Literature Review

Prior to explaining our finding of the determinants of women’s success in international football, it is important to understand contemporary research that has already been done. When looking at the determinants of success in women’s international football, there are many variables that have been found to have an effect. This review will include the findings of Victor A. Matheson, Joshua Congdon-Hohman, Benno Torgler, Robert Hoffmann, Chew Ging Lee, Roberto Gásquez, Bala Ramasamy, and Roberto Panel.

Hoffman, Lee, and Ramasamy are established researchers of the determinants of international soccer success. Their research is focused on performances in the Olympics, for both men and women. They applied an empirical methodology to the analysis of variables that are related to a significant influence of FIFA world rankings. For their research, the authors cross researched 76 teams from the year 2000. The variables examined and tested include GNP per capita (Gross National Product, a measure very similar to GDP), GNP per capita squared, temperature, share of world population, host dummy (if the World Cup has been held previously in a given country), and a Latin dummy variable. The statistics from their research conclude economic, demographic, cultural, and climate variables are significant to the performance of international teams. Also, they found there is an inverted-U shape relationship for temperature and per capita wealth. This means at the temperatures median and the per capita wealth median, soccer performance is at its highest. In nations with extreme temperatures or per capita wealth, soccer performance trends lower. Lastly, the researchers found there is a significant relationship with soccer success when combining population and Latin tradition (a measure of the how ingrained into the culture of the country soccer is in different Latin nations). However, when examined individually, the two variables are insignificant.

Over multiple studies, Benno Torgler analyzed the determinants of performance in football. The author focused on performances on national teams in the 2012 Men’s FIFA world cup. His research included dummy variables as the dependent variables, like winning a match and not winning a match. The independent variable used was the FIFA point rankings. Working with the related variables, determinants of success in a game were defined as shots on goal, possession, sending‐offs, corner kicks, and so forth. The author used a probability selection for 126 countries. The author found the FIFA point rankings are not a good indicator of football performance in a game.  This study does not dive as deeply into factors of a country that indicate likelihood of soccer success, but does show that FIFA rankings do not always accurately reflect the strength of a soccer team.

Torgler also tested the FIFA point ranking with some factors about the country in women’s football. The research focused on 99 countries in 2009. The independent variables included GDP, tradition, population, and temperature.  To quantify tradition, the author measured the historical success of teams. The most important takeaway from this study was his attempt to control for geography using football regions, like confederations. Similar to Hoffman’s review of Lee and Ramasamy, Torgler concluded economy, demography, and tradition are statistically significant determinants of women’s football performance. On the other hand, Torgler failed to find the same inverted U shape relation with per capita wealth. Lastly, Torgler concluded the differences of the determinant geography to be small.

In Torgler’s last study, he tested the previous World Cup final tournament performances from 1930 to 2002 as the dependent variable. By looking at football teams’ performances over time, the author introduces average values of success. For economic and geographic independent variables, he took the averages from 1960 to 2000 and tested the new method across 60 countries. As found in his earlier research, wealth has a positive relationship to performance, population is mainly relevant to Latin countries and tradition is a significant indicator. On the other hand, temperature in a country is found to a bad indicator of performance.

Other researchers like Hoffman ran a similar study to Torgler. Hoffman used a regression model for 88 countries in 2002 for women’s performance and compared it to the male teams. By comparing the two teams, the author is able to test for political and gender related determinants as the independent variables. The most useful information he found was related to the political and gender inequalities between men and women. The research found climate and Latin cultural origin affect men’s performances, while the political system and gender inequalities affect the women’s performances (similar to findings hypothesized in this study). This research is a good representation of the different determinants of success for men and women’s football performance.

On the other hand, Roberto Panel took a different approach. Panel reviewed and analyzed the previous studies and other research surrounding the determinants of women’s soccer. Following the theoretical framework of Bernard and Busse, Panel was able to deliver a sound and consistent result. Panel found GDP per capita is a better socioeconomic determinant of women’s performance in soccer than the Human Development Index. Also, he found the Elo rating to have many advantages over the FIFA Classification in measuring strength of a team. Doing so yielded a list of Panel’s regression estimates over a 33‐year period, representing stronger evidence.  Panel found that variables like economics, demographics, weather, football institutions, and geography are good determinants of performance in soccer. To increase the accuracy of economic data, lagged dependent variables can be used to better account for the persistence of economic influence of a country. Doing so will make a more dynamic model with a fit increase to 96.6 percent.

Lastly, Panel offered some things to consider while conducting additional research. Something to be considered in the future is the influence of migrating football players on a nation’s football performance. However, the research on this effect is still being perfected because it is difficult to analyze indicators of migration and how this affects national teams. Understanding indicators of migration is the next piece of the puzzle of trying to find the determinants of football success.

Limitations:

While much has been done, the research on women’s football has not been perfected. There is still a lot of trial and error done when finding the relevant determinants. Researchers Macmillan and Smith reviewed the work of Hoffman, Lee, and Ramasamy about their sample of population, and FIFA rankings. Macmillan and Smith argue their colleague’s work suffers from statistical problems. First, Macmillan and Smith point out the fact that in the research in question, population only consisted of football players of a given country. Their research struggles significantly because they do not relate their population to the football traditions, or lack thereof, of Latin countries. Football in Latin countries is argued to be a religion, so difference in populations of Latin countries compared to others is significant.  In short, the population of football players in a country is not as important when the whole country is crazy about football.  The method of their population suffers from sample selection bias, because the whole population basically consists of football players. Also, football traditions of Latin countries are not taken into account. In addition, the critics claim the variable, FIFA rankings, is misused. The rankings do not represent a true indication of success because they include the outcomes of friendly matches. International friendly matches do not carry the same incentive to win compared to competitive matches in season. This is just one of many criticisms of the FIFA rankings that has been brought up.

Our research will attempt to build off of the research already done in the space, focusing specifically on the women’s game.  Many of the studies consider men’s soccer, and so largely ignore issues like gender gaps and female participation in government, which we think could be significant to the development of women’s football.

 

Josephine C. Jacobs (2014) Programme-level determinants of women’s international football performance,European Sport Management Quarterly, 14:5,

Robert Hoffmann, Lee Chew Ging, Victor Matheson & Bala Ramasamy(2006) International women’s football and gender inequality, Applied Economics Letters,

Torgler, Benno, The Determinants of Women’s International Soccer Performances. CREMA Working Paper No. 2004-19. Available at

Matheson, Victor A., and Joshua Congdon-Hohman. “International women’s soccer and gender inequality: Revisited.” College of the Holy Cross, Departments of Economics Faculty Research Series, Paper 11-07 (2011)\

Macmillan, T., and I. Smith. 2007. “Explaining International Soccer Rankings.” Journal of Sports Economics8(2):202–13.

Bernard, A. B., and M. R. Busse. 2004. “Who Wins the Olympic Games: Economic Resources and Medal Totals” Review of Economic and Statistics 86(1):413–17.

Gásquez, Roberto, and Vicente Royuela. “The Determinants of International Football Success: A Panel Data Analysis of the Elo Rating*.” Social Science Quarterly, vol. 97, no. 2, 2016, pp. 125–141., doi:10.1111/ssqu.12262.

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