Data

Given the previous literature, there are a multitude of different variables worth analyzing, as each one could influence the success of a country’s women’s soccer team in different and potentially revealing ways. In particular, this study looks to the following variables: men’s soccer success, GDP Per Capita, population, gender gap index, women’s rate of participation in government, economic freedom index, and average level of education. Furthermore, we look to the interaction terms between some of these variables, as they may be correlated with one another. A detailed description of each dataset is provided in subsequent sections.

One of the key variables of interest in our analysis is a country’s men’s soccer success. It will be interesting to see if there a relationship between the success of the men’s team and women’s team, as it will speak to whether culture soccer can exist generally, or if countries tend to primarily value only men’s soccer. To measure this variable, we use the FIFA/Coca-Cola world rankings, which assign point values to each team based on their regional and international success. These rankings, much like an ELO ranking, will be used to proxy for men’s team success in our analysis and the women’s version of the rankings will be used to proxy women’s team success.  We have attempted to find indexes and rankings that best quantify the factors that we were interested in and detail all of these decisions in their respective section.

 

Data analysis

We utilize the following regression when conducting our analysis:

The results of the regression are shown above. There are a few things worth noting here. First, the success of a country’s men’s team is both positive and statistically significant, meaning that countries that tend to have better men’s teams are also more likely to have better women’s teams. Women’s participation in government, population and gender gap index also all yielded statistically significant correlations with the women’s FIFA rankings, with all except for population having a positive correlation.  The other factors were not found to be significantly correlated with the Women’s rankings.

In subsequent sections we will dive deeper into each of the variables that we analyzed, looking at how the variable is calculated, how closely it correlates with the nation’s women’s soccer ranking and what this could mean for the factors that lead to successful women’s soccer teams.  We will attempt to include qualitative analysis to add color and eventually make sense of all of the information in the conclusion.

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