Home Team Advantage Research Articles

Can awareness reduce (and reverse) identity-driven bias in judgement? Evidence from international cricket

Competitions often suffer from biased judgments by officials tied to their social identities. In international cricket, home nation umpires favoured home teams, but neutral umpires were introduced successfully to address this bias. However, the COVID-19 pandemic prompted the return of home umpires, creating a natural experiment amid heightened scrutiny, modern technology, and sometimes empty stadiums. Consistent with the predictions of our behavioural model, we find no evidence of in-group bias during the pandemic; instead, we observe evidence of over-compensation. The pre-pandemic home team advantage in ‘leg before wicket’ decisions vanished, with home umpires seemingly favouring the away opposition, compared with neutral umpires in the period before, especially in more marginal or difficult decisions. This suggests that awareness and scrutiny can not only eliminate identity-driven judgement bias but may even reverse it.

Multivariate Conway-Maxwell-Poisson Distribution: Sarmanov Method and Doubly Intractable Bayesian Inference

ABSTRACT In this article, a multivariate count distribution with Conway-Maxwell (COM)-Poisson marginals is proposed. To do this, we develop a modification of the Sarmanov method for constructing multivariate distributions. Our multivariate COM-Poisson (MultCOMP) model has desirable features such as (i) it admits a flexible covariance matrix allowing for both negative and positive nondiagonal entries; (ii) it overcomes the limitation of the existing bivariate COM-Poisson distributions in the literature that do not have COM-Poisson marginals; (iii) it allows for the analysis of multivariate counts and is not just limited to bivariate counts. Inferential challenges are presented by the likelihood specification as it depends on a number of intractable normalizing constants involving the model parameters. These obstacles motivate us to propose Bayesian inferential approaches where the resulting doubly intractable posterior is handled with via the noisy exchange algorithm or the Grouped Independence Metropolis–Hastings algorithm. Numerical experiments based on simulations are presented to illustrate the proposed Bayesian approach. We demonstrate the potential of the MultCOMP model through a real data application on the numbers of goals scored by the home and away teams in the English Premier League from 2018 to 2021. Here, our interest is to assess the effect of a lack of crowds during the COVID-19 pandemic on the well-known home team advantage. A MultCOMP model fit shows that there is evidence of a decreased number of goals scored by the home team, not accompanied by a reduced score from the opponent. Hence, our analysis suggests a smaller home team advantage in the absence of crowds, which agrees with the opinion of several football experts. Supplementary materials for this article are available online.

A LONGITUDINAL INVESTIGATION OF CROWD DENSITY AND THE HOME COURT PHENOMENON IN THE WOMEN’S NATIONAL BASKETBALL ASSOCIATION

<p>The home team advantage has been extensively documented and studied in many team sports, especially men’s basketball leagues. In contrast, research that has examined the home court advantage in women’s basketball leagues could not be found. Therefore, this study was designed to answer the following questions: (1) is the home court advantage present in the woman’s national basketball association (WNBA)? (2) is there a relationship between crowd density and referee bias in favor of the home team in the national woman’s basketball league? (3) is there a relationship between crowd density and home team performance in the woman’s national basketball league? The study at hand employed a longitudinal study approach to examine 5 regular seasons (2015-2019) of 10 WNBA teams. Data for fan attendance, sport arena capacity, and box scores were collected from public domains. Statistical calculations and analysis were used to compare chosen box scores between the home team and away team. Similarly, chosen box scores were compared between home games that had a crowd density above 50% and home games that had a crowd density below 50%. The results of this study showed that the home court advantage was present in the woman’s national basketball league. In contrast to research studies that examined referee bias in men’s basketball leagues, the results of this study are conflicting and inconclusive. However, home games that had crowd density above 50% significantly outperformed home games that had crowed density below 50%, both offensively (p=0.003) and defensively (p=0.002).</p><p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0337/a.php" alt="Hit counter" /></p>

Improving PageRank using sports results modeling

How to rank participants of a sports tournament is of fundamental importance. While PageRank has been extensively used for this task, the algorithm’s superiority over simpler ranking methods has never been clearly demonstrated. We address this knowledge gap by comparing the performance of multiple ranking methods on synthetic datasets where the true ranking is known and the methods’ performance can be thus quantified by standard information filtering metrics. Using sports results from 18 major leagues, we calibrate a state-of-art model, a variation of the classical Bradley–Terry model, for synthetic sports results. We identify the relevant range of parameters under which the model reproduces statistical patterns found in the analyzed empirical datasets. Our evaluation of ranking methods on the synthetic datasets shows that PageRank outperforms the benchmark ranking by the number of wins only early in a tournament when a small fraction of all games have been played yet. Increased randomness in the data due to home team advantage, for example, further reduces the range of PageRank’s superiority. We propose a new PageRank variant that combines forward and backward propagation on the directed network representing the input sports results. The new method outperforms PageRank in all evaluated settings and, when the fraction of games played is sufficiently small and the sport is not too random, it outperforms also the ranking by the number of wins. Beyond the presented comparison of ranking methods, our work paves the way for designing optimal ranking algorithms for sports results data.

A Machine Learning Approach to Analyze Home Advantage during COVID-19 Pandemic Period with Regards to Margin of Victory and to Different Tournaments in Professional Rugby Union Competitions.

Home advantage (HA) is the tendency for sporting teams to perform better at their home ground than away from home, it is also influenced by the crowd support, and its existence has been well established in a wide range of team sports including rugby union. Among all the HA determinants, the positive contribute of the crowd support on the game outcome can be analyzed in the unique pandemic situation of COVID-19. Therefore, the aim of the present study was to analyze the HA of professional high-level rugby club competition from a complex dynamical system perspective before and during the COVID-19 pandemic. HA was analyzed in northern and southern hemisphere rugby tournaments with (2013–2019) and without (2020/21) crowd support by the means of the exhaustive chi-square automatic interaction detection (CHAID) decision trees (DT). HA was mitigated by the crowd absence especially in closed games, although differences between tournaments emerged. Both for northern and southern hemisphere, the effect of playing without the crowd support had a negative impact on the home team advantage. These findings evidenced that in ghost games, where differences in the final score were less than a converted try (7 points), HA has disappeared.

Predicting Match Outcomes in the English Premier League: Which Will Be the Final Rank?

In any sport competition, there is a strong interest in knowing which team shall be the champion at the end of the championship. Besides this, the end result of a match, the chance of a team to be qualified for a specific tournament, the chance of being relegated, the best attack, the best defense, among others, are also subject of interest. In this paper we present a simple method with good predictive quality, easy implementation, low computational effort, which allows the calculation of all the interesting quantities above. Following Lee (1997), we estimate the average goals scored by each team by assuming that the number of goals scored by a team in a match follows a univariate Poisson distribution but we consider linear models that express the sum and the difference of goals scored in terms of five covariates: the goal average in a match, the home-team advantage, the team’s offensive power, the opponent team’s defensive power and a crisis indicator. The methodology is applied to the 2008-2009 English Premier League.

Home Team (Dis)Advantage Patterns in the National Hockey League: Changes Through Increased Emphasis on Individual Performance With the 3-on-3 Overtime Rule.

Past research examining National Hockey League (professional ice hockey; NHL) data from the 4-on-4 overtime era (seasons between 2005-06 and 2013-14) revealed an inconsistent home team (dis)advantage pattern such that home teams that were superior to their visiting counterparts had slightly greater odds of winning during regulation play compared to overtime (demonstrating home crowd advantages for team performance during regulation); in contrast, home teams experienced lower odds of winning in the shootout period than in overtime regardless of team quality (thereby demonstrating risks for individual choking from home crowd pressures). In this study, we explored the NHL home (dis)advantage pattern during four more recent seasons (2015-16 through 2018-19) in which the league instituted 3-on-3 play during overtime (perhaps increasing individual pressure for athletes competing in the 3-on-3 overtime period). We used archival data from the regular season (N=5,002 games) to compare home teams' odds of winning in regulation (with 5-on-5 skaters per team) to overtime (with 3-on-3) and in the shootout, adjusting for the quality of home and visiting teams. We conducted fixed-effects and multi-level logistic regression modeling. Evenly matched home teams were 1.66 times more likely to win than inferior home teams when games concluded in regulation versus overtime. Superior home teams were 4.24 times more likely to win than inferior home teams when games concluded in regulation rather than overtime. Thus, it is apparently more difficult for superior and evenly matched home teams to win in overtime than during regulation, suggesting that such home teams may be susceptible to choking in overtime. In contrast to the earlier 4-on-4 overtime era, home teams did not have lower odds of winning in the shootout compared to overtime. These results may have implications for NHL coaches' and players' tactical decision-making.

The influence of the video assistant referee on the Chinese Super League

With the development and advancement of technology, various types of high-tech auxiliary equipment have been gradually introduced into football matches to assist referees to officiate the game. The Chinese football Super League (CSL) introduced the video assistant referee (VAR) in the 2018 season. The purpose of this study is to explore the impact of the introduction of VAR on football matches and on referees’ performance. This study compared the data of all 240 games without VAR in the season 2017 and all 240 games with VAR in the season 2018 using Generalized Linear Model (GLM) and means comparison. The following match variables were considered: goals, penalties, red cards, yellow cards, fouls, offsides, playing time in the first half, playing time in the second half and total playing time. The study found that: 1) After the introduction of VAR, the number of offsides and fouls in the Chinese Super League dropped significantly (p < .001); 2) the playing time in the first and second half and the total playing time increased significantly(p < .001); 3) after the introduction of VAR, the home team advantage decreased slightly. The research result can help to better understand the impact of VAR on professional football, especially on the Chinese football Super League, it can also help referees to optimize their refereeing strategy.

Fans and Match Results: Evidence From a Natural Experiment in Brazil

This paper assesses the effect of the crowd size on home team advantage, using a natural experiment occurred in Brazilian football. In 2015, the Brazilian Football Confederation (CBF) quasi-randomly assigned games to be played under an alternative schedule on Sundays at 11 a.m. This measure significantly increased attendance in assigned games. Using this alternative schedule as an instrumental variable, we show that the exogenous increase in attendance did not increase home team advantage.

Home team advantage in the English Premier League

The home team advantage in association football is a well known phenomenon. The aim of this paper is to offer a different view on the home team advantage. Usually, in association football, every two teams—team A and team B—play each other twice in a season. Once as a home team and once as a visiting, or away team. This gives us two results between teams A and B which are combined together to evaluate whether team A, against its opponent B, recorded a result at its home ground—in the comparison to the away ground—that is better, even, or worse. This leads to a random variable with three possible outcomes, i.e. with trinomial distribution. The combination and comparison of home and away results of the same two teams is the key to eliminate problems with different squad strengths of teams in a league. The bayesian approach is used to determine point and interval estimates of unknown parameters of the source trinomial distribution, i.e. the probability that the result at home will be better, even, or worse. Moreover, it is possible to test a hypothesis that the home team advantage for a selected team is statistically significant.

Sport analytics for cricket game results using machine learning: An experimental study

Indian Premier League (IPL) is one of the more popular cricket world tournaments, and its financial is increasing each season, its viewership has increased markedly and the betting market for IPL is growing significantly every year. With cricket being a very dynamic game, bettors and bookies are incentivised to bet on the match results because it is a game that changes ball-by-ball. This paper investigates machine learning technology to deal with the problem of predicting cricket match results based on historical match data of the IPL. Influential features of the dataset have been identified using filter-based methods including Correlation-based Feature Selection, Information Gain (IG), ReliefF and Wrapper. More importantly, machine learning techniques including Naïve Bayes, Random Forest, K-Nearest Neighbour (KNN) and Model Trees (classification via regression) have been adopted to generate predictive models from distinctive feature sets derived by the filter-based methods. Two featured subsets were formulated, one based on home team advantage and other based on Toss decision. Selected machine learning techniques were applied on both feature sets to determine a predictive model. Experimental tests show that tree-based models particularly Random Forest performed better in terms of accuracy, precision and recall metrics when compared to probabilistic and statistical models. However, on the Toss featured subset, none of the considered machine learning algorithms performed well in producing accurate predictive models.

한국프로농구에 있어서 홈 팀의 이점에 대한 경기력 요인의 추정

한국프로농구 (Korean basketball league; KBL)에서 홈 팀의 이점이 있다는 사실은 잘 알려져 있다. 하지만 그 중요성에도 불구하고 홈 팀의 이점을 이해하는 데 도움이 되는 계량화된 연구는 많지 않다. 본 연구에서는 KBL 팀들의 최근 4시즌의 경기 결과를 이용하여 홈경기의 이점이 어떤 형태로 나타나는지를 살펴보았다. 그 결과 승률의 측면에서는 95% 팀들의 홈 승률이 전체 승률보다 평균 9% 높았으며 대부분 기록이 홈경기에서 우수했다. 또한 홈 팀과 원정팀의 포인트 차를 3점 슛 시도, 어시스트, 블록, 파울, 실책, 전체리바운드, 공격 리바운드 및 수비 리바운드의 차로 설명하는 회귀모형을 제안하였으며, 제안된 모형은 홈 팀의 이점을 여러 가지 상황에서 계산할 수 있으며 또 승패를 87% 예측할 수 있었다.

Predicting Final Result of Football Match Using Poisson Regression Model

In any sport competition, there is a strong interest in knowing which team shall be the champion at the end of the championship and one of the sports is football. Football match predictions are of great interest to fans and sports press. In the last few years, it has been the focus of several studies. In this paper, the researchers propose Poisson regression model to predict the final result of football matches. The researchers predicted the average goals scored by each team by assuming that the number of goals scored by a team in a match followed a univariate Poisson distribution. Poisson regression model was formulated from four covariates: the goal average in a match, the home-team advantage, the team’s offensive power, and the opponent team’s defensive power. The methodology was applied to the 2017-2018 English Premier League. The results obtained using this model had a fairly good accuracy.

Home Field Advantage Calculation for Physical Education and Sport Students

It is a well-established fact that playing at home field is an advantageous condition for professional sport teams. For this reason, the home field advantage in team sports is an important issue to be explored. It is also one of the different topics that physical education and sports students can use when they want to perform performance analysis on various sports branches in the future. The concept of home field advantage is determined by the ratio of the points the teams get from matches played at home field compared to the overall points obtained at the end of the season. Only when this advantage ratio is over 50% can we talk about such a benefit. The aim of this study is to show students how to calculate home field advantage in football in the physical education and sports departments in universities with Turkish Super League example. For this reason, 30 seasons and n = 18,052 matches from 1987 to 2017 were analyzed. Data were obtained from tff.org, Turkey Football Federation's official website. According to the results obtained, home-playing teams were found to score over 50% in the light of all seasons analyzed. In the study, the mean home team advantage was found to be 61.4 ± 2.95%. When the literature is examined, it presents similar results with this study. At the end of the study, it was also found that there are different variables by which both the home playing team and the visiting team are influenced when determining the home advantage.

Home advantage in professional soccer: Analysis of Turkey 1. league<p>Profesyonel futbolda ev sahibi olma avantaji: Türkiye 1. liginin analizi

In the present study, it was aimed to analyze the home team advantage in 1st Football League of Turkey. Obtained by examining the scores of matches played in 10 seasons (2005/2006-2014/2015), the study data were analyzed in terms of certain technical parameters such as number of games won as home team and guest team, home team advantage by the seasons and teams. The data obtained were entered to SPSS 16.0 software, and the frequency and percentage values were calculated and then interpreted. In totally 3062 matches played during 10 seasons, the number of matches won by home teams was 1319 (43.07%), whereas the number of games lost by home teams was found to be 886 (28.93%). During 10 seasons of 1st Football League of Turkey, the home team advantage was calculated to be 61.10%, whereas the mean home team advantage values of teams listed in 1st Football League of Turkey within this period were calculated to vary between 48.95% and 85.71%. Mean home team advantage of teams, which completed the seasons as the champion, was calculated to be 56.40%, whereas the same rate was found to be 61.23% for the teams that were dropped from the league. In conclusion, in terms of the home team advantage, the results obtained for 1st Football League of Turkey were in harmony with the literature; thus, it can be stated that the points won in away matches are an important criteria for having a successful season by winning more points. Extended English abstract is in the end of PDF (TURKISH) file. ÖzetBu çalışma, Türkiye Futbol 1. Liginde, ev sahibi olma avantajının incelenerek analiz edilmesi amacıyla yapılmıştır. On sezonluk zaman diliminde (2005/2006-2014/2015) oynanan müsabakaların sonuçları değerlendirilerek elde edilmiş olan araştırma verileri, takımların ev sahibi ve deplasman takımı olarak maç kazanma sayıları, sezonlara ve takımlara göre ev sahibi olma avantajları gibi teknik parametrelerin analizi yapılarak incelenmiştir. Elde edilen veriler SPSS 16.0 programında kaydedilmiş, frekans ve yüzde değerleri hesaplanarak yorumlanmıştır. İncelenen on sezonda oynanan toplam 3062 maçta, ev sahibi takımların galibiyet sayıları 1319 (%43.07) olurken, mağlubiyetle sonuçlanan maç sayısı 886 (%28.93) olarak belirlenmiştir. Türkiye Futbol 1. Liginin incelenen 10 sezonunda ev sahibi olma avantajı ortalaması %61.10 olarak belirlenirken, Türkiye Futbol 1. Liginde bu zaman aralığında mücadele eden takımların ev sahibi olma avantajı ortalamalarının %48.95 ile %85.71 aralığında değiştiği tespit edilmiştir. Bir sezonu şampiyon olarak tamamlayan takımların ev sahibi olma avantajı ortalamaları %56.40 olarak bulunurken, küme düşen takımlarda ise bu oranın %61.23 olduğu belirlenmiştir. Sonuç olarak, ev sahibi olma avantajı açısından Türkiye Futbol 1. Liginde de literatüre benzer sonuçlara ulaşılmasından hareketle, futbolda daha fazla puan sahibi olarak başarılı bir sezon performansı ortaya koyabilmek için deplasmanda kazanılan puanların da hedefe ulaşmada çok önemli bir kriter olduğunu söylenebilir.

Decision-making of English Netball Superleague umpires: Contextual and dispositional influences

ObjectivesThe decisions made by officials have a direct bearing on the outcomes of competitive sport contests. In an exploratory study, we examine the interrelationships between the decisions made by elite netball umpires, the potential contextual and environmental influences (e.g., crowd size), and the umpires' dispositional tendencies – specifically, their propensity to deliberate and ruminate on their decisions. Design/MethodFilmed footage from 60 England Netball Superleague matches was coded using performance analysis software. We measured the number of decisions made overall, and for home and away teams; league position; competition round; match quarter; and crowd size. Additionally, 10 umpires who officiated in the matches completed the Decision-Specific Reinvestment Scale (DSRS). ResultsRegression analyses predicted that as home teams' league position improved the number of decisions against away teams increased. A model comprising competition round and average league position of both teams predicted the number of decisions made in matches, but neither variable emerged as a significant predictor. The umpire analyses revealed that greater crowd size was associated with an increase in decisions against away teams. The Decision Rumination factor was strongly negatively related to the number of decisions in Quarters 1 and 3, this relationship was driven by fewer decisions against home teams by umpires who exhibited higher Rumination subscale scores. ConclusionsThese findings strengthen our understanding of contextual, environmental, and dispositional influences on umpires' decision-making behaviour. The tendency to ruminate upon decisions may explain the changes in decision behaviour in relation to the home team advantage effect.

New Insights Involving the Home Team Advantage

Although the home team advantage is known to exist in many sports, there are nuances of the advantage that are less well understood. In this paper, we investigate various aspects of the home team advantage including changes in the advantage over time, the relationship of the advantage to the overall scoring rate and differential advantages within leagues. The analysis is mainly based on descriptive statistics and is confined to the home team advantage pertaining to the National Hockey League and the National Basketball Association.

How cann soccer improve statistical learning?

This paper presents an active classroom exercise focusing on the interpretation of ordinary least squares regression coefficients. Methodologically, undergraduate students analyze Brazilian soccer data, formulate and test classical hypothesis regarding home team advantage. Technically, our framework is simply adapted for others sports and has no implementation cost. In addition, the exercise is easily conducted by the instructor and highly enjoyable for the students. The intuitive approach also facilitates the understanding of linear regression practical application.

Rugby League in Australia between 2001 and 2012: An Analysis of Home Advantage and Salary Cap Violations

Within this paper, we review whether incidences of salary cap circumvention within the Australian professional rugby league competition led to improved home team wins during the period between 2001 and 2012. In doing so, we show that while the salary cap breach amounts can be attributed to an improved home team win record in the case of the Melbourne Storm, success during the period can also be attributed with other factors such as the management of the club, talent identification and the quality of the coach and/or captain. This raises an important issue surrounding the effectiveness of a salary cap to create a level playing field when uncertainty over the quality and performance of players exists. A notable role of the salary cap violations was the retention of a core group of players that were instrumental in the success that occurred in the 2007 season. As part of the analysis we also review home team advantage. A focus on the NRL is justified due to the peculiar nature of having multiple stadium types within the same city and team. For the year 2012 we find that a match at a traditional Sydney stadium against a non-Sydney team had the highest probability of a home team win when the two teams have had a similar level of success during the season.

There's no place like home: home court advantage in North American sports leagues

We use a measure of home team advantage (HTA) that allows us to examine its relative strength across dissimilar sports leagues. Our metric confirms the widely reported existence of HTA. We control for relative team strength, thereby allowing comparisons across leagues. We find the strongest HTA in the National Basketball Association, followed by the National Football League and Major League Baseball in decreasing order.