When the Swimming Lane Returns an Empty Number

In June 2026, at the My Dinh Aquatic Sports Palace, I spent an entire afternoon cross-checking the performance data of forty-two swimmers at the national championship. By the time I closed my laptop, what I had was a file with exactly two columns: name and final time. No split times for each 50 metres. No stroke rate. No turn count. No reaction time off the blocks. Forty-two people had swum hundreds of laps, and I could not reconstruct a single one of them. This is not the story of a poorly organised meet. It is the story of a swimming nation that has athletes, has results, has medals, yet is almost blank when it comes to data. The sport decided entirely by numbers is precisely the sport most starved of them. Swimming differs from football in one fundamental way: it does not need a complex model to begin. It needs exactly one thing, which is time, and time can be broken down. A standard 100-metre freestyle race consists of the start reaction, an underwater phase of up to fifteen metres, the surface swim, one turn at the 50-metre mark, and the finish. Each part is an independent variable, measurable and comparable between athletes. With enough splits, you immediately see who is strong where. Athlete A loses on reaction but wins on the closing length. Athlete B swims at a slower tempo but with a longer stroke, compensating through efficiency. Athlete C loses two hundredths of a second on the turn, and that is exactly the gap between a medal and fourth place. Without splits, those three look identical in the results table. Everything collapses into a flat string of times, with no highs, no lows, no lessons. In many developed swimming nations, splits are recorded automatically every 25 metres, alongside propulsion data and stroke frequency. In Vietnam, most data stops at the final figure on the electronic board. I call it empty data: the field exists in form, but holds no content to analyse. The first consequence is the loss of diagnostic capacity. When a swimmer stalls, coaches can only guess: guess the athlete is weak physically, guess it is a mental issue, guess the training load is too heavy. But guessing cannot replace evidence. With the last three months of splits, they would see at once that the start has declined while the closing length remains sound, meaning the problem lies in the underwater technique, not in fitness. One correct number saves a whole squad from a training cycle pointed in the wrong direction. The second consequence is the loss of pattern-based selection. To find a successor, you need to know what a successful athlete looks like at fifteen or sixteen. That is a data problem, not a matter of feel. But when an athlete's record holds only a date of birth and competition results, nobody can build a pattern. Every intake starts from zero, resting on a coach's eye, which is valuable but cannot be replicated. Consider the case of Nguyen Thi Anh Vien, who dominated the regional women's lanes for years. Her achievements are recorded in medals, but very little of her split data was preserved systematically. The lesson from one of the finest swimmers in Vietnam's history largely lives in the memories of those who worked with her, not in an inheritable data file. When the next generation wants to learn from her, they learn through stories, not through numbers. Nguyen Huy Hoang, who brought home SEA Games gold medals, is no different. Every time he stalled, the question was always why, but the answer usually came from the coaching staff's intuition. Nobody questions their ability. The problem is this: a sport that wants to go far cannot depend forever on a few individuals with a good eye. It needs a record-keeping system dense enough for that good eye to be multiplied. I once compared this with a regional swimming nation. Some neighbouring countries have digitised their youth athlete registries, complete with growth, arm-span and recovery-heart-rate indices. As a result, they detect stalling cases early, before performance collapses. Here, most records remain scattered across notebooks, photographs and individual memory. I once tried to reconstruct a 200-metre medley race from amateur spectator video alone. The result carried an error of nearly one second against the electronic board, enough to overturn the standings. That reminded me that amateur data can be useful, but it cannot replace standard data. My experience following swim meets shows a pattern: where data is scarce, blame falls on individuals. An athlete who misses the standard is called lazy. A coach who fails to lift a pupil is called weak. Yet the real cause may be nothing more than a turn deviation that was never measured. Every shock has its own probability. We call it a shock only because we have not yet consulted the tables. What is worth noting is that swimming data is not as hard to collect as people assume. Electronic timing has existed for a long time. Lane cameras exist too. All that remains is to define how data is stored and published. A standard split file, open to coaches and analysts, costs little compared with one national-team training slot. But that small task has not been done, and the price is a whole generation of athletes growing up with no mirror other than the electronic board. I sit far from the lanes to see the race more clearly than the referee. That distance shows me what those sitting by the pool edge often miss: a season is not only medals, it is thousands of laps that nobody recorded. One thing must be made clear, lest readers jump to conclusions. A lack of data does not mean Vietnamese swimming is weak, and conversely, more data does not automatically produce medals. I do not want anyone reading the above and thinking that buying software is the whole answer. Between having data and knowing how to use it lies a far wider gap, and that gap sits with people, not devices. We must also be cautious with the few numbers we do have. A fine performance at a domestic meet may not transfer to the regional stage, because conditions differ: a different pool, a different crowd, different opponents, different pressure. The correlation between strong national results and strong international results is not a linear causal relationship. I have seen cases of swimmers very fast at home who stalled on the bigger stage, and cases of the opposite. Without dense enough data, every conclusion must be framed as probability, not assertion. Finally, there is a portion of variance that numbers cannot explain. Those are the days an athlete steps onto the blocks with an unusual state of mind, or the times a whole squad rises together for a reason that cannot be measured. I accept that any model has a confidence interval, and that interval must be stated rather than hidden. A single lap appears once. Its trajectory stretches across many years. Vietnamese swimming data today sits exactly where football once sat: plenty of interest, but no habit of record-keeping. The ordinary eye watches a goal to understand a match. I watch the match to understand the years. If the national championship publishes split times for its finals, that will be a signal worth following more than any medal. And the question left open: are we waiting for a talented swimmer, or waiting for a system transparent enough to see the talent already here?