Women's Football and Bias: When 'That Shot Was Irrational' Becomes a Measure of Truth

On July 3, 2026, I sat in the press room of Rostov Arena, Russia, as one of only seven female data journalists accredited for the World Cup. The match between Japan and Belgium had just ended. Japan led 2-0, then lost 2-3. The room buzzed with talk of Japanese fighting spirit. I opened my laptop and entered raw data from FIFA's tracking system. Japan generated 1.2 xG in the first 45 minutes, but after Marouane Fellaini came on in the 65th minute, Belgium won 14 of 18 aerial duels. I wrote an analysis based on xG and duel data. A veteran editor dismissed my piece with a single sentence: 'Women looking at football data only pick numbers that suit them.' I published the article on a regional sports digital daily. It reached over 200,000 reads. But that wasn't what mattered. What mattered was that from that night on, I understood one thing: Data has no gender, but those who read data have biases.

That was the beginning of a journey lasting nearly a decade, where I learned to let numbers speak for themselves instead of letting emotions lead. In women's football, this is even more difficult. Because even the most basic metrics like xG, PPDA, or dangerous attack counts are often overlooked in women's football coverage. People talk about 'spirit,' about 'effort,' about 'inspiration.' But very few talk about how the Vietnam women's team reduced their PPDA from 14.2 to 10.8 over their last three matches in the 2026 Olympic qualifiers.

When I began following women's football seriously in 2026, I noticed something strange: advanced metrics were virtually nonexistent in women's football coverage. While men's football was flooded with xG, xA, progressive passes, women's football remained trapped in the language of emotion. Journalists covering women's football often described plays with words like 'brilliant,' 'extraordinary,' 'unbelievable.' They didn't write: 'This shot had an xG of only 0.04, but the player chose a position 0.12 better than the horizontal pass.'

This difference isn't just a matter of language. It reflects a deeper bias: Women's football is seen as the domain of emotion, while men's football is the domain of reason. When a male player shoots from distance, people analyze the angle, the power, the goalkeeper's position. When a female player shoots from distance, people talk about 'belief' and 'character.' Both are true, but only one is considered 'professional analysis.'

This leads to a serious consequence: transfer decisions, tactical decisions, and investments in women's football are often based on gut feeling rather than data. A female goalkeeper with a low penalty save rate but 'credibility' in the locker room will be prioritized over a young goalkeeper with better reflex metrics. A female striker who scores few goals but runs a lot will be praised more than a striker who scores many goals but participates less in overall play.

I remember the case of the Vietnam women's team in the 2026 Olympic qualifiers. In three matches against Nepal, Afghanistan, and Palestine, the Vietnam women's team made clear tactical changes. The team's PPDA dropped from 14.2 in the first match to 10.8 in the third. This means the team pressed more aggressively, won the ball faster. But in post-match reports, most journalists focused only on the scoreline and descriptions of goals. No one mentioned PPDA. No one analyzed why the Vietnam women's team changed their pressing approach.

When I wrote an analysis of this change, a male colleague told me: 'You analyze women's football as if it were men's football.' I asked back: 'So how should women's football be analyzed?' He was silent. That was the clearest answer showing that bias still exists.

But there's an interesting paradox: Raw data doesn't care about gender. When I calculate xG for a shot, I don't need to know if the player is male or female. When I measure sprint speed, I don't need to know which league the player plays in. Data is data. The problem lies in how we interpret data.

In women's football, there's a strange trend: analysts often compare female players to male players. 'She runs like Mbappé,' 'She shoots like Ronaldo.' These comparisons are not only technically meaningless but also reflect lazy thinking: Using men as the standard to evaluate women.

I once heard a commentator say about a female player: 'She has the speed of a male player.' I wondered: Which male player? The one who runs 100m in 10 seconds or the one who runs in 13 seconds? And why don't we compare her to another female player in the same position?

This leads to an even more serious consequence: Women's football metrics are often undervalued because they are compared to men's football metrics. A female striker who scores 20 goals in a season in the national league might be seen as 'inferior' to a male striker who scores 20 goals in the Premier League. But if we evaluate her based on expected goals (xG), chances created, or conversion rate, we'd get a completely different picture.

In the 2026-2026 season, I followed the Vietnam women's national league. A player I'll call N.T.H. (for privacy reasons) scored 18 goals in 14 matches. The number sounds impressive. But when I calculated, her xG was only 12.4. This means she scored 5.6 more goals than expected. This is an important metric: her ability to convert chances is above average. But no one mentioned this. No one analyzed why she could score more than her xG. Was it because she positioned better? Was it because she had better finishing technique? Or was it simply luck?

I spent three weeks rewatching all her goals. The result: She had a tendency to shoot from positions with low xG but harder for goalkeepers to save. Specifically, 60% of her goals came from shots outside the box, where average xG is only 0.06. But her conversion rate in these positions was 22%, much higher than the league average of 8%. This is an important insight: She is not just a good striker, but a striker capable of creating quality shots from positions that seem non-threatening.

But this insight would never appear in sports coverage. Because it requires time, effort, and most importantly, respect for women's football.

In men's football, analyzing a player who scores more than his xG is normal. People call it 'elite finishing ability.' In women's football, the same thing is rarely noticed. Journalists often just write: 'She scored 18 goals in 14 matches. How wonderful!' And that's it.

But there's a deeper paradox: If we don't analyze women's football with data, we will never understand its true value. And if we don't understand its true value, we will never invest properly. And if we don't invest properly, women's football will remain trapped in a vicious cycle of neglect.

Investors don't invest in emotions. They invest in data. They want to know: Does this player have growth potential? Can this team attract audiences? Can this league be profitable? These questions cannot be answered by talking about 'spirit' and 'effort.' They need to be answered with xG, with PPDA, with attendance figures, with ticket revenue.

I don't deny the role of emotion in sports. Emotion is an integral part of football. But emotion should not be the only tool for evaluating women's football. xG doesn't replace emotion, it explains why our hearts race.

When I watch a women's football match, I still feel nervous when the home team attacks. I still scream when there's a goal. I still feel sad when the home team loses. But I also open my laptop and enter data. I want to understand why the home team won. I want to understand why the home team lost. And I want to share those insights with readers.

That's why I'm writing this article. Not to prove that women's football is better than men's football. But to prove that women's football deserves to be analyzed as seriously as men's football. People call it a shock, I call it unread data.

Over the past three seasons, I've collected data from over 200 women's football matches in Vietnam and Southeast Asia. I've calculated xG for over 5,000 shots. I've tracked PPDA for over 50 teams. And I've realized one thing: Women's football is not inferior tactically. Women's teams have tactical systems no less complex than men's teams. They press, they defend in blocks, they transition. It's just that no one bothers to take the time to analyze.

This isn't just a media problem. It's a problem of an entire culture. We are taught that men's football is the norm, women's football is the exception. We are taught that when a male player plays well, it's due to technique and tactics. When a female player plays well, it's due to spirit and luck. These biases are deeply ingrained in our subconscious and affect how we perceive everything.

But bias can be broken. And the best way to break bias is with data. Data doesn't care about gender. Data doesn't care about skin color. Data doesn't care about nationality. Data only cares about truth.

Numbers are asceticism: you must abandon ease to see the truth.

I know some will read this article and say I'm 'overcomplicating' women's football. That women's football should be 'enjoyed' rather than 'analyzed.' But I disagree. Enjoyment and analysis are not mutually exclusive. You can enjoy a symphony while analyzing its structure. You can enjoy a painting while analyzing its technique. Why can't you enjoy a women's football match while analyzing its tactics?

For the next seven seasons, I will continue to follow women's football. I will continue to collect data. I will continue to write analysis. Not because I want to prove I'm right. But because I want to contribute to a culture where women's football is evaluated fairly like men's football. Age is the only variable that never lies. And the age of Vietnam women's football is at its most vital stage. Don't let bias blind us.