Student Capstone: Is football commentary racially biased?

Alex's undergraduate research explored unconscious racial bias in football commentary. Specifically, whether darker-skinned players are more likely to be described in terms of physical attributes like pace and power, while lighter-skinned players are more often praised for intelligence, decision-making and leadership.

To investigate it, he used a mixed-methods approach combining natural language processing, data science, computer vision and qualitative analysis. He found further evidence that these patterns persist, and that darker-skinned players were described using more generic language, while lighter-skinned players were characterised more as individuals.

The research has since reached over 1.3 million people across Instagram and YouTube, generating more than 1,000 comments and a conversation that's still growing, especially now, with the World Cup final approaching.

This is what it looks like when rigorous methodology meets genuine curiosity.

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Alex's project is a good example of what the BASc lets students do with a passion that doesn't fit neatly into one subject. He didn't have to choose between studying football and studying racial bias, or between the technical work of building AI models and the critical thinking needed to interpret what they show. The degree's structure, built around interdisciplinary methods rather than a single discipline, meant he could bring computer science, data analysis, and social science together to interrogate something he actually cared about. That's the pitch behind the BASc more broadly: whatever you're passionate about, whether it's sport, cities, science, or humanities, there's likely a way to study it that doesn't force you to leave half your interests at the door.

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Explore the BASc here.

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Citations:

’Racial Bias in Football Commentary’ by Danny McLoughlin, (2021).
Dataset from 1,100 match highlights from GOAL dataset by Allessandro Suglia et al (2022).