The Data Gap in Women's Football: When the Analysis Board Returns Empty Cells

On the night of March 12, I reopened the analysis spreadsheet for a women's match in the Frauen-Bundesliga. The xG column was empty. The PPDA column was empty. The high-press minutes column was empty. My finger rested on the keyboard as I waited for a number to appear, but the screen only returned blank cells. The match had been played in full ninety minutes: twenty-two players, more than a thousand passes, fourteen set pieces, three substitutions per side. All of it existed on the pitch. It was simply that no one had recorded any of it as data.

I went back to the video I had filmed myself from the stands, slowed it down, rewound each phase again and again, and filled those empty cells by hand. A match that professional stat systems returned as "insufficient information" could be fully reconstructed with an old laptop and patience. That is the paradox I face almost every week.

People told me I did not understand women's football. I opened Excel, entered the data, and rewrote it. But this time it was the data itself that refused to appear. And when an in-depth analysis board, with all nine dimensions from tactics to finance, from governance to media, is forced to write "insufficient information" in every cell, the problem is not the match. The problem is how we decide what deserves to be recorded.

Context

In 2026, at sixteen, I happened to watch a match involving the FC St. Pauli women's team in Hamburg. They lost 0-5. The stands thinned out from the seventieth minute, but I stayed until the final whistle, noting fourteen tactical fouls and spotting a pattern: every goal conceded came from the gap between full-back and centre-back. A 0-5 defeat is not about the loser, but about the one who dares to stay and watch until the final minute. That night I understood that to read women's football, I had to create my own data, because the available data barely existed.

Afterward I dug through ten more Frauen-Bundesliga matches, used spreadsheets to analyse pressing schemes, and taught myself tactics from video without any guidance. In 2026, when the men's World Cup in Russia took place, I watched while trying to apply the tactical principles from that St. Pauli match to the German women's national team, launched the blog "Women's Data Lab," and wrote a series comparing Germany women's pressing with Spain men's. The first post drew a comment: "You have never played women's football, how dare you analyse it?" I did not get angry. I replied with a number: 78% of Germany women's goals conceded in 2026 came from set pieces.

By 2026, when competitions paused for COVID-19, I was nineteen. The stadiums were empty, but I did not panic. I downloaded forty Women's Champions League matches from 2026-2026, wrote Python scripts to analyse the average positions of central midfielders such as Amandine Henry and Dzsenifer Marozsán, and published for free an open dataset on 350 European women players. An editor at the online magazine "Fussball im Norden" found it, got in touch, and invited me to contribute.

Looking back, I realise one thing: every turning point in my career came from filling a data gap. When others looked away, I recorded. When the system returned a blank cell, I filled it myself. But at some point, filling every cell by hand becomes an individual burden, no longer the responsibility of an entire industry.

The history of women's football is a history of being struck from the record. In 2026, the English FA banned women's teams from playing on men's club grounds, a ban that lasted nearly fifty years. Throughout that time, thousands of women's matches were played before tens of thousands of spectators, yet almost no official records were kept. When the ban was lifted, history had to be rebuilt from photographs, memories, and short notices in local papers. Today's data gap is the echo of yesterday's data gap.

Men's football has dozens of data providers; each match is tracked by multi-angle camera systems, each pass is given coordinates, each shot is assigned an xG within seconds. Women's football, in most competitions, still relies on one person typing by the touchline, or on no one at all. Women's football is not a smaller version. It is a world with its own rules — and the first of those rules is: if no one records it, it does not exist in any analysis board.

That is precisely why a nine-dimension analysis report, however carefully designed, can return entirely empty cells when applied to women's football. Not because the method is wrong, but because the input is starved.

Core Analysis

I want to walk through each dimension of that framework, not to describe it, but to show how each empty cell corresponds to a concrete reality on the women's pitch.

The tactical dimension is where the gap is most visible. In men's football, xG and PPDA are almost the default language. In women's football, they are usually absent. I once tried to calculate PPDA for a Women's Champions League quarter-final and had to time each pressing sequence with a stopwatch over video, because no source provided it. When I published the result — the away side pressed less but more effectively in the opponent's half — no one could verify it, because there was no reference data. A correct analysis that cannot be cross-checked is still treated as non-existent.

In this dimension, the absence of data creates a double consequence. First, fans have no tool to understand the match beyond the scoreline. Second, women's coaches themselves lack data for comparison. I once spoke with an assistant coach in the German women's second division; she said that to analyse opponents she had to watch video manually because professional data packages were too expensive for the club's budget. The data gap is not only a journalist's problem. It is a competitive disadvantage.

In the Frauen-Bundesliga, some matches have basic data such as possession and shots, but positional data is rare. Without positional data, we cannot know how far forward a full-back pushed, how deep a defensive midfielder dropped, or which gap a forward moved into. I once redrew a women's team's formation by plotting coordinates by hand on screenshots, which took nearly four hours for a single match. In men's football, similar data is available within minutes of the final whistle.

The finance and transfer market dimension returns similarly empty cells. Men's football has Transfermarkt valuations for every player, broadcasting revenue reports, and public wage bills in many leagues. Women's football mostly does not. I once tried to determine the transfer fee of a prominent women's forward and found only estimated figures in the press, with no clear origin. When there are no numbers, every debate about market value becomes pure sentiment.

This is the point I consider most important. When revenue and wages are not published, people easily come to believe that women's football creates no value. A lack of transparency is mistaken for a lack of value. But if we look at rising attendances and streaming views in several women's leagues, we see that the problem lies in recording and disclosure, not in demand.

Even when a women's club wants to disclose its finances, it struggles because most women's teams belong to men's clubs, so the figures are merged and cannot be separated. A women's team may contribute ticket and shirt revenue, but that number disappears in the consolidated report. As a result, the commercial success of women's football becomes invisible even when it exists.

The results and opinion-cycle dimension depends entirely on match data. To know whether a team is overloaded or recovering, we need minutes played, distance covered, and rest days between matches. In women's football, these metrics usually exist only in the big leagues; elsewhere they are zero. I once tracked a women's team through three matches in seven days and wanted to prove they declined due to the schedule, but there was no fitness data to prove it. A correct argument without evidence is easily dismissed as a mere complaint.

The league landscape and team positioning dimension is the same. To compare squad value, academy output, or financial strength between women's clubs, we need data that most leagues do not publish. As a result, every comparison rests on feeling. A team is considered strong because they win, not because we understand why they win.

The rules and governance dimension also leaves many cells empty. Regulations on financial fair play, transfer registration, and competition eligibility in women's football are rarely publicised and rarely analysed. When a women's club faces a licensing problem, information often arrives late and lacks detail, making it hard for fans to grasp the substance of the matter.

The management and dressing-room dimension is even harder to access. Women's football has few dedicated beat reporters, so stories about coach-player relations, generational transition, and leadership structures inside the squad are seldom recorded. I once received a thank-you email from a player's assistant after I wrote about Kosovare Asllani's injury at the Tokyo 2026 Olympics without fabricating anything. She said it was rare for anyone to verify before writing about a women player. That was both a compliment and a warning about the standards of an entire industry.

The risk dimension also returns empty cells in its own way. With no financial data, no fitness data, and no contract data, risk cannot be assessed. But the biggest risk lies in the lack of data itself: when no one measures, no one detects early signs of decline in a club, a league, or a generation of players.

The media narrative and expectation dimension is where data and opinion meet. When baseline numbers are missing, the media easily falls into two extremes: over-praising a single win, or ignoring an entire process. I once saw a women's team called a "phenomenon" after two wins, then forgotten after three defeats. Both reactions lacked foundation, because no one had data to place the results in context.

At Women's Euro 2026, the final at Wembley drew more than 87,000 spectators, a record for a women's European Championship final. At the 2026 Women's World Cup, total attendance surpassed one and a half million. These numbers prove that demand exists. But they also reveal an asymmetry: large figures at event level are recorded, while smaller figures at weekly match level remain blank.

The industry transmission dimension closes the circle. From the youth academy chain, through the club and competition system, to the broadcasting and commercial markets, every link of women's football lacks the data to measure value flows. As a result, when an investor asks about the potential of women's football, the answer is usually silence.

Reading back over the entire nine-dimension framework with its long stretch of empty cells, I see something like a map drawn in invisible ink. The skeleton is complete, the cells are clearly divided, but the content does not appear. And notably: that map is not wrong. It simply reflects a fact — that we have built sophisticated analytical tools for a world we refuse to record.

In my daily work, I am forced to build my own database. The dataset of 350 European women players I published in 2026 remains one of the few open sources of its kind. I write Python scripts to extract midfielders' average positions, standardise data from many sources, and cross-check every figure before publishing. Data does not lie, but it does not feel pain either. I write to fill the gap between those two things. Because behind every empty cell is a player with a name, an age, and a match that no one saved.

Contrarian Angle

There is a comfortable explanation for this situation: women's football is young, and data will come when the market is big enough. I do not fully believe that argument, and here is why.

The data gap is not a natural consequence of youth. It is the result of choices about resource allocation. The same media group can spend millions on men's football tracking systems and almost nothing on women's, even when both take place in the same time slot. When someone says "there is no data yet," the right question is not "when will the data arrive," but "who decided not to record it."

The counterintuitive part is this: the lack of data is being used to justify itself. Because there are no numbers, people say women's football is hard to analyse. Because it is hard to analyse, they invest less. Because they invest less, there is even less data. This is a self-reinforcing loop, and it operates exactly like the way clubs under financial reporting pressure are forced to prioritise short-term profit over long-term investment. When fans' emotions are turned into cash flow, whatever cannot be measured is deemed unworthy of investment.

But there is a deeper paradox. Women's football, precisely because it has little data, forces the analyst to observe more closely. I have said that a 25-year-old with Python can read a match more clearly than an entire commentary box — not because she is better, but because she is forced to look at each phase instead of reading a ready-made stat sheet. The deficit creates a different kind of expertise: the expertise of the person who measures by hand.

So when a nine-dimension analysis board returns all empty cells, I do not read it as a sign that women's football has nothing to analyse. I read it as evidence that we are measuring the wrong subject, or refusing to measure. Some goals conceded matter more than goals scored, if only someone would write them down. And some matches matter more than any summary table, if only someone would stay until the final minute.

Takeaway

What I want to see in the coming years is not praise for women's football, but full data tables. A women's league publishing every player's minutes. A club disclosing its wage structure. A stats provider willing to track every pass. When the empty cells are filled, we will no longer have to argue about whether women's football deserves to be watched. We will argue about tactics, about fitness, about transfer value — the debates men's football has had for a long time. And by then, the right question will be: who will be the first to record the next match?