When Data is Empty: Lessons from a Swimming Analysis with No Information

I received a request to analyze an article about swimming. But when I opened the input file, I found nothing but empty fields. No athlete names, no technical metrics, no competition results. Just a nine-dimensional analysis framework filled with 'N/A — insufficient information'. This is not the first time I have encountered corrupted data. In 2026, I wrote wrong pressing numbers for Belgium in a World Cup quarterfinal because I trusted my memory too much. Since then, I have learned that staying silent in front of numbers is better than embellishing them. Data only tells stories, but mistakes begin with failing to verify. In swimming analysis, the first step is always to identify the subject: which swimmer? what distance? long course or short course? Without these three, any evaluation of technique, tactics, or doping risk is groundless. I don't believe in hunches. I believe in how many variables that hunch has been fed. This article, therefore, is a reminder. If you see a sports analysis without original data, question it. If you see a data report whose source is hidden, demand transparency. Thirty-two years in the trade taught me: data is a mirror, not a lamp. If the mirror is foggy, don't try to polish it with imaginary numbers. A summer without football is when high pressing reveals its skeleton. A summer without data is when analytical discipline is tested. Look into the gaps between numbers — don't fabricate them.