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Belgium has consistently produced world-class footballers, outperforming many larger football associations despite having a smaller talent pool and fewer resources. This paper aims to (1) examine the development pathways of Belgian professional players over the past decade and (2) quantify the role of opportunities in European leagues outside the “Big 5” for a comparative analysis of different player development systems. By exploring how Belgian players progress through various leagues and systems, this study seeks to identify strategic insights that can inform the development practices of both Belgian football and other European nations with similar constraints.

Data on player performance were collected over ten seasons (2013/14 to 2022/23) from 15 European leagues, including the “Big 5” (England, France, Germany, Italy and Spain) and ten other prominent leagues (Austria, Czech Republic, Denmark, Greece, Netherlands, Poland, Portugal, Scotland, Switzerland and Turkey). The variables collected included player name, nationality, team, league, season, appearances, minutes played, age and position. For Belgian players in the sample, the youth academies they attended were also noted.

Belgian players have achieved significant success, particularly in terms of transitioning into the “Big 5” leagues. However, the number of “home-grown” players making appearances and gaining minutes in the Belgian league is relatively low (ranking 13th of the 15 leagues studied). In contrast, Belgian players rank third in terms of total minutes played in the “Big 5” leagues, behind Portuguese and Dutch players. Anderlecht was the most successful Belgian club in developing professional players, and other key contributors were clubs with consistent Champions League participation.

While substantial research exists on player development in the “Big 5” European leagues, comparatively little attention has been given to other significant European leagues. This paper addresses that gap by examining the role of smaller leagues in developing young talent, despite their limited resources and reduced access to Europe's elite competitions. The findings highlight the need for policy reforms and strategic improvements at both the national and European levels to enhance player development pathways.

This study examined differences related to gender and racial/ethnic identity among academic researchers participating in the National Science Foundation’s “Innovation-Corps” (NSF I-Corps) entrepreneurship training program. Drawing from prior research in the fields of technology entrepreneurship and science, technology, engineering and mathematics (STEM) education, this study addresses the goal of broadening participation in academic entrepreneurship.

Using ANOVA and MANOVA analyses, we tested for differences by gender and minoritized racial/ethnic identity for four variables considered pertinent to successful program outcomes: (1) prior entrepreneurial experience, (2) perceptions of instructional climate, (3) quality of project team interactions and (4) future entrepreneurial intention. The sample includes faculty (n = 434) and graduate students (n = 406) who completed pre- and post-course surveys related to a seven-week nationwide training program.

The findings show that group differences based on minoritized racial/ethnic identity compared with majority group identity were largely not evident. Previous research findings were replicated for only one variable, indicating that women report lower amounts of total prior entrepreneurial experience than men, but no gender differences were found for other study variables.

Our analyses respond to repeated calls for research in the fields of entrepreneurship and STEM education to simultaneously examine intersecting minoritized and/or under-represented social identities to inform recruitment and retention efforts. The unique and large I-Corps national dataset offered the statistical power to quantitatively test for differences between identity groups. We discuss the implications of the inconsistencies in our analyses with prior findings, such as the need to consider selection bias.