The Silence Between Two Numbers: The Discipline of an Empty Data Table in the V-League

One night, I re-ran the data table for a V-League match for the fourth time, and the screen still returned a single word: empty. The xG column — a model estimating expected goals from shot position and quality — stayed blank. The column for passes into the penalty area stayed blank. The PPDA column, a measure of pressing intensity based on how many passes an opponent is allowed before being challenged, stayed blank as well. Four runs, four blanks. What struck me was that I felt no irritation. I felt lighter.

Thirty-one years of observing this industry — beginning in 2026 as a fact-checker at an international sports magazine, later hosting broadcasts of major events, and in recent seasons dissecting the transfer market — taught me something few want to hear: the most honest moment for a data person is the moment he says, “I don't have enough information.” An empty table is not a failure. An empty table is an answer.

Vietnamese football is at a stage where data has never been more abundant, and has never been used more carelessly. Every V-League round, platforms such as InStat and Wyscout supply thousands of data points: shot counts, heat maps, duel-win rates, distance covered. A head coach can open a laptop and see that his player ran 11.4 kilometres in a match. But the right question has never been “how much did he run”. The right question is “what did he run for”.

I once wrote that heat maps have become football's new fortune-telling. They paint a blazing red zone and let the reader draw his own conclusions, when that red zone may simply be the by-product of a passive tactical setup, not a sign of energy. Data does not lie. But people lie with data very well.

And I am someone who has lied with data, even if unintentionally. That is why I am writing this piece — not to teach anyone how to read numbers, but to recount the two times numbers betrayed me.

In April 2026, I analysed the match in which Hà Nội FC beat Thanh Hóa 3-2 at Hàng Đẫy Stadium. InStat data at the time showed that Hà Nội created only 0.9 xG, while Thanh Hóa generated 1.7 xG. The media praised the head coach at the time as a tactical genius. I held to a dry point: the win came from an unusually high conversion rate, and that rate would not last. Hà Nội then went through a run of dropped points, and my article was later cited by specialists.

But the bigger lesson lay elsewhere. “In 2026, I bet on xG. The V-League answered with a shock.” The shock was not that xG was wrong. The shock was that I believed xG alone was enough.

The summer of 2026 taught me the same thing on a larger scale. Before the World Cup, a football website asked me to predict the champion with my own model. Based on total xG and PPDA across the group stage, I picked Brazil. Brazil were eliminated by Belgium in the quarter-finals. France won. Going back through every match, I found my error: I used whole-tournament aggregate data, while France improved their PPDA from 11.2 in the group stage to 8.7 in the knockouts. The champion changed how it played from one phase to the next, while I applied one fixed number to every moment. “The 2026 World Cup taught me: data is never a single layer.”

From those two shocks I drew a professional principle: better to present an empty table than to fill it with guesswork. When my analysis system cannot find enough data for a match — a frequent occurrence in youth competitions, in matches played at grounds without tracking cameras, or in matches where the home club does not publish statistics — then the correct output must be “insufficient information”, not a number interpolated to make a report look complete.

The greatest value of an analysis system does not lie in how many questions it can answer, but in its willingness to refuse to answer when there is no basis. A model that can say “I don't know” is more trustworthy than a model that always has an answer. Because an always-available answer, in the hands of an overconfident person, becomes a false prophecy.

I see this most clearly in the transfer market. “Market administrators do not manage cash flow. They manage expectations.” When a player is valued with numbers that have no provenance — minutes played that are never verified, goals without the context of the opponent — the number itself becomes a rumour wearing a scientific coat. A rumour disguised as data is the most dangerous kind, because it makes people stop doubting. I have seen more than a few V-League deals inflated by a handsome statistics sheet, only for the coaching staff to admit three months later that they had never watched the player live.

I recall a season when a V-League club published a twelve-page scouting report on a foreign striker. It had every metric: goals per 90 minutes, aerial duel win rate, number of box entries. The only thing missing was the context of his previous league — he had scored in a lower division where opposing defences were markedly slower. The report was not wrong arithmetically. It simply omitted one layer of information that changed the meaning of every other number.

In 2026, I hosted broadcasts of several major events, from the Table Tennis World Cup to the Sudirman Cup in badminton. That multi-sport experience taught me that each sport has its own “real unit”. In table tennis, that unit is spin. In badminton, it is the rhythm of movement. In football, the unit is not the goal, but space. And space is something statistics only partly grasp.

There is a paradox here that Vietnamese analysts rarely admit. We live in an era where a lack of data is treated as a professional defect. A report with an empty table is judged lazy. An analysis that says “not enough basis” is seen as evasive. That pressure pushes people to fill the gap with whatever is available: a metric borrowed from another league, a three-match sample, a pretty heat map.

But look at the nature of the game. Football is a chaotic system with feedback. Every metric is born in a specific context: weather, pitch condition, a congested schedule, player psychology, and even refereeing decisions that no metric records. When we force a number to represent a reality it does not measure, we do not make the analysis more accurate. We only make it sound more certain. And false certainty, over a long season, always exacts a price.

There is a line I always keep in mind: “After seven years, I believe in the silence between two numbers.” That silence is where data stops speaking and a person must take responsibility for his own judgement. It is not a gap to be filled. It is the frontier of understanding.

The same holds in esports, which I have followed for years. “Esports taught me that tempo is also a layer of data.” Spectators often mistake a flashy team-fight for a high-level match, when what decides it usually lies in the quiet minutes: vision control, ward placement, tempo pressure. Those minutes leave almost no beautiful number to quote. They are an empty table to anyone who reads only statistics. And precisely for that reason, they are where the match is truly decided.

So when a data table returns an empty result, I do not treat it as a full stop. I treat it as a signal for the next round of analysis: which source is needed, how many matches must be watched live, whom in the coaching staff to ask in order to understand why the data does not exist. An empty table points precisely to where the digging should go.

Vietnamese football will have many more seasons with matches whose data is not enough to tell a story. The question I leave for myself, and for anyone holding a data table: when there is not enough information to conclude, do we have the courage to write the two words “not yet known” — or will we keep manufacturing a number, just so our report looks fuller than the truth?