An Athletics Analysis Sheet Filled With N/A: The Evidence Standard Under Strain

The report ran nine sections and sat on a monitor in Osaka. Every column read the same. Performance metric: N/A. Qualifying status: N/A. Season ranking: N/A. Nine risk flags, none of them ticked. Not one number, not one name, not one date.

The sender attached a single line: the source provided no information points.

In twenty-nine years of reading athletics result sheets, I have received no fewer than three hundred reports of this kind. Most of them were not empty at all. They were stuffed with numbers — 400-metre splits, pace fluctuation between laps, the share of running time above lactate threshold, heart-rate distribution charts. And most of them were just as worthless as this N/A sheet. They simply hid the emptiness more skilfully.

Context: nine questions and the price of completeness

The nine-section framework on my screen is not a software product. It is the question set I use in betting analysis: performance and results, athlete condition, qualification mechanism, competition landscape, competition rules and anti-doping, training system, risk matrix, public narrative, and industry transmission.

The order is not arbitrary. It moves from what can be measured to what cannot, from milliseconds to market belief. When a source lands on my desk, the first thing I do is not read its conclusion but establish how many of these nine questions it actually answers.

The report on my screen answered none of them. It was an empty frame with every box ticked.

What matters is that such sheets are multiplying across the industry, yet they are rarely submitted blank. Editors want a complete sheet. Readers want a complete sheet. So the writer fills the gaps with the nearest available substitute for data.

Three evidence layers any athletics sheet must clear

The first layer is the validity of the number itself. World Athletics technical rules state that a tailwind above 2.0 m/s removes record eligibility from marks in the 100 metres, 200 metres, long jump and triple jump. The number still exists, still enters the minutes, but it is no longer the same quantity. An analysis sheet that omits wind speed has skipped this layer.

The current men's marathon world record is 2:00:35 by Kelvin Kiptum, set at the Chicago Marathon on 8 October 2026 and ratified by World Athletics in early 2026. Four years earlier, on 12 October 2026, Eliud Kipchoge ran 1:59:40 in Vienna — faster, but never ratified because of the pace car and rotating pacers. Two numbers, two entirely different legal statuses.

The second layer is the equipment dividend. Since 2026, World Athletics has capped racing-shoe sole thickness at 40 mm, permitted a single rigid plate, and required the model to have been available at public retail for at least four months before competition. The rule exists because a generation of marathon marks was suspected of being the product of super-elastic foam rather than of lungs. Any comparison that places a 2026 mark beside a 2026 mark without deducting the equipment dividend is comparing two different sports.

The third layer is qualification value. The Paris 2026 men's marathon entry standard was 2:08:10, inside a performance window running from 1 November 2026 to 30 April 2026. In the 10,000 metres the figure was 27:00.00. Alongside it runs the second pathway: the World Athletics Rankings, operating since 2026, allocating places on accumulated points. An athlete can hit the standard and still miss out, and can miss the standard and still get in, if the ranking points are sufficient.

These three layers explain why I never read an athletics sheet from the top down. I read from the bottom up: rules first, equipment second, performance last. Performance is the easiest thing to measure, and therefore the easiest thing to misuse.

At the narrative layer, another class of evidence appears constantly: training marks. Every season, a few names are said to have run under some threshold in a closed session, and the figure spreads before any official confirmation exists. Those numbers are not meaningless — they indicate a baseline capacity. But they are not competition marks, and any ranking that mixes the two is selling the reader a degree of certainty the data never possessed.

At the compliance layer, the cost of error is far higher. The Athlete Biological Passport tracks blood and urine markers over time; three whereabouts failures within twelve months are enough to constitute an anti-doping rule violation, even with no positive sample on record. A risk sheet that leaves this box blank leaves blank precisely the box that can end a subject's career.

At the industry layer, the flow runs from the track to the market. When super-elastic foam appeared in major marathons, racing-shoe sales followed, entry standards were pushed upward, and youth cohorts were trained against the new benchmarks. That chain moves slowly, but it moves surely. It is why I track it in years, not in fixtures.

The contrarian angle: the N/A sheet is the most honest one in the drawer

In a market where every sheet must carry nine sections, emptiness becomes a defective good. Nobody wants to submit a blank frame. So the nine boxes get filled with three materials: unverifiable figures, accurate but irrelevant figures, and inference dressed up as figures.

The third kind is the most dangerous. It is not technically wrong, but it builds a bridge between correlation and causation and then calls the bridge a conclusion.

The N/A sheet on my screen does not make that mistake. It states plainly that it does not know. To someone whose trade is pricing risk, not knowing is worth more than being confidently wrong.

But fairness demands this too: the N/A sheet is not an achievement. It signals an intake process that failed at the first stage. Nine blank sections do not prove there was nothing to measure; they prove only that nobody measured.

Based on my experience tracking matches, I once spent nearly a month reviewing an entire group-stage footage archive because a single detail was missed at the recording stage, bending every conclusion downstream. The cost of repairing an error at the data-entry stage is always several times the cost of recording it correctly in the first place.

When everyone is looking in one direction, I start examining the gap behind their backs.

Takeaway

Numbers never lie; the liars are the people who choose how to read them. But before anyone gets to choose a reading, there has to be a number to read. The question I carry into next season is not who wins, but this: of the hundreds of analysis sheets that will be published, how many will genuinely clear the first layer?