Full of N/A: A Sports Analysis That Teaches Honest Storytelling

I opened a sports analysis document with nine sections: patch meta, tournament format, roster, staff, club finance, rules, risk, public narrative, and industry transmission. Each section had a clean table. I scrolled down, then scrolled back up. All the analysis was reduced to one phrase: insufficient information, cannot assess.

In an empty stadium, I hear my own voice more clearly than ever. Not because the document is meaningless, but because it shows something sports media rarely dares to do: admitting, I do not know yet.

Modern sport runs on instant opinions. After the final whistle, fans need someone to explain why a team won, why a coach picked the wrong player, why a young star suddenly shone. In South Korea, where I live and host a podcast, that pressure is even stronger. Broadcasters need a sound bite within seconds. Social platforms need a headline hot enough to pull in viewers. In that machine, saying “let me check further” is almost a taboo.

That is why a document that fills nine blocks with N/A, instead of inventing a comfortable conclusion, feels radical. I read each table and each note again. There were no player names, no transfer figures, no tactical verdicts. But I did not see an unfinished piece. I saw an analytical framework reflecting on itself: it forces readers to confront how little we truly know about what we call the sporting world.

We often confuse watching many games with understanding the game. The screen broadcasts 90 minutes, but it cannot transmit what happens in the dressing room. We can count expected goals, successful passes, distance covered, but those numbers do not tell us about a hamstring injury, about a growing fracture inside the team, or about why a striker suddenly fears receiving the ball. N/A in sports analysis is itself a form of data: it measures how thin the layer of public information is. It does not tell us which team is stronger, but it tells us that our evidence is not yet enough to answer a bigger question.

During my postgraduate research, I once got stuck in a project without enough variables to run a model. My supervisor said something I remember to this day: the biggest early discovery is not the result, but the empty fields in the data. Those empty fields are where the next questions belong. Sports writing works the same way. A report should only conclude when the evidence is heavy enough to carry a conclusion. When the data is incomplete, offering a smooth-sounding conclusion betrays the reader.

I once mispronounced N’Golo Kanté’s name three times on a live broadcast and nearly quit. But I did not choose to hide. I spent the next thirty days reviewing every France match and practicing player names. I pronounced it wrong, but I found the voice I did not know I had. I learned that admitting a mistake does not end a career, but pretending certainty when you are not certain can. By that same logic, a sports report that says “insufficient data” does not diminish the writer. It shows that the writer can tell the difference between guessing and knowing.

Reading more closely, I realized this document is less like an article and more like a map with white zones carefully annotated. Media people usually fear white zones because audiences do not want to look at silence. But in an empty summer, we still practiced for an invisible audience. When the pandemic shut down every league, I hosted a podcast called “A View from the Empty Seat.” I invited fans to tell me about their stadiums, and I learned that silence can make us hear more clearly. An N/A report is like an empty seat: it reminds us that some story has not been told, that some character has not appeared, that some fact has not yet been collected.

Of course, I could be wrong in reading this N/A document as a statement of journalistic ethics. Maybe the author simply had no time, or lacked the proper data access, or was disconnected from official sources. Perhaps a data-starved analysis system could become an excuse for lazy media work. But even in that case, the document remains useful: it reveals how much of the boldest sports commentary is built on a very thin foundation.

Toward the end, I want to think about what is verifiable in this season. If a report says a team played badly, I want to know in which phase: pressing, defensive organization, or finishing. If an article praises a coach, I want to know what he changed from last year. Data cannot answer every question, but it can teach us how to ask the right ones. And when data is missing, the most honest answer is often: I do not have enough evidence to say.

A season is always longer than one match. Some information only appears after five rounds, after a press conference, after a quiet injury. A great sports writer is not the one who guesses correctly most often, but the one who waits for evidence-based signals. The place that once doubted me is now where I find answers—by accepting that an answer may not have arrived yet. A report full of N/A is not empty. It is a reminder that sport still has dark zones that need light, and our job is to keep that light honest.