International Journal of Performance Analysis in Sport
ISSN: 2474-8668 (Print) 1474-8185 (Online) Journal homepage: http://www.tandfonline.com/loi/rpan20
Global differences in home advantage by country, sport and sex Richard Pollard, Jaime Prieto & Miguel-Ángel Gómez To cite this article: Richard Pollard, Jaime Prieto & Miguel-Ángel Gómez (2017): Global differences in home advantage by country, sport and sex, International Journal of Performance Analysis in Sport, DOI: 10.1080/24748668.2017.1372164 To link to this article: http://dx.doi.org/10.1080/24748668.2017.1372164
Published online: 13 Sep 2017.
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Date: 14 September 2017, At: 09:01
International Journal of Performance Analysis in Sport, 2017 https://doi.org/10.1080/24748668.2017.1372164
Global differences in home advantage by country, sport and sex Downloaded by [Biblioteca Universidad Complutense de Madrid] at 09:01 14 September 2017
Richard Pollarda, Jaime Prietob and Miguel-Ángel Gómezc a
Department of Statistics, California Polytechnic State University, San Luis Obispo, CA, USA; bDepartment of Musical and Corporal Didactics, Complutense University of Madrid, Madrid, Spain; cFaculty of Physical Activity and Sport Sciences, Polytechnic University of Madrid, Madrid, Spain
ABSTRACT
The purpose of this study was to use a multivariate approach to investigate variations in home advantage between different team sports and between different countries both for men’s and women’s competition. The data were based on the domestic premier leagues of 15 sports in 65 countries worldwide, over a 5-year period from 2011 to 2015 with a total of 1952 league tables qualifying for inclusion. After controlling for differences in competitive balance between the leagues, a general linear model found significant differences between sports, between countries and between sexes. Quantifying home advantage as the proportion of total points won by the home team in a league, basketball and handball were highest for both men and women. For men, Bosnia-Herzegovina had by far the greatest advantage with other Balkan nations well above average. Rugby union in France was the domestic league in which playing at home provided the most advantage. The results suggested that the pace of a sport and the dimensions of the playing area might both be having an effect on home advantage.
ARTICLE HISTORY
Received 26 July 2017 Accepted 24 August 2017 KEYWORDS
Sport; home advantage; sex; country
1. Introduction Home advantage (HA) in sport is a well-established phenomenon documented by a large and ever-growing literature. Studies have analysed different sports competitions in both individual and team sports, with professional European and North American team sports leagues forming the main foundations from which the HA effect has been investigated (e.g. Doyle & Leard, 2012, in ice hockey; Jones, 2015, in baseball; Pollard & Gómez, 2013, in basketball) and especially multiple studies in football (e.g. Jacklin, 2005; Pollard & Gómez, 2014a). The vast majority of these studies have focused on men’s leagues, with only a very few of them analysing women’s competitions or comparing results between men and women. To avoid confusion when comparing the results from North American and European studies, we will use the European terms of football, American football and ice hockey rather than their respective North American equivalents of soccer, football and hockey.
CONTACT Miguel-Ángel Gómez © 2017 Cardiff Metropolitan University
[email protected]
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R. POLLARD ET AL.
Overall, a considerable decline in HA since the 1980s has emerged, with the major team sports all showing their lowest ever figures during the last two decades (Pollard & Gómez, 2009; Pollard & Pollard, 2005). Researchers have proposed different causes that might explain this fact and also relate to the main factors associated with the existence of HA. These are crowd effects, travel effects, familiarity, referee or judging bias, territorial protection, playing tactics, rule changes and psychological aspects (Pollard, 2008).The majority of HA studies have tended to consider each factor in isolation when attempting to explain HA (e.g. Agnew & Carron, 1994; crowd effects; Pace & Carron, 1992, travel effects; Neave & Wolfson, 2003, territoriality; Boyko, Boyko, & Boyko, 2007, referee bias). However, determining how these factors operate and the way in which they affect performance is still unclear. There is little consensus as to the specific manner in which they contribute to the HA effect, which is currently considered more and more as a multifactorial phenomenon that has a variety of interacting causes and contributing factors (Balmer, Nevill, & Williams, 2003; Pollard, 2008). A few previous studies on HA in different sports and in different countries provided a background against which to set the study. The most comprehensive of these comparing different sports was a meta-analysis performed by Jamieson (2010) in which 10 sports, seven of them team sports, were considered, but for men only, and almost all data related to competition in North America, mostly baseball, ice hockey, basketball and American football. This was augmented by a few football leagues from England, rugby union and Australian rules football from Australia and cricket from England. Regular season games as well as play-off games were included, as were both collegiate and professional competition. Data were collected for different time periods, going back over 60 years for some sports. Although this study provided a useful resource for referencing previous research on different sports, the analysis consisted of a series of univariate tests. Since the sports being analysed differed from each other in terms of the mix between regular season and play-off games, between levels of competition and between time eras, any of which could have had a confounding effect on HA, inferences about differences between sports were open to question in the absence of a more global multivariate approach. Jamieson concluded that HA in football (mostly from England) was significantly higher than in any other sport. The pitfalls of Jamieson’s analysis were avoided in a comprehensive study of HA in nine different team sports in Spain (Gómez, Pollard, & Luis-Pascual, 2011). Not only was the analysis confined to a single country, but it was also carried out over the same five-year time period (2005/2006–2009/2010) and consisted only of the regular season games in each sport and at the same level of competition, the premier national league for each sport. Thus, any difference found between sports could be attributed to aspects of the sports themselves and not to confounding factors. In all sports, home teams did significantly better than those playing away. HA was highest for rugby union with 67.0% of all points gained being won by the home team. This method of quantifying HA has been much used in the past and will be adopted for comparisons in this introduction. Gómez, Lago-Peñas, and Pollard (2013) compared HA for the major sports of North America and England for the five years up to 2012, producing average annual HA values for baseball (55%), basketball (60%), American football (57%), ice hockey (54%) and football in England (62%). Over a similar time period, HA in professional lacrosse in North America was found to be 57% (Pollard & Gómez, 2015). In an interesting discussion of the relationship between the structure of various team sports and HA, Jones (2015) noted that baseball was a team sport that was essentially a
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INTERNATIONAL JOURNAL OF PERFORMANCE ANALYSIS IN SPORT
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series of contests between individual players. The same can be said for cricket, both sports having low HA. He also showed that for specific individual actions in team sports, such as taking a free-throw at basketball, or a penalty shot at football or ice hockey, HA vanishes. He argued that the main factor driving HA was impaired teamwork among away players and that sports in which teamwork was especially important, such as football, would have the highest HA. In an attempt to explain the difference in HA between football (high), baseball (low) and American football and basketball (intermediate), Tsonis and Tsonis (2001) introduced the concept of “information transfer”, based on both the frequency of stoppages in a game and the extent to which player substitutions are allowed, both situations during which coaches can interact with players. Information transfer is minimal in football, virtually unlimited in baseball and intermediate in the other two sports, reflecting exactly the gradient found in HA. Few studies have been designed specifically to look at differences in HA between countries. Pollard (2006a) compared HA in the football leagues of 72 countries, an analysis that was subsequently broadened to 157 countries worldwide (Pollard & Gómez, 2014a), based on six seasons between 2006 and 2012. Large differences were found, ranging from 86% in Nigeria, through a pocket of high values throughout the Balkan countries, down to no HA in a handful of small nations. Significant factors associated with countries with high HA included distance travelled, altitude, a recent civil war and the perception of corruption (all p
