Broken Timing and an Empty Dataset: The Honesty Standard of Vietnamese Athletics Analysis

The dataset landed in my inbox at 10 p.m. on a Friday: exactly 1,247 rows — the number the meet-management system had declared for a national athletics final. Rows containing real values: zero.

The time column was empty. The wind-speed column was empty. The 200-metre split column was empty. The competition-date column was empty. The athlete-ID column was empty. A file with a name, a format, and the promised row count, holding not a single fact about anyone who stepped onto the track that afternoon.

Seventeen years in this trade taught me to live with dirty data. I have seen decimals truncated, units mixed, two stopwatches disagreeing by three hundredths of a second. Those things are still data — ugly, but readable. An empty file is different in kind. It does not say the athlete ran slowly. It says we never measured.

When the numbers speak, all I have to do is listen. When the numbers fall silent, the only right thing is not to speak on their behalf.

The situation is not rare. At a national athletics meet, the electronic timing system failed in a handful of events, and the organisers fell back on the backup plan: hand timing. Results were still published, medals were still awarded, but the layer of data beneath the medal had vanished. No wind speed, no splits, no measurement error.

For spectators, that is nearly harmless. Whoever crossed the line first won. For an analyst, it is a quiet disaster. Every later conclusion — whether this athlete is rising or fading, whether this event has improved year on year, who deserves a SEA Games slot — must be anchored to a data series that begins on the very afternoon that was lost.

I had taken an analysis contract for a middle- and long-distance training group preparing for a selection trial. The brief sounded simple: build each athlete's performance-progression curve, compare it against the selection standard, and identify who shows a durable upward signal. To do that, I needed one minimum thing: real data.

What I received was a structurally perfect file with nothing inside it. In that moment I understood I was facing a very specific temptation, one every data professional knows by sight: filling the blanks with plausible-sounding guesses.

The wider context deserves spelling out. Vietnamese athletics has produced memorable milestones in recent years. At the 32nd SEA Games in 2026, Nguyễn Thị Oanh won four gold medals, according to domestic sports-press tallies. At the same Games, Hoàng Nguyên Thanh won the men's marathon. Those medals were built on years of training, and every training year leaves a data trace — except that the trace is rarely archived in full.

A decent athletics dataset must answer six questions, and missing any one of them strips value from the rest.

Start with timing. Without a competition date, a mark cannot be placed on any progression curve. A personal best set in March and an identical result set in October are two different stories, because between them lies an entire training cycle — a build phase, a sharpening phase, and a taper before peak form.

Next comes venue and altitude. A track sitting more than 1,000 metres above sea level favours sprints and jumps, simply because thinner air means less drag. A fast result there cannot be compared directly with a lowland result without correction.

Wind speed cannot be skipped. Sprint and jump marks are only ratified as records when the tailwind does not exceed 2.0 metres per second. Beyond that threshold the performance still exists, but it no longer carries comparative value. A well-timed gust can erase months of training; a headwind can make a good athlete look ordinary.

The measurement method is another variable. Hand timing and electronic timing are two different methods. A hand-timed 100-metre result is adjusted by roughly 0.24 seconds in conversion; over 400 metres the adjustment is about 0.14 seconds. It sounds small, but in a sport where medals are separated by hundredths, that is a wide gulf.

Split data is the fifth question. Total time tells you who won. Split times tell you why. Two athletes finishing a 1,500 metres in 4:20 may be telling opposite stories of conditioning: one running evenly, one burning early and cracking in the final 300.

Identity is the last. A number not tied to a name cannot be tracked over time, cannot form a curve, cannot raise an injury warning.

Six columns. My file was empty in all six.

This is where the data trade reveals its hardest part. When the table is blank, anything can be reconstructed from imagination. I know athlete A usually runs 800 metres around 2:05. I know athlete B medalled last year. From those two fragments of memory, a highly persuasive analysis can be written: an upward chart, a form verdict, a selection forecast.

That analysis would be a lie, even if each individual number happened to be true. It is no longer analysis. It is memory dressed up as data.

I do not believe in luck; I believe in what has been repeated enough times. One fast run does not make form. One slow run does not make decline. And an empty table makes nothing at all except one thing: the admission that we do not yet know.

In athletics analysis there is a test I always run before concluding anything about anyone: the performance-explosion test. If an athlete's single-year improvement exceeds roughly three times the average annual improvement of the preceding years, that is a signal to look again. It may be a genuine leap from a changed training plan or a move to a new squad. It may be a sign of something else. But to run that test I need a year-by-year mark series. No series, no test. No test, and every conclusion is just belief, carefully packaged.

There is a paradox outsiders rarely see. A risk checklist filled entirely with the words "insufficient information" looks very much like a clean checklist. Same shape, same tidiness. But the substance is inverted: one says "no risk," the other says "no information."

In sport, that confusion can do real damage. An athlete absent from an injury-watch list is not necessarily healthy; the clinic may simply not have sent the data. An event with no doping tests is not necessarily clean; the regional testing system may simply be thin. Absence of evidence is not evidence of absence — the first principle of anyone working with missing data.

In Vietnam this deserves particular care, because sports-data infrastructure is still young. Many provincial meets still treat hand timing as the standard. Many training sessions go unrecorded. Many important indicators exist only in a coach's notebook. No one is at fault for that — Vietnamese athletics grew up on bare-bones stadiums, and running fast has always mattered more than measuring correctly. But on the regional and continental stage, where rivals arrive with laboratories and sensors, a data gap becomes a performance gap.

So if guessing is off the table, what is an analyst to do? My answer is concrete, and it begins with lowering ambition.

The first task is to record the shortfall. A clear note stating that this dataset lacks wind speed, splits and measurement method. It sounds trivial, but it is the single most important act, because it stops the analysis from being reused later as though it were complete.

The second task is to separate three kinds of information. The first kind is what the source states plainly. The second is what can reasonably be inferred from available data. The third is what can only be guessed. Blending all three into one passage is the fastest way to turn analysis into propaganda.

The third task is to conclude only within what the data permits. If I have total time but no splits, I can speak about the final result but not about pacing tactics. If I have only hand timing, I can speak about placings but not about records.

The fourth task is to set a minimum gate for myself. For me, an athletics dataset must contain at least the competition date, the athlete ID, the event and the measurement method. Miss one of the four and I stop and file a report instead of an analysis. This gate does not make me slower. It makes me honest.

Based on my experience watching matches and meets, I have learned that a good coach rarely says "I know for certain." He says "I believe." The distance between those two verbs is the distance between someone who reads data and someone who sells it.

Once, at a long-distance race in central Vietnam, I sat beside the course for two hours, clicking lap times by hand. Afterwards I found my stopwatch was nearly a second off the official clock on the final lap. I could have chosen the prettier number to report. I chose to record both, with a note on the discrepancy. Later that note paid off: when it was checked against the organisers' data, people finally understood why the two sources disagreed.

People ask me why I stay silent; I am reading the words the field writes. But when the field is blank, an honest writer must admit he has read nothing.

One more point belongs here, because it bears directly on Vietnamese athletics. In domestic running circles, the notion of a "training mark" comes up constantly. Beautiful numbers appear in sessions, in internal tests, and are sometimes passed around by word of mouth as though they were official results. Anyone working with data must treat this category with great caution. A training measurement has no officials, no wind check, no calibrated equipment, and cannot be placed beside a competition result. It has value as a training signal, and only as that.

The same holds for carbon-plated racing shoes. This technology has shifted the baseline of track and road performances substantially over the past decade. When comparing an athlete today with one from ten years ago, the analyst must subtract the advantage the shoe technology confers — otherwise the progress of materials science gets booked as the progress of a human being.

Here a contrarian angle appears, and I would argue it matters more than any figure in this piece.

The natural reflex on seeing a data gap is to fill it with something — anything. For a fan, that is a harmless prediction. For a coach, it is pressure to answer an interview question. For an analysis system, it is pressure to emit a complete report. That pressure for completeness produces the most dangerous artefact of all: a document that looks full but is, in substance, empty of information.

The danger lies in being right in form and wrong in essence. A risk table with every cell reading "insufficient information" will be read as "no risk found." A technical report with every conclusion reading "cannot be assessed" will be read as "everything is normal." Correlation is not causation, and emptiness is not safety. In sport, those two confusions are twin siblings of every serious mistake.

So when my dataset came back empty, I chose an unglamorous action: I wrote down that it was empty, specified what it lacked, and returned it with a request for supplements. My report may be judged unexciting. But it contains no lie.

Every number is a confession the match cannot deny. And when there is no number, the only thing left to confess is the analyst himself.

Vietnamese athletics is at a stage where every regional medal is precious, and every timing failure is a lost fragment of memory. I am not proposing that we stop the competition for lack of data. I am proposing something much smaller: record honestly what was measured, and record honestly what was not. A strong athletics nation is built by finishes, and also by the times we dare to say we could not see clearly.

The distance never lies; we simply have not been patient enough to listen. But to listen, there must first be a distance that was written down.