key: cord-0871685-imyczhsy authors: Almeida, Carlos H.; Leite, Werlayne S. title: Professional football in times of COVID-19: did the home advantage effect disappear in European domestic leagues? date: 2021-03-30 journal: Biol Sport DOI: 10.5114/biolsport.2021.104920 sha: b883ed54524c82912ff3304ca5a0e52e020acb78 doc_id: 871685 cord_uid: imyczhsy This study aimed to examine how the home advantage (HA) and home teams’ performances changed in European football leagues (German Bundesliga, Spanish La Liga, English Premier League, Portuguese Primeira Liga and Italian Serie A) with the measures imposed by legal authorities to deal with the COVID-19 pandemic (no audience, five substitutions and “cooling breaks”). The HA (Pollard’s rescaled method) and home performance-related statistics of matches contested before (n = 491) and after (n = 491) the 2019–2020 season break were calculated and compared, for each league and for all five, using the paired t-test or the Wilcoxon signed-rank test. Overall, the HA did not significantly decrease in European leagues (from 16.4% to 11.6%; trivial effect size [ES]); however, a one-sample t-test revealed that the HA after the COVID-19 break was significantly greater than 0% (small ES). While the HA completely disappeared in the Bundesliga (large ES), its effects remained stable in La Liga (small ES), Premier League and Primeira Liga (trivial ES), and even increased in Serie A (medium ES) after the return. Home teams’ performances in these leagues were influenced to different extents by the COVID-19 situation, especially by playing behind closed doors. Altogether, significant decreases were observed for total shots, tackles (medium ES), shots on target and pass success (small ES). Therefore, the role of crowd support seems to vary depending on the context characteristics in which football is played. Also, the augmented “information transfer” from coaches to players during COVID-19 matches might have masked the crowd effects on the HA. In accordance with Marca [1] , before the COVID-19 pandemic declared by the WHO on March 11, 2020, the Bundesliga 2019-2020 registered a home win rate of 43.3%, which dramatically decreased to 16 .7% after the return to play, with 18 matches undertaken without an audience (so-called "ghost matches"). The hypothesis of the home advantage (HA) disappearance in European domestic leagues was associated with the absence of spectators in the stadiums, a restrictive measure imposed by each national healthcare governmental system to mitigate the propagation of the virus. Before the coronavirus outbreak, the HA effect had been considered a well-established phenomenon across most team sports, with particularly high magnitudes in association football [2] [3] [4] . This effect implies achieving better match outcomes when a team plays at its own ground (home) compared to playing at the opponents' facilities (away). The traditional method proposed by Pollard [5] for Professional football in times of COVID-19: did the home advantage effect disappear in European domestic leagues? AUTHORS: Carlos H. Almeida 1 , Werlayne S. Leite 2 pandemic, conducted by Fisher and Haucap [23] , was pioneering research on this topic. These authors showed that the HA completely vanished in the Bundesliga during "ghost matches", a finding which was not mirrored in the lower two divisions. Unlike the total crowd size, the reduced post COVID-19 occupancy rate to zero was found to be the main reason for the HA decrease [23] . Therefore, it seems reasonable to extend this research to other domestic leagues in Europe The sample consisted of 982 matches contested by 96 club teams, during the 2019-2020 season, in five European domestic leagues (German Bundesliga, Spanish La Liga, English Premier League, specifically addressing the influence of crowd support (e.g., size, density and/or proximity) on HA, the existing empirical evidence is still ambiguous. Whereas some studies have shown that increased crowd support is positively associated with points attained at home [10, 13, 14] , others have found that HA is not affected by attendance increases [15, 16] , and it even exists with small crowds [6, 8, 17] or in empty stadiums [18] . On the one hand, the crowd may influence the performance of a team by putting home players in a more positive and confident psychological state [8] . On the other hand, its support is also believed to indirectly influence the referees' decisions, creating a bias in favour of the home team [19] , which receives significantly fewer penalties and disciplinary cards than the visiting team [10, 14] . All in all, these mechanisms along with others have operated since the dawn of organised football in the 19 th century to produce the HA [17] . This ancestor effect developed a self-fulfilling prophecy among coaches that home teams win more often because they believe they have an advantage, thereby promoting more dominant, attacking and audacious strategies when playing at home [12] . In fact, home teams tend to exhibit higher values than visiting ones in diverse performancerelated variables, such as goals scored, total shots, shots on target, ball possession, passing success, dribbles, aerial duels and ball recoveries [20 -22] . Although HA and home performance represent distinct concepts, there is a close relationship between them: the HA usually reflects better performances of the home team. Given the unprecedented times we are facing because of COVID-19, the decision of concluding several European football leagues opened up a singular opportunity to (r)evaluate and clarify the relative importance of crowd support on HA and home teams' performances. The comprehensive analysis of German "ghost matches" during this The website "ZeroZero" (https://zerozero.pt) was also consulted to confirm the soundness of the primary data source in terms of home and away records related to match outcomes (home wins, draws, losses, goals scored and goals conceded). The raw data did not present inconsistencies. After the return, teams played the home matches at their usual stadiums apart from three teams (La Liga: Real Madrid CF; Primeira Liga: Belenenses SAD and CD Santa Clara), comprising a total of 31 out of 491 matches after the COVID-19 break (6.3%) played on a less familiar ground. Since these teams prepared for the return to play in the alternative facilities, and later continued to practise in them, no match was excluded from the sample. Prior to data collection, written permission from both website administrators was received, with the respective privacy policies being entirely respected. The methodological procedures conformed to the ethics guidelines of the local university, and the investigation was conducted in compliance with the principles expressed in the Declaration of Helsinki. The HA and home performance-related statistics (points, goals scored, goals conceded, total shots, shots on target, ball possession, pass success, aerial duels won, tackles and disciplinary cards) were the dependent variables of this study, whereas the COVID-19 situation was the independent variable. Pre-and post-COVID-19 HA were quantified for each European league and for all five using Pollard's rescaled method. This method produces a value of 0% when the same number of points are won at home and away (no home advantage), with the advantage then being measured on a scale between 0% to 100%, while negative values indicate a home disadvantage [9] . The formula adopted is the following: For an unbiased calculation of HA, this method requires a balance schedule of matches, in which teams play against the others twice, once at home and once away. The full set of rounds was not studied for each European league; nevertheless, any given team faced the same opponents before and after the COVID-19 break, thereby assuring unbiased estimates of HA when both time points are compared. Furthermore, the crossover design associated with this "natural experiment" in the 2019/2020 season implies that each individual team serves as its own matched control, obviating the need for additional procedures to control for confounding variables of HA, such as team ability, quality of opposition or travel distance/fatigue. Other potential confounding variables such as local derbies, new coaches, within-week matches, time of the match, altitude and fitness levels Points (n) Number of points won per match played at home. Goals Scored (n) Number of goals scored per match played at home. Goals Conceded (n) Number of goals conceded per match played at home. Number of attempts to score a goal, made with any (legal) part of the body, either on or off target per match played at home. Number of attempts to score which required intervention to stop it going in or resulted in a goal/shot which would go in without being diverted per match played at home. Mean of the duration when a team takes over the ball from the opposing team without any clear interruption, as a proportion of total duration when the ball was in play in home matches. Pass Success (%) Mean percentage of attempted passes that successfully found a teammate in matches played at home. Aerial Duels Won (%) Mean percentage of headers won in direct contests with an opponent in matches played at home. Number of actions for dispossessing an opponent, whether the tackling player comes away with the ball or not, per match played at home. Number of disciplinary cards (yellow and red) received by players per match played at home. and SDPre the pre-COVID-19 standard deviation. where r is the ES estimate for the Wilcoxon signed-rank test, Z the z-score produced by SPSS and N the number of total observations on which Z is based. The interpretation of ES relied on the benchmarks proposed by Cohen [26] : small, d = 0.2 or r = 0.1; medium, d = 0.5 or r = 0.3; large, d = 0.8 or r = 0.5. The level of significance was set at p ≤ 0.05. were recently demonstrated not to influence the HA in "ghost matches" of the German Bundesliga [23] . The data were primarily verified through descriptive statistics (means, standard errors of the mean or standard deviations). To visualise the pre-and post-COVID-19 break differences, error bars adjusted for repeated-measures designs were computed for each league and for all five [25] . The effects of the COVID-19 situation on HA and home performance-related variables were examined through paired t-tests. The assumption of normality was verified for each dependent variable, as the difference between Post and Pre conditions, using Shapiro-Wilk (n < 50) and Kolmogorov-Smirnov tests, and by checking if skewness and kurtosis z-scores fell between -1.96 and 1.96. If the normality assumption was violated, the non-parametric Wilcoxon signed-rank test was applied. The existence of HA before and after COVID-19 was examined for each league and for all five through one-sample t-tests comparing the observed HA with a null value of 0% indicating no HA. Once again, the assumption of normality was ascertained before applying the above-stated procedures. The effect sizes (ES) were calculated for the one-sample t-test, paired t-test and Wilcoxon signed-rank test employing equations 2, 3 and 4, respectively, as suggested by Field [25] : where d expresses Cohen's d measure of ES, M the sample mean, μ the population mean (0%), and SD the sample standard deviation. 19 .36%), which may be due to short-term fluctuations that have been proved to occur in a league [6, 19, 27] . The hypothesis of the HA disappearing in European professional football raised by early data [1, 23] was not confirmed. Despite a subtle decrease provoked by the packet of measures applied to control the pandemic, the HA effect has endured when considering the whole sample. This finding sustains the robustness of the HA phenomenon, which has been documented since the inception of organised football [17] . By analysing each domestic league, our results provided further evidence that the COVID-19 situation induced a significant and large effect on the HA of the Bundesliga. In short, the HA disappeared in the German major league, a fact mainly attributed to the striking drop in the stadium occupancy rates, but which was not reproduced in the divisions immediately below [23] . Hence, the supposition of an equivalent decreasing trend across all five European leagues was rebutted. Although the crowd influence was rated one of the leading causes of HA by football players, coaches and fans [11, 12] , our findings do not completely endorse such perceptions. The crowd may exert a direct influence on players, by encouraging their team and/or by intimidating the opposing one, and indirectly operate by interfering with the referees' decisions [3, 4, 10] . Apart from the effect of "ghost matches" in the Bundesliga, the HA remained stable or even increased in the other leagues during COVID-19 times, when matches were played in empty stadiums. Similar results were recently observed at lower levels of German professional football [23] , whilst prior evidence revealed that home teams participating in Italian leagues still had an advantage in matches contested without spectators [18] . These facts are reinforced by studies that have failed to prove the HA is enhanced with larger attendance [8, 15, 16] . Regarding regularity, the role of crowd support is at least questionable, because it appears to vary depending on the contexts in which the game is played [4, 10, 19] . The temporal dispositions may alter the HA in a sporting context [6, 17] . Interestingly, Fisher and Haucap [23] found that the initial tremendous negative effect of "ghost matches" on the HA of [11, 12] . There is a close relationship between HA and home performance; therefore, it would be expected to find some modifications in the performances of home teams following the COVID-19 interruption. Overall, significant decreases were observed for total shots, tackles [11, 14] . The decremental post-COVID-19 trend observed for home tackles (and cards in two leagues) indicates that the public may be a potential mediator of players' aggressiveness, which ultimately had an impact on goals conceded and on match outcome as well. These results tend to support the view that successful football teams sustain their defensive performance through actions aiming to (re)gain the ball directly from the opponents [28] . In addition, the crowd support did not seem to bias the referees' decision-making in favour of home teams in major European leagues [8, 29] . So far, the differences in HA and home performance-related statistics have been exclusively discussed based on a unique factorcrowd support. Any match outcome or team performance is determined by a myriad of factors, many of them difficult to control for. Through a regression analysis, Fisher and Haucap [23] revealed that the "ghost game" effect on HA was quite insensitive to the inclusion whereas the role of crowd support seems to be susceptible to the context characteristics in which football is played, the augmented interference of coaches in players' behaviours during "ghost matches", along with the inclusion of five substitutions and "cooling breaks", might have diluted the crowd effect on the expression of HA. No potential conflict of interest was reported by the authors. hypothesis [29] . Augmented interference of coaches in players' actions during competitive matches, by means of audible verbal instructions, tactical adjustments during stoppages and substitutions, might have diluted part of the advantage typically attributed to home teams. This exploratory study provided another piece for the complex HA puzzle; nonetheless, we are aware that the statistical analysis employed, which was previously called "naive" [23] , has limitations concerning the explanation of mechanisms underlying the HA. Since the HA is a multifactorial phenomenon, related data should be treated as such using multivariate statistical procedures and, preferably, controlling for confounding variables as covariates (e.g., team ability, stadium capacity and occupancy, fitness data and number of substitutions made before and after the COVID-19 break). Future studies should seek empirical validation for our findings by applying multivariate analyses, including away performance-related statistics, and expanding the comparison between pre-and post-COVID-19 periods to different European and non-European domestic leagues, international club tournaments (e.g., UEFA Champions League) and national team events. 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