Dataset for field experiments analyzing discrimination in amateur soccer

Area of Science:

• Sociology
• Sports Science
• Economics

Background:

• Discrimination in sports is a pervasive issue, impacting opportunities and participation.
• Amateur soccer provides a unique context to study subtle forms of bias due to its widespread nature and diverse player base.
• Previous research has hinted at ethnic or national origin-based discrimination in various sectors, but comprehensive data from sports is limited.

Purpose of the Study:

• To present a large dataset from field experiments analyzing discrimination in amateur soccer across multiple countries.
• To provide empirical evidence on whether foreign-sounding names affect trial invitations for amateur soccer players.
• To facilitate comparative research on discrimination across different societal domains.

Main Methods:

• The study utilized a field experiment design involving the creation of fake player accounts.
• These accounts, differentiated by native-sounding versus foreign-sounding names, were used to apply for trial practices.
• Data was collected from amateur soccer coaches across 23 countries, forming a dataset of 24,915 observations.

Main Results:

• Analysis of the dataset revealed significant disparities in trial invitations based on the perceived origin of player names.
• Coaches were less likely to invite players with foreign-sounding names for trial practices, suggesting discriminatory behavior.
• The findings highlight a pattern of exclusion affecting individuals with non-native backgrounds in amateur soccer.

Conclusions:

• The data provides robust evidence of discrimination against players with foreign-sounding names in amateur soccer.
• This research contributes to understanding ethnic or national origin discrimination within the sports context.
• The dataset's breadth allows for future comparative analyses with discrimination in fields like migration, economics, and political science.