Vietnamese Swimming's Missing Split Data: The Long-Term Cost After Every SEA Games

On the electronic scoreboard at a SEA Games swimming final, the stands receive exactly one number per lane: the finishing time. No 100m splits. No average speed per segment. No stroke-distance data. For a casual spectator, that is enough to know who won. For an analyst, that is when the work begins, and when the raw material runs out.

I have followed swimming since 2026, when I joined Thanh Nien as a swimming reporter. The trade left me a notebook: heat times, final times, the gap between two swims, an athlete's age at the moment a record is set. After more than a decade the notebook has grown thick, yet it stays empty in exactly one column: the structure of the race.

Swimming is a sport where the margin between elite athletes is measured in hundredths of a second. In the 1500m freestyle, the gap between gold and bronze at regional championships is often just a few seconds, while the gap between a Southeast Asian swimmer and a leading Asian swimmer can reach half a minute.

To understand why that gap exists, an analyst needs to know where a swimmer accelerated, where they faded, whether a negative split appeared, and how stroke rate shifted as fatigue accumulated. A single total time says none of that. It reports the result without revealing how the result was produced.

In many countries with developed swimming programmes, split data is published alongside results, sometimes every 50m. In Vietnam, most domestic meets and several regional championships still return only the final time. Fans lose nothing. Coaches, young athletes and analysts lose roughly half the story.

The most memorable case is Nguyen Thi Anh Vien. She won a great many SEA Games medals across several years, yet the gap became obvious once she stepped onto continental and world stages. Each time, the analysis community asked the same question: was it conditioning, technique, or pacing strategy? Without splits, nobody could answer with data. They answered with impressions, and impressions cannot be repeated.

Nguyen Huy Hoang is the mirror case in one respect. He won a silver medal at the Asian Games in the 1500m freestyle, one of the rare achievements by Vietnamese swimming on the continental stage. Looking at that result, the natural question is what produced it and what prevents it from recurring. Answering that requires knowing how he distributed his effort over the first 300m, how he held rhythm through the middle, and at which metre his finishing kick began. Those numbers exist inside the organiser's system. They simply never travel outward.

This is the point I want to make plainly: the biggest problem for Vietnamese swimming, viewed through a data lens, is not a shortage of talent but a shortage of verifiability. A swimmer may improve by two seconds over six months of training. If we do not know which segment produced those two seconds, we do not know which set to repeat, and we do not know which set to cut.

There is a lesson I carried over from another sport. “A small GPS drift was enough to teach me: verification is everything.” In 2026 I miscalculated a player's sprint distance, then discovered a systematic fault in the data-sync software. Since then, every table I publish carries a confidence column. In swimming, that column is routinely blank.

Even the recovery index runs into the same wall. “The pandemic season taught me to measure a competition by recovery metrics, not by points.” Applying that to swimming requires training load, match density and each athlete's shoulder-injury history. Those three data fields currently sit scattered, largely undigitised.

Missing granular data weakens analysis, and it carries a heavier consequence: it distorts how people are selected.

In sprint events, performance leans on raw speed, which is easy to see and easy to time. In distance events, performance leans on energy distribution. A swimmer can be excellent over 400m and never make the step to 1500m, because their body cannot hold rhythm through the third quarter. Conversely, someone may swim a slow heat but finish powerfully; give them a final with a sensible pacemaker and they explode.

Without visibility into race structure, coaching staff default to selecting on personal bests. But a personal best is an index dependent on the pacemaker, water conditions and the competition schedule. That is a systematic error no model can catch, simply because the model has no input.

I believe in numbers, but only after a number has cleared three rounds of checks. In Vietnamese swimming, those three rounds have never run completely.

The work required is smaller than it appears. A 50m split table recorded automatically alongside results. A rule obliging organisers to publish that data. A shared database across training centres. After a few seasons we would hold something more valuable than any guess: a baseline for comparison, and the ability to say “we do not yet know” while still moving forward.

“Data does not tell stories; it records everything so that I can tell them.” In Vietnamese swimming we currently lack both the recording and the telling. The next championships will come around again, and the empty column in my notebook will stay empty, unless someone decides to write it down.