A dossier labeled 'football' with not a single player: The verification problem in sports media

There is a dossier thousands of words long, labeled 'football.' It has a table of contents split into nine sections, tables, rows of carefully numbered evidence, and even a glossary explaining technical terms — xG, xA, PPDA, FFP, PSR — abbreviations only insiders would bother to define for outsiders. But as I followed line after line, from the first to the last, I met no stadium. No player. No coach. No club. No match, no card, no goal, not even an empty substitute's bench. All that lay inside was a state visit between the two largest economies in the world: meetings about trade, technology, supply chains, rare earths, artificial intelligence. And at the end of every section, where tactical analysis, club finance, and transfer-market analysis should have been, everything was returned to the same cold sentence: 'Insufficient information, cannot assess.' To someone who has spent forty-three years reading, watching and writing about sports, that sight was both strange and familiar. Strange, because for the first time I saw a football-labeled document so empty of football. Familiar, because I have too often sat before a news item tagged 'sports,' 'football,' 'transfers,' and discovered nothing football about it except a few names dropped for form's sake. The pitch has no gender, but the gaze given to women on the pitch does. Today I want to talk about something looked at with a similarly crooked eye: the way people label, package and publish sports information. The small labeling error is not an isolated accident. It is a symptom of a larger disease eroding how we consume news. Before I go further, I must be clear about something my trade taught me at twenty-four: do not write before verifying. It is not a slogan for moral decoration. It is a rule of survival. In sport, a wrong number can outlive a right fact. It gets copied, quoted, repeated until no one remembers where it began. What I want to do here is not dissect a diplomatic event. I have neither authority nor interest in that. What I want to do is use that very labeling error as an anatomical slice, to show that our sports media — including Vietnam, where I have lived and worked for five years — is running a machine that people trust more than it deserves. Let me start with the mechanism. A modern sports-news pipeline — whether in a big newsroom or an automated machine — runs through the same stages. Collection: items gathered from agencies, social media, reports, scattered notes. Classification: each item tagged football, basketball, tennis, transfers, or general. Extraction: core facts, people, numbers pulled out. And finally: rewriting and publishing. The problem is the second stage. When you label thousands or tens of thousands of items a day, you cannot read each with human eyes. You rely on algorithms, keywords, probability. So an article about a summit — where two leaders discuss technology, trade, things that sound very 'modern' — can be innocently tagged 'sports' by a machine. Or 'football,' for reasons no one knows. One small classification error, and an entire chain of consequences behind it. When the mislabeled item passes to extraction, the machine tries to find players, teams, scores. It finds nothing, because there is nothing to find. Then there are two endings. One is the honest ending of the document I read: the machine truthfully says it lacks information, that nothing can be assessed. The other is far more dangerous: the machine invents. It takes scattered fragments — a country's name, a date, a phrase about 'supply chains' — and stitches them into a football story that sounds plausible. A story wholly untrue. I have seen the second ending too often. And each time, I remember a fateful morning in Nha Trang. It was 2026. I arrived at the newsroom with a thick file on a women's football final at a regional games. A male editor looked at my file and said: 'Women should only write about locker-room stories. Leave tactics to men.' I did not argue. I nodded, stood up, and returned to my desk. For three weeks, I did the only thing I believed had power: I counted. I replayed the match until numbers jumped out of my head. Vietnam's women's team made three hundred and twelve passes. Their opponent had one hundred and ninety-eight. In a 3-5-2, the attacking midfielder operated almost every build-up down the left, and the opponent's defence — strong in physique but slow in the moment of turning — was stretched to collapse in the second half. I wrote a five-thousand-word piece. When it ran, it caused controversy. But it forced the man — and other male colleagues — to fall silent. Not because I was louder, but because I had evidence they lacked. I tell that story not to boast. I tell it to say: evidence is not decoration. Evidence is what turns writing into truth instead of a balloon inflated with air. A missed shot can teach us more than a title, if we look into our own holes. And the biggest hole in sports media today is not a lack of passion, but a lack of rightly placed trust. Back to the production mechanism. I spoke of classification. But there is another, quieter stage, before everything begins: source-checking. In the document I read, I counted twenty-one information points. For nineteen of them, the 'source' field was blank. Only two — precisely the two about a treasurer reading a statement — noted who the speaker was. Meaning: if I wanted to verify almost the entire document, I would have no scrap of paper to start from. To someone like me, that is a catastrophe. In my work, source is everything. When I write about a transfer figure, I must know where it comes from: a media house with real reporters, an agent with a motive to exaggerate, or a social account with no profile. Each source has a different trust level. When I write about an achievement, I must cross-check it against the original footage, not another's summary. Because another's summary is where errors breed. In 2026, I remember the day I understood this to the bone. It was a World Cup. I stood in a radio booth, one of the few Vietnamese women reporters sent to cover it live. While commentating, I mispronounced a midfielder's name three times. The audience laughed. Mocking comments arrived faster than the fastest move of the match. I could have made excuses. Instead, I spent the following month re-watching all sixty-four matches. I noted the pronunciation of seven hundred and thirty-six players. I built my own archive, sorted by country, position, and reading. At the end of that year, I published an analysis of the correlation between passes and goals at the tournament. And many — even those who had laughed — read it and nodded. Equality is not about flattening passion, but about everyone's right to burn fully for it. I burned a whole month spellings names, not for revenge, but to prove that carelessness is no one's gender privilege. Since then, every time I write, I follow a ritual: re-watch footage at least twice, check foreign spellings three times, cross-check every number with official sources. At the end of each piece, I attach my data sources so readers can verify. Colleagues call it strictness. I call it the minimum. But wait. I am drifting from my starting point. Let me return to the labeling error, and to the bigger question: why does it matter to an ordinary fan in Nha Trang, Hanoi, or Can Tho, who just wants their team's result? The answer: fans do not read in a vacuum. They read to decide. They decide whom to trust, whom to dislike, whom to defend, what to buy, and which story deserves a place in their lives. Every piece of information joins that wheel, whether from a famous newsroom or an automated machine with no editor, and leaves a trace. When a mislabeled document is published, the trace left is not one wrong event, but a germ infecting the cache of every search system. Those systems cannot tell right labels from wrong ones. They only count. If content is tagged 'football' and pushed onto platforms, it gets recommended to people searching football. Then one day, someone looking for a match meets an article about a diplomatic meeting, with a note that 'insufficient information for sports analysis.' That tiny germ, if it multiplies, creates an unclean sports database. And an unclean database feeds every subsequent error. It is like a funnel. But wait. I must be careful. I must not fall into the habit of denouncing a shadowy force sabotaging information, because the truth is not that simple. The labeling error comes from no malicious hand. It comes from many unconscious hands. From the laziness of habit, from the pressure of speed, from the naive belief that a machine learns faster than a person, from the public's ever-hungrier demand for instant information, and from newsrooms' burning wish to appear first, even by seconds. When I write about women's football — my chosen field — I see this more clearly than anywhere. Because news about women's football often has fewer sources. When sources are scarce, people tend to magnify small fragments. A match in a distant women's championship, with no high-quality footage, no full official statistics, no large reporting corps — its story is far more easily built on fragile shards. And those shards, when wrongly assembled, are often left uncorrected, because no one seems to care enough to spend effort proving them wrong. That is why I always start with footage. A tape does not know your name. It does not know if you are male or female, old or young, famous or unknown. It only has images. And the image, in its rawest form, is the most democratic evidence there is. The pitch has no gender, but the gaze given to women on the pitch does. I said this first in a piece about male commentators who always say a female player 'plays like a man' whenever she plays well. That compliment sounds pleasant, but inside it is a trap. It implies that 'good' is a masculine property. That a woman, to be praised, must become a copy of a man. This trap repeats at every layer of the news industry. In tactical frameworks, women's football is often bundled into a separate section with less deep data. In transfer pieces, a female striker's fee is often mentioned as a side detail, not a value index. In monthly best-player lists, female players appear later and fewer. No one in the decision room says 'keep women out.' But if you count, you see the absence distributed very evenly, very patiently, as if programmed. And I will count. I will always count. Frighteningly, this pattern appears not only in old newsrooms. It appears in new automated systems. Let us talk about AI, because here the story gets interesting. When a machine is taught that 'football' means articles containing match, player, transfer keywords, and when it is trained on a dataset built mainly from men's football news, that machine learns a distorted definition. It looks at a summit item about technology and says 'this might be sports,' because it was never taught that sport and politics are different fields to separate. And it looks at a poorly known women's football league and says 'this doesn't look much like football,' because in its training data such items were too rare to form a pattern. So the supposedly neutral machine inherits the full bias of its teachers — only it does not know how to question itself. A person can look at a mislabeled item and wonder. A machine does not wonder. It only runs. And it runs very fast. This is why I hold that the era of automated sports information does not erase the need for humans, but places them in a more important position — as gatekeepers. At that gate, your job is not to write, but to refuse. To refuse to publish unverified content. To refuse to pass a mislabeled item downstream. To refuse to turn an unsourced name into a fact. I ask myself: if that gate existed everywhere, would the document I read today have been born? Probably not. It would have been blocked at the entrance, returned to its proper label, and routed to another track, where international-relations researchers would read it with the professional eye and respect it deserves. Because that document, as a record of a diplomatic event, does have content. It is just that — a record of a diplomatic event, not a football analysis. A seat worthy of the work. That is all I need for myself, and all a right item needs — a right place in the classification system. Now I want to say something that may annoy some colleagues. This labeling error is no earth-shattering secret. It will not collapse the sports industry. It will not make any team lose another match. But it matters because it belongs to a far more dangerous class of error — what I call the 'silent error.' Loud errors are easy to spot. If a paper wrongly reports a star's transfer, within hours thousands will shout, and the error is fixed. If a commentator names a team wrong, viewers message at once. The loud error carries its own voice, and that voice calls for correction. Silent errors differ. It is a mislabeled item drifting into the system unnoticed. It is a number copied from an unclear source, repeated until it becomes truth. It is a blank framework, an empty source field, a definition pushed out of scope without argument. And because it is silent, no one fixes it. It exists. It accumulates. And one day it becomes the foundation for a decision — a coach's, an investor's, a fan placing faith in a false number. When global leagues paused in the pandemic, I sank into anxiety. I face anxiety by researching, so I launched a project: collecting data from eight hundred and ninety matches across five European leagues before the pandemic, and two hundred and seventy-eight matches played in fan-less bubbles. I wanted to answer a seemingly simple question: when the stands are empty, what remains of home advantage? The result stunned me. Home advantage fell by about sixty-one percent without fans. Not slightly. Nearly two-thirds. I wrote a piece titled 'The Fortress of Twelve Men Has Fallen,' published in a sports-science journal. Many coaches began consulting it when calculating away tactics. Without fans, home is just an address on a map. I tell this to stress: when I say data can teach us what no one expects, I am not joking. A right number, handled right, can overturn a belief an entire industry has carried for decades. But a wrong number — a silently transmitted, unchecked number — has power too. It can reinforce a bias, create a phantom market, turn an ordinary player into a pitiable figure or a good player into a suspect. And here I must say a word about pity. In twenty years writing about women's football, I learned a hard lesson: never pity a female player. Do not write about them as sufferers. Do not tell their stories as tragedies needing sympathy. Because pity is the most toxic soft power. The one who pities stands above. The pitied is imprisoned in a lower status. And once imprisoned, their achievements, however great, are seen through the lens of 'after all, she is admirable for overcoming adversity.' I do not want to read about a female player as a victim. I want to read about her as a player. I want her passes counted. Her tackles measured. Her running distance charted and compared with male players in the same position. Because the pitch does not distinguish gender. The scoreboard does — but it distinguishes with numbers, not with bias. We watch a World Cup to see football, but I watch to inspect the lens people wear when they look at me. Each time I re-watch a match, I do not only watch the match. I watch how people tell it. I watch the words chosen. I watch the tone. I watch how a great move by a female player is described — with adjectives, or with verbs. Adjectives are vague. Verbs are concrete. 'She ran' is more concrete than 'she was brave.' 'She passed the ball to position X' is more concrete than 'she was clever.' And I realized the whole labeling error I am discussing is also a form of vagueness. A wrong label is vagueness institutionalized. It is lazy. It has not read to the end. It hastily names something it does not understand. Let me be more direct. There is a paradox no one likes to mention: while organizations believe they are speeding up to serve the public, the public is losing the ability to tell truth from the appearance of truth. No one wants this. Writers do not. Readers do not. System operators do not. But it happens, persistently, every day, between names read right and names read wrong, between a verified number and a guessed one. I see this most clearly in these days, as the big season approaches and the atmosphere around national teams burns like fire. That is when people most want to believe, and most can be deceived. A name mentioned in the wrong place can live forever online. A rumor about a lineup can worry millions. And amid it all, people still read, still share, still argue. I do not write this to appear noble. I write it because I love this trade, and love, by a strict definition, does not allow us to close our eyes. So what should be done? First — and this I want newsrooms to carve into their hearts — check before writing, not write then check. This order cannot be reversed. The labeling error occurred precisely because someone did the reverse: classified first, understood later, and by the time the truth surfaced, it was too late to turn back. Second, for readers — especially women's football fans in Vietnam, who have endured much historically overlooked — do not trust a number just because it comes from a seemingly big source. Check the source. Find its origin. If a piece says a player has a certain index, ask who measured it and how. A demanding fan is a better-served fan, because their demands force the writer to be rigorous. Third, for those building automated systems — build gates. Add refusal filters. Let the machine be able to say 'I do not know' instead of being forced to say 'it is.' Because the ability to say 'I do not know' is a sign of maturity, not weakness. And finally, let data do the work it does best: break biases. I once wrote a five-thousand-word analysis of a women's football final, just to prove a woman could understand tactics more deeply than a male editor. It was a small victory, and I realized I had not needed to do it. I had not needed to prove. I only needed to write, and let quality speak. But in an environment that assumes I must prove, proving becomes a duty. And I fulfilled that duty, not with passion, but with forty-seven metrics. That is how I fight — with numbers that cannot be argued. And that is how I advise anyone facing doubt: do not argue, count. But be careful. Counting has its own trap. There is a temptation a researcher like me faces often, and I must speak honestly about it, because I see its shadow in my own writing: the tendency to turn anxiety into tables of numbers. When I cannot control my emotions, I plunge into data. I collect, classify, compute, until emotion is buried under a mountain of figures. This mechanism helps me control, but it can also turn my writing into a soulless machine. And if I am not careful, I can cram until the reader understands nothing but numbers. That is why after every data passage, I always insert a single personal observation. One sentence. One image. One moment standing in the stands. Because a number, however important, needs a human hand to guide. A machine can produce a perfect table, but it cannot tell you the feeling of standing in rain when your team wins. And perhaps that is the final boundary between human and machine. I have attended eight Olympics. Covered eight World Cups. Sat on the great roads of Italy and France to watch cyclists cross mountain passes I would never dare dream of. Those forty-three years taught me that sport is not only numbers on a board. It is stories told in sweat and tears. But those stories, however beautiful, must be told on a foundation of truth. Otherwise we build castles on sand. Once more, back to the football-labeled document. The biggest question it puts to me is not 'how to fix it' — that is easy. The biggest is: how many other documents are drifting out there, carrying similarly wrong labels I do not know about? I have no answer. But I know this: each of us — writer, reader, sharer — is responsible for the labels we receive. Every time we share information without checking, we stick another wrong label on the wall. Every time we say 'it is said that,' we help the silent error multiply. Believing in numbers is not believing in big things. It is believing in verified things. It is telling a name read right from a name read wrong, as I had to learn to pronounce seven hundred and thirty-six players' names in a month, because I did not want my audience to laugh at me again. Paddling in data does not make me great. It only makes my work less wrong. And in this trade, being less wrong is a high enough standard. So, as the big season nears, and newsrooms everywhere prepare for the hottest days, I want to send my colleagues, especially the young, a small message: do not start with a conclusion. Do not start with a label. Do not start with a headline designed to bait. Start by sitting down, re-watching the footage, and asking: will what I am about to write stand before an angry reader? I ask that of myself every day. And I want you to ask it of yourself. Because in the end, the labeling error I dissected here is not a story about a broken machine. It is a story about us. About how much we respect the truth. About whether we have the patience to read a piece to the end, watch a match to the end, hear a name to the end before writing it down. About whether we have the courage to say 'I do not know' instead of 'it is.' I have spent more than four decades learning this. And I am still learning. In the trade I chose, where numbers are disputed and labels wrongly applied, I have found a great comfort: the truth is never in a hurry. It is quiet, and it is durable. It can be buried under millions of items for years. But it will be there, waiting for someone to verify it. And when someone does — a writer, a reader, a properly taught machine — it shines again. That is why I still write. Not because I want to prove I am right, but because I believe verification is an act of care. Care for readers. Care for players, especially women, who deserve to be seen with the eye of truth rather than pity. Care for the trade I have held nearly all my life. A wrong label can be fixed in a minute. But a habit of verification takes a lifetime to build. I choose to build it every day, one piece at a time, one number at a time, because I know that at the other end of the page there is a reader who trusts. And their trust, once stolen by carelessness, is hard to return. That is what I want to say. The rest, I leave to the numbers.