Diary of an Empty Sheet: When Swimming Data Is Not Enough to Conclude Anything

At Lạch Tray, I learned to read injuries from the very first numbers.

Tuesday morning, January 14. I opened my inbox and found a training-load monitoring file sent from a swimming training center in the north. The filename was explicit: DuongBoi_Tre_2024.xlsx. I opened it. The date column was complete from the start of the season. The training-volume column, the recovery heart-rate column, the long-set count column — the three most important columns for someone in my line of work — were empty from the first row to the last. Not one number. Not one note. Not one period.

This was the fourth time in two months. Not a one-off error. A pattern. And the pattern said something very clearly to me: someone wanted me to write an analysis about shoulder injuries in swimmers, but nobody was willing to record the data I would need to base it on.

I sat still for about twenty minutes. Picked up the phone, put it down. Didn't call. Because in this profession, there are moments when the first move — no move at all — is the only correct move.

The body is a closed system, but data is the key that opens it. Without the key, the door stays shut, and I have no right to guess what is behind it.

Many people in sport think a good analyst is someone who always has an answer. I believed that for roughly the first three years of my career. Then I realized: the person who always has an answer is usually the person who is inventing the answer. The person who says "not enough information" is the one being honest with the trade.

This essay is about that gap. Not the gap in the Excel file. The gap in how an entire swimming ecosystem operates — where people want to conclude faster than they are willing to measure slowly, where hope is placed higher than data.

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Last December, I received a similar request from a media outlet. They wanted a "deep professional analysis of injury risk for the national swimming team in the upcoming cycle." I asked three questions back: Do you have individual training-load data for each athlete? Do you have injury history detailed down to the muscle group? Does anyone track return-to-sport after injury?

Three days later, they replied: "We don't have that yet, but you can just analyze based on experience."

That answer scared me more than any injury number ever has. Because "analyze based on experience" sounds impressive, but it really just means telling stories by feel. And the feel of someone standing outside the lane cannot replace the training diary of an eighteen-year-old carrying sixty kilometers a week on their shoulders.

I declined. Not because I didn't want to write. Because if I wrote, I would have to invent numbers that don't exist, assign them a scientific weight they don't carry, and let readers believe they were facts.

In sports medicine, we call this a "null input." It differs from "sparse data." Sparse data still allows low-confidence inference. A null input allows none at all. You cannot build a building on a foundation without piles.

In Vietnamese swimming, null input is not a rare case. It is the default across most centers outside the national system. Clubs have good coaches and talented young athletes, but no one sitting down to record what is happening to their bodies every day. By the time the shoulder hurts, the knee hurts, the back hurts — you start from zero. And from zero, every diagnosis becomes a guess.

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I want to tell a specific story, even if it comes from a field closer to football than swimming.

In 2026, I tracked 412 minutes of Harry Kane's play in the World Cup group stage in Russia. I was not the only person counting his goals. I was one of the few counting his sprints — and comparing them to his season average at Tottenham. Sprint intensity dropped 12 percent. Nobody talked about that number. Everyone talked about the goals. Three weeks later, Kane faded in the knockout round, scoring nothing from the round of 16 on. The media called it a "World Cup curse."

Kane 2026 was not a curse, but simple subtraction. He was minus 12 percent sprint speed, and the remainder was not enough to make a difference in matches where opposing defenders sat two meters deeper.

I tell this story in an essay about swimming not to talk about football. I tell it to talk about method: when you have a number, you can predict. When you have no number, you can only lament.

In swimming, that number is meters per week, hours per day, strokes per length, shoulder-load volume, elbow-catch angle on entry, recovery days between hard sessions. All of it is countable. All of it can be recorded. And all of it is being left blank at most of the swimming centers I know.

The number is silent, but its sequence always knows how to tell a story. The problem is we are erasing that sequence from day one of the season.

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I have worked as an injury analyst in swimming for nearly ten years, counting from when I started at Thanh Niên Báo in 2026 as a swimming reporter. In 2026, at twenty-six, I moved to an assistant injury-analyst role at a football club in Hải Phòng. In my first season, I built my own training-load monitoring system and logged 127 injuries across 43 monitored players. The coaching staff thought the approach was "too defensive." But after four months, cross-referencing with national-league injury precedents, I identified eight high-risk players and helped the team cut injury-related days lost by 23 percent compared with the first half of the season.

That number — 23 percent — is not an achievement. It is a consequence of record-keeping. If I had no four months of data, I would have nothing to compare against. And with nothing to compare against, I would not have noticed who was drifting off baseline — until they were already injured.

The first principle of injury work is this: an injury does not begin with a fall. It begins with a number deviating from baseline — and a baseline requires data to exist.

In swimming, this principle is stricter still. Swimming is a sport of repeated motion at extreme frequency. A butterfly swimmer completes roughly 15 to 20 stroke cycles per length. A 5,000-meter session means more than 800 shoulder rotations. Times six days a week, times four weeks a month — and you have an overload model the body cannot recover from without proper rest.

Swimmer's shoulder is the clearest example. It does not come from a collision. It comes from thousands of times the shoulder tendon gets pinched under the acromion during the entry phase. Every pinch is a micro-trauma. Micro-trauma accumulates into inflammation. Inflammation into pain. Pain into injury. And by the time the athlete tells someone their shoulder hurts, the process has been running for months.

That is why record-keeping is not administrative procedure. It is the only early-warning device we have.

Every fall has a graph, and every graph has a break point. My job is to read that break point before it happens.

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Having said that, I have to address the most uncomfortable thing in this field: the gap between those who hold data and those who hold the microphone.

At most Vietnamese swimming centers, the data holders are young assistant analysts like I was ten years ago. The microphone holders are head coaches and administrators. In many cases, the two groups never sit at the same table. The result is data collected but never read; and decisions made but not grounded in data. A system running for nothing. A process turning without load.

In 2026, when football returned after a five-month pandemic suspension, I was working at the PVF Sports Medicine Center. Clubs played in empty stadiums, schedules were compressed. I recorded a 40 percent rise in hamstring injuries in the national league compared with the same period the prior year. I proposed that one club adopt a ten-day progressive loading protocol for substitutes. The head coach refused, wanting to win the opening match immediately.

By matchday five, the non-compliant teams had lost 15 percent of their squad to injury. The team I was tracking stayed intact.

Empty stadiums, golden rules bent, and the body pays the price. When there is no crowd, people think pressure is lower. The reverse is true. When no one is watching, technique is easiest to neglect. And when technique is neglected, the body receives the bill.

I tell the football story to talk about swimming because the mechanism is the same. A swimmer returning after three months off for the pandemic has slightly atrophied shoulder muscle; the training volume stays the same as before. Result: shoulder pain after two weeks. Not because of swimming. Because of swimming the same old volume on a new fitness base.

That is the lesson I have written again and again: the golden rule of return after interruption is not to come back fast. It is to come back at the right rhythm.

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Now I return to the empty Excel file on my desk.

There are three possible explanations for it being empty. One is technical error: someone forgot to save, or the format was corrupted in sending. Two is systemic error: the center never had a recording process, so there was nothing to send. Three is strategic error: someone wants me to conclude first, then backfill data afterward to justify the conclusion.

Of the three, only one is harmless. The other two signal a deeper problem in the field.

The second — systemic error — worries me most, because it is more common than people think. Imagine a swimming center with 40 athletes, a head coach working 12 hours a day, no assistant analyst, no load-monitoring software, only a notebook and memory. Injured athletes are recorded with a single line in the medical log: "right shoulder, 5 days off." No onset date, no training volume that week, no idea which set changed. When that athlete re-injures six weeks later, nobody can compare the two injuries. Nobody knows whether this is a new problem or the same unresolved one.

That is medical blindness. And it is currently the default.

In 2026, invited as a senior expert on a sports TV analysis team, I had the chance to see the difference between swimming ecosystems. I tracked 48 group-stage matches at a major international event and recorded 31 muscle injuries. Four years earlier, at a comparable event, the number was 19. Instead of rushing to condemn the new tactics, I classified each case by match temperature, recovery gap between games, and pressing volume. I built a risk-correlation table. My conclusion was cited by a European sports-medicine journal.

What I learned from that process is simple: the difference between a sport with data and a sport without is not who is hungrier. It is that, when a problem appears, the data holders can find the cause; those without data can only find someone to blame.

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There is a question I have never dared answer directly in my earlier pieces: is Vietnamese swimming genuinely short on data, or over-supplied with confidence?

After ten years in the field, I lean toward the second answer.

Because a data shortage is a problem money and time can solve. Buy software. Hire an assistant. Build a process. Three to five years and you have a system. But over-confidence is a cultural problem. It is not solved with money. It is solved by changing how people think about the relationship between feeling and evidence.

The over-confident believe they know their athletes well enough to skip record-keeping. The over-confident believe twenty years of experience on the pool deck can replace a monitoring sheet. The over-confident believe "I can see it by looking" is a methodology sufficient for decision-making.

I do not deny the value of experience. A good coach's experience is an asset that cannot be bought. But experience without data is like a physician who diagnoses only by feeling a forehead. It may guess right. It cannot prove it is right. And it cannot be passed to the next person.

That is the biggest problem. When experience is not recorded, it dies with the person who holds it. When data is recorded, it lives on through the next generation.

In swimming, we are losing too much experience each time a coach retires. Because most of their knowledge was never written down.

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So if I were forced to write an analysis of that empty Excel file, what would I write?

I would write four things.

First, I would write about the structure of a swimming ecosystem without data. It has three layers: the coaching layer — working on instinct; the medical layer — working on incidents that have already happened; and the management layer — working on competition results. These three layers rarely talk to each other in the same language. The coach says "how did you feel today." Medical says "does it hurt." Management says "are the results better." Nobody speaks in the language of training-load numbers — the only language all three can share.

Second, I would write about the cost of emptiness. A young athlete with a shoulder injury at 17 can lose a season. But if that injury is a recurrence of an unresolved problem from age 15, the real cost is not one season — it is three years of distorted development. If we do not record, we will never know how much we paid.

Third, I would write about what can be done immediately. A simple spreadsheet. Four columns: date, training volume in meters, training intensity by heart rate, and body status on a 1-to-10 scale. Thirty seconds of logging per day. No expensive software. No specialists. Just one person responsible for recording.

Fourth, I would write about the need for the injury analyst to have the right to say "not enough information." This is something I rarely see among colleagues, because the pressure to always have an answer usually outweighs the pressure to be honest. But if we cannot say "I don't know," we will have to say "I know" in cases where we actually know nothing. And that is when injury analysis becomes number-guessing.

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I have been criticized for being too technical. An editor once told me: "Reader doesn't want to read tables. They want stories."

I think he was half right. Readers want stories. But a story with no numbers is just an anecdote. And a sport built on anecdotes will collapse when it meets evidence.

So I refuse to choose. I write both. The story of a 17-year-old butterfly swimmer with shoulder pain, alongside his twelve-week training-load chart. The story of a training center that lost three athletes in one season, alongside a load graph showing the break point exactly at week eight. The story of the empty Excel file on Tuesday morning, alongside an analysis of three possibilities and four things I would write if forced to write.

When both appear together, the reader is moved and given a tool to check that emotion. That is the boundary between sports journalism and sports analysis.

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From Moscow to now, I have never seen a conclusion that was right without data behind it. Even when it was right, it was right by luck, not by method. And in this field, a conclusion right by luck is more dangerous than one wrong by method. Because a conclusion wrong by method gets fixed when the method is fixed. A conclusion right by luck never gets fixed, and will be repeated until luck runs out.

Harry Kane not scoring in the 2026 knockout round was not a curse. He didn't score because his sprint speed dropped 12 percent, and because knockout-round defenders know how to stop a striker twelve percent slower. If he had scored, we would have had no lesson. The beauty of sports science is this: it is only right when reality is right. And it is only right when reality is measured.

I have kept that empty Excel file on my machine. I have not deleted it. Whenever I read an analysis with no data anywhere in it, I open it to remind myself. An empty sheet is not a failure. An empty sheet is a lesson waiting to be written down.

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There is one thing I have never told anyone in the field. The night before I sent my decline to that media outlet, I sat for a long time in front of the computer asking myself: am I being too rigid?

I could have written a piece. I know enough about shoulder injuries, have seen enough swimmers, have enough seniority to be trusted. I could have written an analysis that sounded very convincing, built on general sports-medicine principles, illustrated with well-known cases. Readers would be satisfied. The editor would be satisfied. The sponsor would be satisfied. And I would never be checked, because nobody has data to compare against.

I chose not to write. Not because I am rigid. Because I understand something about this profession: the credibility of an injury analyst is not built by pieces that sound good. It is built by the ability to decline pieces that sound good but are not true. Every time I decline, I lose an opportunity. But I keep something more important: the right to be believed when I actually speak.

In a field where evidence is still thin, credibility is the only asset an analyst has. Without it, every piece is just an article.

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Someone will ask: so in your view, do we have to wait for complete data before writing anything?

No. If we waited for complete data, we would never write, because complete data is a concept that exists only in textbooks. In reality, we always write with incomplete data. The question is not how much data we have, but whether we are honest about how much we have.

A piece with three data points that says "I have three data points" is a trustworthy piece. A piece with three data points that says "I know for certain" is a dangerous piece — not for the writer, but for the reader.

In Vietnamese swimming, there is a common belief that athlete injuries come from "constitution," from "bad luck," from "overtraining," from "the coaching staff changing the program." These four explanations are not mutually exclusive. But none can be verified without data. All are plausible stories, not testable hypotheses.

The only way to turn them into hypotheses is to measure them. What does "constitution" mean? It means this athlete's injury rate is above the group average, measurable. What does "bad luck" mean? It means the injury occurred in a rare situation, classifiable. What does "overtraining" mean? It means volume exceeded the tolerance threshold, comparable. What does "changing the program" mean? It means a training-program shift in a short window, recordable.

All four explanations can turn from story into data. It just takes one person willing to spend thirty seconds a day recording.

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I want to end this piece with an observation that is not particularly pleasant.

Over the past ten years, I have read many analyses of athlete injuries in Vietnamese sports media. Most share the same structure: name the athlete, describe the injury, recount the time off, predict the return. What is missing from all of them?

The numbers. No numbers on training volume before injury. No numbers on recovery speed. No numbers on recurrence probability. No numbers on career impact.

That is why I wrote this piece. Not to criticize colleagues. But to say to the next generation: if you want to do this work seriously, start by recording. Not by writing. A good writer without data is only a good storyteller. A good record-keeper who cannot write is already an injury analyst.

The body is a closed system, but data is the key that opens it. I have written that line many times and will write it again. Because I believe that one day, a swimming coach in Vietnam will open a spreadsheet, log their athlete's training volume, and discover what no one has discovered in ten years: that injuries do not come from bad luck. They come from a line of data left blank, repeated often enough to become fate.

And when that day comes, the empty Excel file on my desk will no longer be needed.