When the Dataset Is Empty: Vietnamese Football and the Cost of Unfounded Decisions

That day was matchday 20 of the 2026 season. I reopened the geometric dossier covering 43 matches and saw what I had overlooked for nineteen rounds: Sanna Khanh Hoa BVN's defense exposed a left-wing gap in 61% of their defeats. The number had been there all along. The problem was not that it did not exist, but that it was not read at the right time. When the team was relegated, I redrew the diagram of the pain — and realized I had held the answer for months, only no one had bothered to open the dossier.

That story is not the private tale of a 50-year-old assistant coach in Nha Trang. It is the story of an entire football culture accustomed to making decisions on instinct, and only turning to data once everything is too late. Today, writing these lines at 59, I want to talk about something more dangerous than wrong data: empty data — the thing everyone believes they have, but actually do not. It is the most insidious trap in analysis, and Vietnamese football falls into it every week, every season, every time a tactical decision is made without anyone checking whether the information foundation beneath it is real.

Over many years watching V.League and youth competitions, I have noticed something: at European analysis centers, there is a data-quality department that verifies information before it reaches the coaching room. Here, that step is usually skipped. A scouting report is typed from memory. A PPDA figure is copied from a foreign website without anyone checking it belongs to the right competition. A three-minute clip is cut from a match two months old. All of it is gathered, bound into a dossier that looks professional, and brought into the closed room. And in that windowless room, no one asks: is this data real, or is it just an empty space decorated with paperwork?

The windowless meeting room has no windows, so I write to see what I am saying. And what I see, after more than four decades in football, is a decision-making system built on assumptions that have never been verified. The first question a coach should ask before any tactical decision is not "how does the opponent play", but "do I actually know how the opponent plays". The difference between those two questions is the difference between a grounded decision and a belief.

The annual season is when this problem is most visible. The table shifts every round, relegation and title pressure produce hasty decisions, and in that haste people easily draw conclusions from the emptiest datasets. I have witnessed coaching-staff meetings where people argued for hours about whether the opponent would play 4-4-2 or 4-2-3-1, while no one had a single accurate figure on the opponent's successful pressing count in the last three matches. That argument was not analysis. It was an exchange of feelings dressed in tactical terminology.

In my experience watching matches, the clearest sign of an empty dataset is overconfidence. When someone states with certainty that the opponent is weak on the left flank, without citing concrete data on dribbles conceded, fouls committed, or goals conceded from that zone across a given number of matches, that is the moment to stop. Because certainty without data is usually certainty built on a void. And a void, in football, is always filled by prejudice.

My 2026 story is painful proof. When I proposed a geometric note-taking system to profile the movement of four opposing defenders — measuring cut-off angles, inter-positional distances, and the frequency of exposed gaps — the coaching staff judged it perfectionist and postponed it. For nineteen rounds we made decisions based on video impressions and assistant coaches' memory. By matchday 20, when I completed the dataset for 43 matches myself and found that the left-wing gap appeared in 61% of defeats, the team was already too close to the abyss to turn around. We finished the season with 21 points from 26 matches and were relegated.

The lesson was not "data matters". Everyone knows that. The lesson was that data only has value alongside the moment of intervention — and a dataset completed after the season ends is no different from an autopsy report. It accurately describes the death, but saves no one. This is why I always begin each analysis with a specific timestamp, and always ask: when does this information remain valid?

Vietnamese football's problem is not a lack of data. We have enough video, enough statistical tables, enough scouting reports. The problem is that we lack the habit of verifying data before using it. An assistant may spend three days cutting video on the opponent, but not thirty minutes checking whether that video represents current form. A coach may cite an opponent's attacking metric without knowing it was calculated during a period when the opponent fielded their strongest lineup — before three key players were injured. This is the most dangerous kind of empty data: real data that has expired.

I wrote about this in the series "Empty Stadiums, How Tactics Change" after the summer of 2026. When global football shut down and matches were played before empty stands, the concept of "home advantage" that I had used for twenty years suddenly became meaningless. I spent six months reviewing 120 European matches played without crowds, measuring the average distance between center-back and goalkeeper when the home side was trailing. The results showed home teams pushed their line up 18% higher than usual, creating more dangerous counterattacks for opponents. The empty-stadium summer taught me that applause is only a coat of paint — and when that paint is stripped away, a completely different dataset is revealed.

That lesson applies directly to V.League. We are still using tactical concepts built under conditions of crowds, home pressure, and psychological advantage — to analyze a league where those conditions change every season. New stadiums, congested calendars, long travel, harsh climate — all these factors make old data expire faster than we think. A coach who reuses last season's lesson plan without rechecking its assumptions is coaching a team that no longer exists.

In refereeing and VAR analysis, the empty-data problem is even subtler. "Clear and obvious error" — the clause VAR uses to decide whether to intervene — is itself a vague clause. No dataset can objectively define "clear" and "obvious". Each referee has their own threshold, and that threshold shifts by match, by pressure, by moment. When we say VAR reduces errors, we assume there is an objective standard for measuring error. But there is no such standard. The subjective judgment space within VAR is larger than people think, and every time a decision is made, we fill that void with the belief that technology got it right.

I am not saying VAR is useless. I am saying we are using a high-precision tool to cover a larger data void: data about how we ourselves make decisions. No one measures how much crowd pressure affects a referee in the 90th minute. No one measures how much a referee's decision shifts after watching a replay three times. Those voids exist, and we fill them with belief — belief in technology, belief in experience, belief in "seeing is believing".

This is where I want to offer a counterintuitive angle. In analysis, people usually fear wrong data. But in my experience, empty data is more dangerous than wrong data, because wrong data can at least be detected, while empty data is never checked. A wrong number can be cross-referenced and discarded. A void has nothing to compare against, so it persists, decorated by assumption, and finally becomes "truth" in the meeting room.

I have seen this happen many times. A team builds a match plan on the assumption that the opponent plays long ball, when in fact the opponent switched to short passing three rounds earlier. No one rechecks. The assumption is passed from one assistant to another, from one meeting to the next, until it becomes the foundation of a tactical decision — and that decision fails. When it fails, people blame the players, the referee, the weather. No one blames the data void that existed from the start.

Tactics cannot save a team, but they help us know where we die. And to know where we die, we need to know where we stand — with real data, not with decorated assumptions. This is why I always add a "base assumptions" note at the end of each analysis. It is a disciplinary habit: listing what I am assuming, so the reader knows which parts of the article stand on solid ground and which stand on sand.

A tactical diagram is like a landslide map — it shows where not to stand. But a map only has value if it is drawn from real data. A map drawn from memory, from feeling, from unverified assumptions is not a map — it is a painting. And a painting saves no one from a landslide.

In this annual season, I want to propose a small but systematic change: before every tactical decision, spend five minutes checking whether the data you are using actually exists. Those five minutes may be the most valuable time in a coaching staff's week. Because a decision based on empty data is not only wrong — it also sets a wrong precedent, making subsequent decisions stand on sand too.

I do not expect Vietnamese football to change overnight. But I believe every coach, every assistant, every analyst can start with a small habit: question the source of every number before using it. That is the only way to turn analysis into a genuinely useful tool, rather than a decorative ritual.

At 59, I understand that winning matters less than explaining why we won. And to explain, we need real data — not empty data decorated with belief. Vietnamese football deserves decisions built on solid ground. And that solid ground begins with a simple question: do I actually know what I am talking about?