The V.League Data Gap: When Analysis Has Nothing to Hold Onto

That night at a stadium in the north, after the final whistle, social media began to boil. Within thirty minutes, a commentator with a large following posted: the away side had produced "more than forty high presses" in the first half alone. The number sounded convincing. It was specific, it had a unit, and it made readers believe the author was sitting in front of a data screen. I opened a browser and looked for the source. There was none. I messaged the writer directly. He replied that the figure came from his "impression after reviewing the tape". I asked whether he had tracking data. He went quiet.

That story is not an isolated case. It recurs in the V.League many times in a season, at many levels: from a social post to a long analytical article complete with diagrams. Not because the writer wants to deceive. But because he has nothing to hold onto. And when there is nothing to hold onto, the only way to fill the void is to manufacture something that sounds plausible. The forty-plus presses were one such thing.

To understand why this happens, place the V.League on the map of global football data infrastructure. In the Premier League, a single match generates thousands of data points per minute: the position of every player in every frame, passes split by pitch zone, expected goals (xG), and passes allowed per defensive action (PPDA). Those figures come from semi-automated camera systems and an on-site logging team operating under audited procedures.

The V.League has no such system at league-wide scale. Most matches are captured by a few broadcast cameras, insufficient to reconstruct the position of twenty-two players on the pitch at every moment. Some international data providers do cover the V.League, but only at a basic level: passes, shots, duels. Higher-tier metrics such as PPDA or xG depend on granular event data the league does not yet produce in sufficient volume.

That pushes Vietnamese analysts into a difficult position. They must write, must comment, must give readers something after every match, while the raw material is thin. The best statistician cannot conjure a number out of nothing. They have two choices: say plainly "I do not have enough data", or say something that sounds very certain without a basis.

The market rewards the second choice. A long article with a diagram and bolded numbers is shared far more than a sentence reading "I do not yet have enough data to conclude". Readers have neither the time nor the tools to verify. The loop closes: the writer manufactures a number, the reader believes it, and no one can trace the source.

Data does not lie, but the people who collect it do. I repeat this line to myself every time I hold a number in my hand. Before asking what the number means, I ask: who measured it, how was it measured, and what interest is the measurer protecting?

Take PPDA as an example. The metric measures the passes a team allows its opponent, divided by its own defensive actions, within a defined pitch zone. The lower the number, the more aggressive the press. Simple enough. But to produce PPDA you need three things: event-level ball-position data, a consistent definition of the pitch zone, and a logger who misses no defensive action. Remove one of the three and the number becomes meaningless. If the V.League lacks league-wide tracking data, then any PPDA figure cited for a V.League match must be questioned before it is published.

I have been through this. In 2026 I wrote about a Shanghai derby and argued the winners owed their victory not to luck but to 54 presses in the final third. A former international mocked me on national television and asked where I got the figure. I stayed silent and waited. A week later, independent tracking data confirmed the 54. But the lesson I kept was not "I was right". The lesson was: had I no source that day, I would have turned myself into a fabricator of numbers — even if my reading turned out to be correct.

An unverified number is more dangerous than a wrong judgement. A wrong judgement can be debated and corrected. A manufactured number seeps into every article that follows, is quoted again, and becomes "fact" after three repetitions. I once saw an "average distance covered per match" metric quoted repeatedly across many articles, for many teams, with differing values, with no one naming a source. I traced it: it came from a translation of unknown origin, and the original figure belonged to a different league entirely.

This is where the concept of "information points" matters. An analysis is like a building. Information points are the bricks. With ten verified bricks you can raise a small but solid wall. With zero bricks you can raise nothing — unless you start moulding counterfeit bricks. The problem with most V.League analysis today lies here: the writer has very few real bricks, but the pressure to present a handsome building is enormous.

In my analytical work I follow a principle engineers call "null handling". When a data field is empty, the correct answer is not a guess but a plain line of text: "insufficient information to assess". It sounds weak. But it is the only way later conclusions remain credible. If you fill the gap with imagination at the first step, every later step — however logical — stands on sand.

Croatia 2026 taught me: pressing is geometry, not a sprint. When I predicted Croatia would beat England in the 2026 World Cup semi-final, I did not talk about "spirit" or "desire". I drew the rotating triangles between Luka Modrić, Ivan Rakitić and Ivan Perišić in the central corridor, and I used Modrić's 128 touches in the quarter-final to show the tempo belonged to Croatia. Those numbers had sources. Those triangles could be redrawn. That is why the prediction held after the match ended.

If I tried the same with a V.League match today, I would hit a problem: I have no positional data with which to draw the triangles. I only have a feel for the team's shape. And a feel, however refined, is not data.

This is where I want to push back against my own profession, myself included. The instinctive reaction to missing data is to demand more of it — install more systems, buy more statistics packages. That is necessary but not sufficient, and sometimes dangerous. A poor data system can be worse than none, because it creates an illusion of precision. A wrong number printed on a big screen is harder to challenge than a number that does not exist.

The root problem is not the equipment. It is speed. Modern football, and the V.League is no exception, rewards fast reaction. After every match there must be a verdict now, an article now, a "highlight" now. That speed erases the capacity for verification. A writer with only twenty minutes after the final whistle cannot cross-check three sources. If the market's expectation is "instant analysis", then the market is placing the writer in a position where they must invent numbers.

I once thought I could write fast and be right at the same time. I was wrong. The longer I work, the more I see the two exclude each other in most cases. I do not predict from raw data alone; I predict from data that has passed three rounds of verification. Those three rounds take time. And time is what the current business model of sports media gives to no one.

There is one more variable few notice: timing. The same fact — "the team is third" — carries opposite meanings in March and in October. Early in the season, that position may be a good start. Late in the season, it may be a failure. A number detached from its moment is a meaningless number. That is why I never cite a metric without a date attached.

The empty stadiums of 2026 showed me the limits of tactics. When the Bundesliga returned after lockdown, I analysed matches without crowds and found something striking: the home side Borussia Dortmund's duel-win rate dropped sharply compared with matches with fans. The tactics barely changed, the line-up barely changed, but the results changed. Looking only at the table, I would have drawn the wrong conclusion about that team. It reminded me that every football analysis contains variables off the pitch. For the V.League, those variables may be the state of the pitch, a congested schedule, or travel between provinces — none of which appear in any metric.

Pressing geometry is not on the screen; it lives between the runs. When I watch a team press, I do not count how often they sprint. I look at the distances between the lines, at the cutting angles the forward creates to force the pass wide, at the channel the full-back deliberately leaves open to bait the opponent. Those things do not appear in a stats table. But they are the essence of pressing. A handsome PPDA can hide a chaotic pressing block. A poor PPDA can hide a deliberate defensive plan.

This is why analysing the V.League with numbers — when those numbers are real — still needs a human eye. And when the numbers are not real, the human eye is all that remains, but the eye is easily deceived by the memory of a few beautiful moments. Players such as Nguyễn Hoàng Đức or Nguyễn Quang Hải leave a strong impression in a handful of instants, and that impression can override the whole-match picture.

So I propose something that sounds technical but is in fact simple: a verification "gate". Before a number reaches an article, it must answer three questions. Who measured it? How was it measured? Is the source willing to take responsibility? If any of the three answers is empty, the number should not appear. Not because it is wrong, but because we do not yet know it is right.

For the V.League, this means accepting a period that looks less glamorous. Fewer diagrams. Fewer bolded numbers. More sentences reading "I do not yet have enough data". It sounds like a step back. But I believe it is the only real step forward. The Shanghai derby forged in me a healthy instinct to doubt data. That instinct did not make me write less. It made me write more slowly, and every remaining sentence more trustworthy.

The question I leave behind is not whether the V.League should invest in data — the answer is obvious. The question is this: without data, who among us is brave enough to say "I do not know"? And can a football nation grow from that admission?