Women’s sports are fighting an uphill battle against our social media algorithms

Women’s sport is more and more getting the attention it deserves.

Stadiums are filling^[1], television ratings for many sports are climbing and athletes such as the Matildas’ Mary Fowler, triple Olympic gold medallist Jess Fox and star cricketer Ellyse Perry are becoming household names.

Despite this progress, an invisible threat looms, one that risks undoing years of advocacy and momentum.

That threat is the algorithm.

How sports consumption is changing

As more fans consume sport through digital platforms such as YouTube^[2], TikTok, Instagram and increasingly, AI-curated streaming services such as WSC Sports^[3], the content they see is being selected not by editors but by artificial intelligence (AI).

Algorithms, trained to maximise engagement and profits, are deciding what appears in your feed, which video auto-plays next, and which highlights are pushed to the top of your screen.

But here is the problem: algorithms prioritise content^[4] that is already popular.

That usually means men’s sport.

This creates what researchers call an echo chamber effect^[5], where users are shown more of what they already engage with and less of what they don’t.

In sport, this can be deeply problematic.

If a user clicks on highlights from the AFL men’s competition for example, the algorithm will respond by serving up more men’s footy content^[6].

Over time, content from women’s competitions risks being squeezed out, not because it is unworthy but because it has not yet achieved^[7] the same levels of engagement.

This is not a glitch, it is a structural flaw in how digital platforms are designed to serve content.

It means women’s sport, already underrepresented in traditional media^[8], risks becoming all but invisible to many users in this AI-driven ecosystem.

Also, generative AI tools such as ChatGPT, Sora and others don’t just curate content, they now create it.

Match reports, fan commentary, video summaries and social posts are being generated by machines^[9]. But these systems are trained on historical data, which overwhelmingly favours men’s sport^[10].

So, the more content the algorithm generates, the more it reproduces the same imbalance. What was once human bias is now being automated and scaled across millions of screens.

This may sound abstract, but it has real-world consequences.

Young fans raised on algorithmically curated content are less likely to see women’s sport unless they actively search for it. And if they don’t see it, they don’t form emotional attachments to it.

That has major implications for ticket sales, merchandise, viewership and sponsorship investment.

An uphill battle

In short, visibility drives viability. If women’s sport becomes digitally invisible, it risks becoming financially unsustainable.

A 2024 study in Victoria^[11] shows only around 15% of traditional sports media coverage in the state goes to women’s sport. This mirrors a 2019 European Union study across 22 countries, which found 85% of print media coverage^[12] is dedicated to male athletes.

And while progress has been made, particularly during events such as the FIFA Women’s World Cup or the Olympics, regular, everyday visibility remains an uphill battle.

AI threatens to compound these historic disparities. A 2024 study^[13] found algorithms trained on historical data reproduce and even amplify gender bias.

The very systems that could democratise access to sport content may, in fact, be reinforcing old inequalities.

What can be done?

We can’t turn off the algorithm. But we can hold it to account.

Platforms like YouTube, TikTok and Netflix should be required to undergo independent algorithmic audits.

These would evaluate whether content recommendation engines are systemically under-representing women’s sport and propose changes.

In Europe, the Artificial Intelligence Act^[14], one of the world’s first comprehensive AI regulations, requires transparency and oversight for high-risk AI applications. Australia and other countries should consider similar obligations for content platforms.

Sport organisations and broadcasters need to create intentional pathways for fans to discover women’s sport, even if they haven’t previously engaged with it.

That means curated playlists, featured stories and digital campaigns that surface content outside the fan’s usual algorithmic bubble.

Platforms must balance personalisation with diversity.

We also need better media literacy, especially for younger audiences. Fans should be encouraged to explore beyond what’s served to them, seek out women’s sport channels, and recognise when the algorithm is reinforcing narrow viewing habits.

Teaching this in schools, sport clubs and community programs could make a big difference.

An opportunity for Australia

Australia is well placed to lead this change because our women’s national teams are globally competitive, our domestic leagues are growing and fan appetite is rising.

But without visibility, this momentum can fade. We must remember that algorithms don’t just reflect our preferences, they shape them.

In an age where AI can dictate what we see, the battle for attention becomes even more crucial.

If we want women’s sport to thrive every week, we need to ensure it is seen, heard and valued in the digital spaces where fandom now lives.

Because in the age of AI, what we don’t see may be just as powerful as what we do.

References

1. ^{^} Stadiums are filling (ministryofsport.com)
2. ^{^} digital platforms such as YouTube (www.sportspro.com)
3. ^{^} such as WSC Sports (wsc-sports.com)
4. ^{^} algorithms prioritise content (www.ucl.ac.uk)
5. ^{^} echo chamber effect (doi.org)
6. ^{^} more men’s footy content (www.researchgate.net)
7. ^{^} not yet achieved (doi.org)
8. ^{^} underrepresented in traditional media (changeourgame.vic.gov.au)
9. ^{^} being generated by machines (www.unitedrobots.ai)
10. ^{^} favours men’s sport (arxiv.org)
11. ^{^} study in Victoria (changeourgame.vic.gov.au)
12. ^{^} 85% of print media coverage (www.europarl.europa.eu)
13. ^{^} A 2024 study (dx.doi.org)
14. ^{^} Artificial Intelligence Act (artificialintelligenceact.eu)