When the Water Goes Silent: An Empty Spreadsheet and the Limits of Swimming Data

When the Water Goes Silent: An Empty Spreadsheet and the Limits of Swimming Data

Hook

On a July night in 2026, I opened a spreadsheet I had spent three weeks preparing. It held the full indicator set from the heats of a major swimming meet: split times for every 50 meters, stroke rate, reaction time off the blocks, the count of underwater dolphin kicks. I had named it Basin No. 7. I opened it, and the time column was bare. Not a single figure. Not a single row of numbers. Only a few swimmer names and competition dates, sitting there like untied threads.

I sat still for a few minutes. In the sports-betting analysis trade, an empty spreadsheet is more frightening than a spreadsheet full of bad numbers. When a number is wrong, I know where to fix it. When a number vanishes, I know I am standing before the greatest temptation of the profession: the temptation to invent an answer. And I realized, after sixteen years of watching this industry, that this is the lesson the water taught me more slowly than any other sport.

Context

I entered the trade in 2026, starting as a swimming reporter for a major newspaper in Saigon. Back then I believed swimming was the cleanest sport in the world when it came to data. No xG like football, no PPDA, no arguments over whether a shot counted as a chance. Swimming hands you a single number, blunt and absolute: time. Whoever touches the wall first wins. It was so simple that I once thought I had chosen the wrong sport to become a data analyst.

But the deeper I dove, the more I saw that this single number hides more than it reveals. A world record from 2026 does not share the same standard as a world record from 2026. A time in a 25-meter pool cannot be laid next to a time in a 50-meter pool. A 15-year-old swimmer breaking her own age-group record does not mean she will still be breaking it four years later. What I thought was a straight data line turned out to be a maze, where every branch needs its own filter.

And then there are nights like the one in July. Nights when the maze has no entrance. Nights when the data source falls into total silence, and I must choose between two paths: constructing a plausible-sounding story, or admitting I know nothing at all.

Core

I chose the second path, and I want to spend most of this piece explaining why that is the right call — even when it runs against the instinct of a writer who is paid for speed.

Swimming has a peculiar data structure that few bother to make clear. Each swim produces a total time, but the total time is only the surface layer. Beneath it lies a string of 50-meter splits. Over 100 meters freestyle, the first split and the second split tell two different stories: a swimmer who goes out very fast and fades in the back half shows an unripe fitness base, while a swimmer whose back half is faster than the front — a negative split — is usually a sign of a mind that knows how to distribute effort and a body still holding energy at the final 50. When I have no splits, I have nothing to tell those two swimmers apart. They become just two equal numbers on a calendar page.

Deeper still is the technical data. Reaction time off the blocks tells a story about foot explosiveness and alertness to the signal. The count of underwater dolphin kicks off the start and after each turn tells a story about upper-body power and the ability to hold the water line. In the 200-meter butterfly, this indicator almost dictates the entire race, because the 15-meter rule requires a swimmer's head to break the surface before that mark, and a swimmer who fits in eleven dolphin kicks and surfaces right at the line carries a real advantage over one who manages only seven. The number shown on the scoreboard does not distinguish those two. But an analyst with technical data does, and knows who will improve and who will stall.

I once witnessed a small but memorable case during the buildup to an Olympic Games. A young swimmer was praised by the media for a dream-like 100-meter butterfly time at a domestic meet. I looked at the odds and was about to bet on him. But when I checked, I found the whole performance had taken place in a 25-meter pool, while the upcoming meet was a 50-meter pool. A short pool always has more turns, more starts, and therefore produces faster technical times — but cannot be converted directly. That boy was inflated by a beautiful number in a different context. When he reached the real stage, his time fell back to his true position, and I avoided a loss simply by checking the pool length.

The larger story of swimming data lies in its historical dimension. The period from 2026 to 2026 was the era of high-tech polyurethane swimsuits — what the trade calls shiny suits. At the World Championships in Rome in 2026, forty-three world records fell in a single week of competition. That figure alone should make anyone who reads data stop. When the international swimming federation banned the suit from 2026, most of those records became markers that share no standard with the present. A careless analyst may take a 2026 record as a yardstick, then conclude a modern swimmer is progressing slowly. That conclusion is wrong at its root, because it compares two non-equivalent eras.

The same holds for age and sex. Swimming is one of the few sports where junior world records are frequently broken by young girls who then never touch them again. Those in the trade call it the puberty barrier. A fifteen-year-old female swimmer breaking a world record in the 200-meter butterfly may be a phenomenon, but many cases show that as the body changes over the following two years — height rising, muscle and fat ratios shifting — her times slow down systematically. Any analysis that looks only at time without looking at the swimmer's age and sex risks turning a child into a hot stock while she stands before an unpredictable physiological period.

So when my spreadsheet was empty that July night, what I truly lost was not just the numbers. I lost the ability to rule out. I could not rule out that a beautiful time was set in a short pool. I could not rule out that it was a record from the shiny-suit era. I could not rule out that the swimmer was only fifteen and standing before the puberty wall. Without data, I could not rule out anything at all. And an analyst who cannot rule anything out is not an analyst. He is just a man with an opinion.

There is a point I consider core and rarely spoken of in the sports-data trade: the greatest value of data is not telling you what is true, but helping you eliminate what cannot be true. An empty column does not tell me who will win. But it stops me from asserting who will win based on feeling. That is the entire difference between someone who works with data and someone who merely comments.

Contrarian

In the world of swimming, there is a counterintuitive paradox I have watched for years. The less data there is, the more the market wants a fast conclusion. Swimming events have far fewer official competitions than a dense football season. A good swimmer may appear at the top level only a few times a year, while a footballer plays fifty times. That means the swimming data sample is far thinner, and each appearance becomes such a heavy datum that people tend to inflate it. A single brilliant night is suddenly read as destiny. A single fade is suddenly read as permanent decline.

An inexperienced data writer in that situation tends to do something very dangerous: filling the gap with story. With no numbers, they tell tales of willpower, of "fighting spirit," of "the courage to overcome." Those stories sound good and are not emotionally wrong, but they are not analysis. They are hypotheses dressed as conclusions. And in a market where people stake real money on such verdicts, a hypothesis dressed as a conclusion is the most expensive thing of all.

Once, a sports company sent me the file of a swimmer for review before they signed a representation contract. The file ran thirty pages, full of praise articles, good photos, and one paragraph spelling out a peak achievement. But when I looked for detailed split times, there were none. When I looked for the date of the meet that made that name, there were none. When I asked for the pool length of that meet, there were none. Thirty pages painted a hero, but could not answer the three most basic questions. I advised them not to sign. They signed someone else. Four months later, that athlete faded completely at an international meet and disappeared from every results list.

I do not tell that story to boast that I was right. I tell it to point out something rarely admitted: most risk in swimming does not come from reading the data wrong, but from having no data and reading anyway. The gap is where temptation reigns. And the only way to resist it is the discipline of admitting the gap, instead of filling it with belief.

Takeaway

I still keep Basin No. 7 on my hard drive, untouched — not deleted, not filled in. It is a reminder that there are nights when the water refuses to speak, and my job is not to force it to talk, but to sit still long enough to hear that very silence. Swimming taught me what sixteen years in the trade still has not taught me fully: sometimes the most honest verdict is to leave a cell empty, and let the next round answer on its own.