Vietnam's Swimming Lanes and the Data Void: What Is Not Measured Remains Unknown

At the men's 200m freestyle final at the national swimming championships in April 2026, I sat in the stands of the My Dinh Water Sports Palace with a notebook and a stopwatch. Eight lanes, eight athletes, one scoreboard. When lane four touched the wall, the number one minute forty-eight seconds appeared. The gap between first and eighth was nearly four seconds. I turned to a member of the organizing committee and asked for the 50m split data. He shook his head: "We only record the finishing time."

That is an answer I have heard no fewer than ten times in eighteen years of working with sports data. It explains why, every time Vietnam's national swim team steps onto the SEA Games or Asian Games stage, international analysts look at us the way one reads a book missing half its pages. We have results, but we lack structure. We have names, but we lack lanes.

For years, I told myself my job was to read numbers. But the more I read, the more I realized: in Vietnamese sport, most of the most important numbers simply do not exist. And what does not exist cannot be verified, let alone improved.

A small GPS deviation is enough to teach me: verification is everything. That lesson came to me in 2026, not in swimming but in a football team's GPS data, when I misrecorded a striker's sprint distance. But it haunted me enough that I kept asking myself: if a top Vietnamese football club can still have skewed data, then how far off can a 50m swim lane timed by hand at a national meet be?

Context: A swimming nation with results but no memory

Vietnam is not a country without swimming data. We have performance records managed by the aquatic sports federation, national record lists, and results from each round. The problem lies deeper: we lack process data, the indicators that shape a result.

At the international level, a swimmer competing in an event organized by the world federation will have their 50m splits, turn times, distance to record, stroke count, underwater depth, and stroke rate recorded. At the SEA Games, depending on each country's investment, part of this data is captured. But at Vietnamese national meets, the data stops at the final number on the scoreboard.

This creates a paradox. We have many big names — Nguyen Thi Anh Vien, Nguyen Huy Hoang, Tran Hung Nguyen, Hoang Quy Phuoc, Pham Thanh Bao — but we know very little about how they swim. We know they are fast, but not where they are fast. We know they break records, but not how they distribute effort. We know they win medals, but not what percentage of those medals is built on technique versus conditioning.

I once sat beside a foreign coach during a national team training session. He opened his laptop, connected to a sensor strapped to a swimmer's goggles. After the session, he had a lane chart for each person: every 50m, every turn, every second of acceleration or deceleration. He told me something I immediately wrote in my notebook: "You have swimmers, but you have no roadmap."

A roadmap — that is exactly what process data creates. Without it, any conclusion about an athlete's performance is guesswork. And guesswork, in elite sport, is a form of risk.

Let me be clear: this problem is not new. Since I began following national swim meets in the early 2010s, the way data is recorded has barely changed. Organizers record finishing times, print results, award medals, and close the book. There is no archiving phase, no cross-checking phase, no analysis phase. Data is born to be announced, not used.

Meanwhile, at international training centers, data is not only recorded but used to personalize training plans. A backstroke swimmer can have stroke rate tracked by sensor and elbow angle adjusted weekly. A butterfly swimmer can have hip stability analyzed across stroke cycles. These details, accumulated over time, create a bigger difference than any coaching change.

Analysis: When every second matters

Let me take a concrete example to show how process data changes the way we understand a lane.

Suppose two swimmers finish the 400m freestyle in three minutes fifty-two seconds. Looking at the results, they are equal. But with splits, the story is entirely different. Swimmer A swims the first 100m in 55 seconds, then slows: 58, 59, 60. Swimmer B swims evenly: 58, 58, 58, 58.

Swimmer A went out too fast and faded, a sign of early overexertion. Swimmer B swam steadily, meaning they can accelerate at the end without breaking structure. These two readings lead to completely different training programs. Swimmer A needs to learn to restrain the first 100m. Swimmer B needs to learn to build a gap over the middle 200m. With only the final number, a coach cannot know what to fix.

In many years of analyzing swimming data, I have always used splits as my main tool. Only splits show whether a swimmer swims on technique, on conditioning, or on willpower. And these three factors require three different training programs.

At the 2026 national swimming championships in Ho Chi Minh City, I filled my personal tracking sheet with data for forty-two final swims. There were forty-two final results. The number of splits I collected by timing myself: forty-two. The number of splits provided by the organizers: zero.

That means the entire national database of the year's most important meet, in terms of process, depended on one person sitting in the stands with a stopwatch. The accuracy of this measurement, according to my own tests, deviates by 0.15 to 0.4 seconds depending on the timer's reflexes. In the 50m event, where world records are determined by hundredths of a second, I am not confident enough to draw any conclusion.

This is not Vietnam's story alone. Many Southeast Asian countries face similar issues. But what troubles me is the gap between awareness and reality. We talk a lot about elevating Vietnamese swimming, but we have not built the minimum data infrastructure to do so.

One point needs emphasis: data is useful not only for post-race analysis but also for risk forecasting. If a swimmer's first-100m split is rising over three months, it may be a sign of an unhealed shoulder injury or an overloading training plan. If we only look at the finishing time, everything appears normal. If we look at splits, we see the problem before it becomes a crisis.

In 2026, when competitions were suspended due to the pandemic, I spent seven months building a recovery index model for athletes. The model combined high-intensity running distance, acceleration counts, and injury history to determine risk. Applied to swimming, the principle is similar: process data allows risk forecasting before it manifests in results.

The pandemic season taught me to measure a tournament by recovery indices, not by points. In swimming, this is even truer, because a swimmer competing across multiple events in one week can accumulate fatigue without any external sign.

So if data matters so much, why don't we have it? The answer, I believe, lies in three reasons. First, the initial investment in equipment and staff is considered high relative to national meet budgets. Second, traditional Vietnamese sports culture prizes results over process. Third, no one is responsible for data collection, so no one does it.

All three reasons can be solved technically. The issue is will.

Contrarian angle: Medals are not the measure of a sport

This is the part I always find hard to write, because it differs from the crowd's sentiment.

Every SEA Games, the medal table becomes the measure of success. Vietnamese swimming wins a few golds, the news buzzes, and we tell ourselves the sport is improving. But from a data perspective, a SEA Games gold can come from a rare generation of exceptional athletes, from the absence of certain rivals, or from a small field of entrants.

Without process data, we cannot distinguish systemic achievement from individual achievement. And if we confuse the two, we will invest in the wrong place.

I have always believed: medals are the result, but not the indicator. The real indicators are the number of athletes meeting continental qualifying standards, the number of athletes breaking personal records each year, and the number of young athletes improving their splits season over season. These numbers require data we do not have. So we keep measuring with the easiest thing — medals — and keep confusing victory with growth.

Croatia 2026 was not a miracle — it was xG written into history. I always remember that lesson when I look at a medal table. A team or an athlete can outperform expectations relative to an indicator, but to understand why, we need that indicator. Without it, we call success a miracle. With it, we call success repeatable skill. The difference between these two labels determines how we invest in the future.

I know someone will say: why invest in data when athletes keep swimming and coaches keep teaching? The answer is this: data does not replace people. Data only helps people make fewer wrong decisions. A coach can watch a swimmer and feel something. But when that swimmer is half a second slower than three months ago, the coach needs to know where the slowdown is, why, and whether to change the plan. Feeling cannot answer that. Data can.

I believe in numbers, but only after they pass three rounds of verification. In Vietnam, we have not even passed the first round.

There is another paradoxical angle I want to raise. Many people think data is a luxury, only for developed sports nations. But the reality is the opposite: sports nations with fewer resources need data more, because they have no margin for wasted investment. A country with hundreds of potential athletes can afford trial and error. A country with a few dozen potential athletes must optimize every choice. Data is not a luxury; it is a tool for saving.

Signals for the next round

What I write here is not meant to deny the efforts of athletes or coaches. Vietnamese swimming has come a long way from the 2000s to now, and I have followed its growth step by step with both notebook and computer. But following does not mean being satisfied.

If I may propose three things for the next round, I would say: first, record 50m splits at every national meet, including youth level — this costs very little but creates long-term value. Second, build a public database of Vietnamese athlete results over the years, so anyone can query and cross-check. Third, integrate data into coach training programs, so the next generation does not struggle with numbers that do not exist.

These three things do not require expensive technology. They require one decision: to treat data as an asset, not a procedure.

People see a contract; I see a ten-page probability table. Two years ago, when a club ignored my data analysis in a transfer deal, they got exactly the result the model predicted. I do not bring it up to say I was right. I bring it up to point out that where there is data, mistakes can be avoided. Vietnamese swimming is the same.

I do not expect these changes within one season. But I know one thing: data does not tell stories; it records everything so I can tell them myself. And in Vietnam, we are letting our story drift away without saving it.

When I left the My Dinh Water Sports Palace that afternoon, my notebook was full of finishing times and split lines timed by my own hand. I knew that in three months, those numbers would sit in a drawer, and no one would cross-check them with anything. A lane had been swum. An opportunity had passed.

In sport, memory is not in medals. Memory is in data. And a sport without memory finds it hard to speak of the future.

Will the next generation of Vietnamese athletes get to swim in a system that knows how to remember?