The Empty Split Table and the Verification Discipline of a Swimming Analyst

Just write the analysis for me — it's fine if the data is blank, readers mostly read the headline anyway. That sentence came from a young colleague in the newsroom, attached to a draft about a 200-meter individual medley final. The headline was there. The outline was there. The opening was smooth. Only one thing was missing: the split table. No 50-meter splits, no reaction time, no backstroke-leg data after the turn. A bare table, four ruled lines, not a single digit. I looked at that table and recognized the feeling. On the night of July 6, 2026, I had sat in front of a number sheet of my own. The difference was this: that sheet was full, so full that I did not bother opening a second source. I wrote that Belgium pressed successfully 21 times in the quarterfinal against Brazil. The real number was 14. A reader pointed it out that same night, and I had to publish a correction before dawn. My mistake in 2026 reminded me that data is a mirror, not a lamp. Seven years later, an empty table put me in front of the same old question, only with a different sport. The craft of swimming analysis in Vietnam sits at an awkward crossroads. On one side are readers' expectations during the major-games season — SEA Games, ASIAD, the Olympics — where every medal is read through emotion before it is read through data. On the other side is the nature of the lane itself: a sport where almost everything decisive lies in quantities measured to the hundredth of a second. Put differently, swimming is the easiest sport to fake numbers in, and also the easiest sport in which faked numbers get caught. In Vietnamese sports media, the number of dedicated swimming analysts can be counted on one hand. Most swimming coverage stops at results: who won, what the time was, whether a record fell. The explanation of why is thin. That leaves a gap, and every gap has two ways to be filled: with data, or with inspiration. I choose the first, but I understand why many choose the second. Inspiration is faster. Inspiration needs no verification. I drew a data pyramid for my young colleague. The base is raw figures: reaction time off the start, splits for each 50 meters, total time. The middle layer is derived metrics: stroke rate, distance per stroke, turn time at each wall, stability of rhythm. The apex is tactical interpretation: who accelerated in which segment, who saved energy for the return length, who lost rhythm in the breaststroke leg of a medley. Leave the base empty and the middle and apex cannot exist. An empty split table is not a table missing detail. It is a building with no foundation. One more thing keeps me cautious: in Vietnam, deep swimming data is not always open. Domestic meets sometimes publish only the final result, not the splits. When the data is closed, an analyst has two choices: collect it personally by reviewing footage and timing by hand, or admit the limitation. The first is time-consuming but produces original value. The second is honest but rarely praised. I usually choose the first, and I state clearly that the figures are my own hand-timed readings, not official data — because a hand-timed number attributed to the wrong source is still a wrong number. The major-games season puts writers in an emotional bind. Readers are swept up in the flag and the story, and they deserve pieces that carry that emotion. But emotion does not need wrong numbers. On the contrary, an analysis built on solid data can inspire more, because it shows readers why a medal is so hard to win. What I hold to is this: stay close to what happens in the lane, not to the holes in the story. I gave my colleague an example. In the 400-meter individual medley, the four legs — butterfly, backstroke, breaststroke, freestyle — are nearly equal in length, but the energy distribution is not. The breaststroke leg is usually where the field separates most: the breaststroke kick technique, the glide after the kick, and the ability to hold rhythm once the muscles are tired. If I have a 100-meter split per leg, I can read who collapsed in the breaststroke leg, by how much, and whether the cause was technique or pacing. If I have only the total time, I know only who finished first. A winner with a worse breaststroke leg than the runner-up can still be told as a story of "grit," when in fact it is "hiding a weakness with the freestyle leg." That is why I cannot accept writing a piece whose pyramid base is empty. Stepping into Vietnam's football-data scene, I learned to stay silent in front of numbers. Those years taught me something I now carry over to the lane: the most honest answer when data is missing is "not enough data," not a number that sounds plausible. In the newsroom, we call it the null-value protocol. It sounds dry, but the principle is simple: whenever a data cell is empty, it must be marked "insufficient information to assess," and must never be filled with a guess. A table with three empty cells looks bad. A table with three invented cells looks good, until someone opens the source. I keep a two-source verification table before publishing any figure. For the lane, the first source is the organizer's official results. The second is broadcast footage or independent tracking data, to cross-check splits and turn times. If the two do not match, the figure is not cleared to run. This rule costs me three extra hours per piece, but it is the line between analysis and fiction. There is a subtle distance between missing data and wrong data. Missing data makes a piece shorter and drier, but it still stands. Wrong data makes a piece more attractive and quicker to collapse. Inexperienced writers often fear blank space more than they fear error. That is a fear misplaced. I showed my colleague my own 2026 case as precedent. The number 21 instead of 14 did not change the match result. It changed something else: it changed whether readers would still trust me in the next piece. A small wrong number in a long piece does not stay where it is. It spreads into other numbers, into how I am read, into the value of an entire column. Data only recounts; tactics begin with mistakes. And a data mistake begins no tactic at all; it only ends trust. Back to the empty split table. I told my colleague that without splits we can still write a decent piece, but we must change the question. Instead of asking "who won which segment," we ask "how does the structure of this event operate." That is a shift from reportage to the discovery of rules — exactly the direction I took from the football-free summer of 2026, when I moved to writing about rules rather than recounting matches. In a 100-meter breaststroke event, the rule lies at the turn. In breaststroke, each stroke cycle may contain only one kick, and after the start and after each turn, the swimmer is allowed one long underwater pull before surfacing. That underwater window, plus the quality of the glide, decides who surfaces with momentum. An analysis without splits can still measure this if footage exists, because we can count cycles and observe the length of the glide. But if there is neither split nor footage, all we have is memory. And I do not trust intuition. I trust how many variables that intuition has been loaded with. An intuition with no data loaded into it is just a guess wearing makeup. In distance freestyle events such as the 800 or 1500 meters, rhythm is everything. New viewers often think this is a speed race. It is not. It is a pacing race, where the winner is the one who holds a stable stroke rate longest without trading away distance per stroke. A 100-meter split table shows me who held rhythm and who broke it between 900 and 1200 meters. Without that table, I can only tell a story of a "lightning finish" — a story that is usually wrong, because most decisive finishes are built in the middle. Nguyễn Huy Hoàng is a case where I always want full data before writing. A long-course swimmer of Vietnamese swimming, tied to distance freestyle events. For swimmers like that, value lies in consistency across seasons, and consistency can only be read through split sequences across many meets, not through a single race. Nguyễn Thị Ánh Viên is the opposite case in how she is read. A multi-event swimmer, ranging from the individual medley to butterfly and freestyle. The more events, the more data cells, and the more likely someone fills an empty cell with inspiration. I have seen pieces assign a multi-event swimmer a "pacing strategy" simply because her final leg was faster than her first — when it may only have been the consequence of poor early pacing. The same data, two opposite readings. That is why a second source is required, and why multi-season context is required. There is another metric I always check before writing about any swim: reaction time off the start. The gap between two elite swimmers in this metric is often tiny, but in short events such as the 50 meters it can be the entire difference between a medal and fourth place. The problem is that this metric can only be read when the organizer publishes electronic data. If it is not there, the writer must say "no reaction data available," and must not guess. I have seen a piece assert that a swimmer "started slowly" based only on a feeling while watching television. That feeling may be right, but it is not data. In butterfly, backstroke, and freestyle, a large share of the first length is spent underwater. After the start and after each turn, the swimmer may stay underwater for a limited distance, and within that window performs the dolphin kick. The quality of the breakout after that limit decides the momentum of the whole length. This is the zone where tracking data is most valuable, because the eye struggles to measure the exact moment a swimmer surfaces. Without data, we easily credit a swimmer with "good technique" simply because the image looks pretty. The blind spot of this craft does not lie with bad writers. It lies with good writers pushed by speed. The major-games season is when every newsroom wants its piece ahead of the competition. That pressure turns an empty table into a temptation: fill in a plausible number, make the deadline, and hope no one checks. Most of the time, no one checks. That is exactly the problem. Punishment in this craft arrives late and unevenly, so many people learn the wrong lesson: they learn that fabrication is cheap and silence is expensive. I believe the opposite is true. A piece brave enough to say "not enough data to conclude" is a piece protecting readers from themselves. It is less attractive, but it does not plant a false belief in the reader's mind that then flows down into coaching decisions, into commentary about young athletes, into how a parent judges whether their child has potential. In swimming, this ripple effect is stronger than in many sports, because it is a sport children enter very early and stay in very long. A fabricated figure about a young athlete's "potential performance" can become a benchmark an entire training group follows. The writer does not see that consequence. But it exists. There is another, subtler temptation: filling in numbers by inferring from the total time. From the total, people "divide evenly" across the legs and produce a split table that looks plausible. That table is wrong in essence, because a lane is never evenly paced. A swimmer's rhythm has its own shape, and that shape is precisely what deserves analysis. Dividing evenly erases exactly what needs to be read. I returned the draft to my colleague with a single request: go get the official split table, or find footage and reconstruct it yourself. If neither exists, we write a different piece — one about the structure of the event, about the turn, about distance rhythm — and state clearly that the individual assessment is awaiting data. An empty table is not a full stop. It is a reminder that a good analyst is not the one who always has an answer, but the one who knows which answer they are not yet permitted to give. Tonight, before sleeping, I will ask myself a question like every night for the past seven years: in my most recent piece, was there any data cell I filled with a guess without citing a source? If so, I must fix it before the reader fixes it for me.