums from playing at least once at each venue within a season for a long run of seasons (Pollard & Gómez, 2009; Pollard & Gómez, 2015; Leite & Pollard, 2018). One factor that may counter growing familiarisation in domestic soccer is the use of randomised draws, including teams from outside of that division, in cup competitions which could bring visiting teams to new venues in which players may not have visited before though that would indicate that the new venues belong to lower ranked teams (Pollard, 1986).

Difference in team quality is most evident in cup competitions, even though the majority of cup competitions don’t include the top ranked teams until after a series of qualifying rounds or competition rounds, with these early rounds excluded from the data sample of this study. The randomness of the draw coupled with the presence of lower ranked teams in the competition means that teams from leagues higher up the league hierarchy could be drawn away to those from leagues lower down the hierarchy which has the potential to significantly impact home field advantage. In some competitions, like the UEFA Champions League and Europe League, there is a seeding process which keeps limits the number of top ranked teams that can face each other in the group phase of the competition. That the round-robin group phase has weaker teams, some of whom have had to play preliminary qualifying rounds to get into the group phase, playing both home and away against stronger teams which has a direct effect on reported home field advantages for these competitions.

Regardless of the tournament type, there is a widening gap between the top ranked teams in Europe and the lower ones, both within their league or within the continent, which is unsurprising given the financial implications of being one of those teams (Pollard & Gómez, 2009). By finishing higher up the league, the teams claim a larger percentage of the tournament prize fund which also makes it more likely to qualify for the Europe-wide competitions and gain the financial benefits from participating in those tournaments. Additionally, these teams have deeper squads of better-quality players so can also compete to later stages of domestic cup competitions (Pollard & Gómez, 2009). The combination of all this is that these teams collate more tournament prize funding, more income from crowds, which tend to be bigger than weaker competitors, a larger share of the television money, which ultimately make the team stronger at the detriment of their opponents and thus more likely that the top ranked teams will be better equipped to win away from home (Pollard & Gómez, 2009). Even at home and with the aim of countering the difference in team qualities, weaker teams may often adopt a more defensive strategy, regularly known as “parking the bus” (Pollard, 1986; Pollard & Pollard, 2005b). This altered focus on not conceding goals instead of scoring them makes it less likely for the team to win and should the weaker team be hosting a stronger opponent this approach will have a negative impact on home field advantage. Difference between tournaments for home field advantage could initially be explained through the greater variation in team strengths between league and cup competitions, greater familiarisation with league venues, the randomness of the cup draw meaning that the best teams are not necessarily going to play at home and the widening gap between the best teams and the rest in their league or Europe-wide. Arguably it is in the cup competitions where we could see travel effects having an influence on home field advantage (Dowie, 1982; Pollard, 1986; Clarke & Norman, 1995; Pollard & Pollard, 2005b; Goumas, 2012; Samuels, 2012). For the Europe-wide competitions, distance travelled for away games will be significantly higher than for games within their domestic competitions, in conjunction with most of the travelling being mid-week between a pair of domestic games at the bookending weekends. Additionally, it is not guaranteed that the travelling club will be one that can afford to travel in comfort, should it be a lower ranked team with a limited budget, as well as the prospect of travelling to areas of countries, or countries as a whole, which do not have the same level of infrastructure as the nations which host the top rated leagues (Pollard, 1986; Marques, 2002; Waters & Lovell,2002; Pollard, 2008; Marques, 2009; Samuels, 2012; Pollard & Gómez, 2015).

Unsurprisingly, due to the elimination threat of in either cup competitions, there are more mean goals per game in both the knockout and combined cups than in the league competitions (Figure 2A). With each competition type having an average of over one goal per game, the near 50-50 split between home team winning with or without a clean is easy to understand as there are either a 50-50 split in the top ranked teams playing at home and away to the lower ranked teams in leagues and the combined randomness of the cup draw with the presence of lower league teams still in the cup. To fully understand the mean goals and first goal aspects, the timing of when the first goal was scored would need to be included as the later the first goal is scored, the less likely it is for the opponent to score. To the author’s knowledge, this is the only study to have calculated a value for how many goals advantage it is playing at home with knockout cup’s recording the highest with a 0.512 goal advantage (Figure 2B).For the combined competitions the two-legged knockout phase with the away goals rule, tries to promote scoring goals away from home as a priority which could have significant impacts on both the mean goals and home edge once it progresses from the round-robin phase where teams of differing strengths are playing one another.

Home field advantage in soccer is in the decline in European soccer and is apparently continuing this trend regardless of the tournament type that is being researched to the extent that home field advantage has dropped below the 50% mark used for definition. Although, there is a discrepancy between the number of games analysed between the tournament types, a series of significant differences have been identified for winning percentages, when broken down into wins with clean sheets and wins without clean sheets, mean goals per game, home edge, and the frequency of the home team scoring the first goal. Previous research has indicated a range of external variables which can cause, or can influence, home field advantage and the findings of this study could be used to support a number of these variables. Further research would be suggested to focus on playing indices as well as winning percentages in cup competitions to bring the understanding of home field advantage in cup competitions to a similar level as league competitions.

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Appendix A: Solver Extension Use in Microsoft Excel

Appendix B: National Results

GOAL SCORING IN EUROPEAN SOCCER Tournament Structure and Home Field Advantage

GOAL SCORING IN EUROPEAN SOCCER
Tournament Structure and Home Field Advantage