Nine Blank Fields in Vietnamese Athletics Files

The A4 sheet lay on the meeting table in a small office on Nguyen Thien Thuat Street, Nha Trang, on the morning of November 7, 2026. The assessment table had been printed to the exact nine-section framework I designed for organisations that hire me to evaluate performance. I read from the top down, pencil resting across the first line.

Performance section: N/A. Competition conditions: N/A. Split segments: N/A. Qualification mechanism: N/A. Anti-doping: N/A. Nine sections, forty-seven lines, the letters N/A repeated thirty-one times. The person across the table folded the pages, pushed them toward me and said: “Just assess it from experience.”

My experience does not replace data. That sheet never told me which stadium the athlete ran in, how many metres per second the wind was blowing, whether the time was taken by hand or by an electronic system, whether the surface was synthetic or packed earth. The meeting ended twenty minutes later. The only conclusion I signed: insufficient information to assess — and that is a professional verdict, not a refusal to work.

I have been reading results since 2026, when I joined Runner’s World and wrote thousands of pieces about running. Those early years taught me one simple rule: a mark only carries meaning beside the conditions that produced it. A 100m time without wind speed is half a sentence. A marathon without a split record is a number that cannot be diagnosed.

In 2026 I published a series using xGA to show that the Thanh Hoa defence — then praised across the media as the best in V.League — was conceding far more than expected: 1.9 goals per match, with the goalkeeper saving only 64% of shots. The coaching staff called me the man sitting in the cold room. On February 7, 2026, Thanh Hoa lost 0-3 to Ulsan Hyundai in the AFC Champions League play-off, exactly the script the numbers had drawn beforehand.

In 2026, the PPDA metric took me to Russia. While most media praised the German defence, my spreadsheet showed their PPDA had risen from 7.3 to 12.8 between the 2026 qualifiers and the 2026 qualifiers — a signal of lost high pressing capacity. I wrote that Germany would go out in the group stage and colleagues laughed. On June 27, 2026, Germany lost 0-2 to South Korea and finished bottom of Group F.

In 2026, when Vietnamese stadiums stood empty, I compared Binh Duong’s 14 home matches with crowds (xG 1.85 per match) against 10 without (xG 1.31) and concluded that home advantage had been inflated by 29%. That study took me out of the newsroom and into a full-time data consultancy contract from August 2026.

Since then, Vietnamese football has gained something athletics still lacks: a standard data box at the end of every match report, holding xG, xGA, save percentage and sprint counts. That standard was adopted by my former newsroom in 2026 and remains mandatory. In athletics — the sport I was trained in most deeply — we still stop at two columns: name and time.

The nine-section file I received on November 7 was the fourth such sheet I had been handed in 2026. Numbers never lie. They simply wait for someone sober enough to listen. But when the sheet holds no numbers at all, the listener is obliged to say what they hear: emptiness.

Athletics is a sport whose rulebook states the valid conditions of a mark. Assisting wind speed is capped at 2.0 metres per second for events under 200m; beyond that threshold, a result cannot be officially ranked. Altitude above 1,000 metres thins the air and shortens sprint times. Temperature and humidity determine how well a body sheds heat.

My N/A sheet held no line for any of those variables. Which means that if an athlete ran 10.85 seconds, I do not know whether that came on a still afternoon or with a 1.9 m/s tailwind. The gap between those two scenarios, in the model I use, stretches to 0.12 seconds — a third of the distance between gold and bronze at a national championship.

The timing system was also absent. Hand timing can read roughly 0.24 seconds faster than an electronic system, and World Athletics regulations recognise records only when times are captured electronically. A results sheet that does not state the timing method is a sheet that cannot be verified.

Before trusting a reputation, I need to see the data behind it. For an athlete, that data is the personal best (PB) curve and the season best (SB) plotted over time, laid against the age curve.

Male sprinters commonly peak between 24 and 27; women earlier, usually 22 to 26. A 19-year-old running 11.00 seconds is a growth signal. A 29-year-old running the same mark is a plateau signal. Identical figures, opposite conclusions.

The N/A sheet had no date of birth, no PB sequence, no current-season SB, no injury note for the past thirty days. It is impossible to say whether the athlete sits on the rising or falling slope of a career — which happens to be precisely the question a coaching staff pays to have answered.

The selection mechanism section was entirely blank. A place at an international meet can arrive through three routes: hitting the qualifying standard, accumulating world ranking points, or being nominated by the federation under a quota. Those three routes carry different physical costs and different closing dates. Qualifying early allows long-cycle training. Qualifying late forces a peak into a single week, and forced peaking is the fastest way to tear a hamstring.

An athlete who does not know how far they sit from the standard cannot plan. A coaching staff that does not know the standard cannot choose the schedule. Nobody in that chain holds a number, so everything runs on feel — and at elite level, feel is the most expensive and least accurate instrument available.

The file also lacked any picture of the opposition. To know what a mark is worth, I need three layers of data: the level of the leading group, the depth of the chasing group, and the rate at which young talent has been produced over the past three years.

A nation with one athlete at 10.20 and ten athletes under 10.60 is stronger than a nation with one at 10.10 and the rest above 11.00. In the second case, one injury to the leader wipes out an entire relay squad. Depth is insurance; a lone star is a speculative asset.

The N/A sheet held no comparison table, not even against regional neighbours. We compete in a region where every rival publishes split data, while at home we cannot read ourselves.

The rules and anti-doping layer was likewise empty of inputs. At professional level, an athlete’s file includes whereabouts schedules, therapeutic use exemptions, and equipment status.

On equipment, World Athletics limits stack height to 20mm for track shoes and 40mm for road shoes. A carbon-plated shoe at the permitted limit can save an athlete roughly one to two per cent in energy cost, and over 10,000m that percentage is worth tens of seconds.

Ignore the rules layer and a good mark may belong to the shoe rather than the leg. Ignore the doping layer and an abnormal leap may belong to chemistry rather than the training plan. An analyst has no right to attach either possibility to a named athlete without evidence, but is obliged to record both in the risk section.

Team and training systems were blank in all three dimensions: coaching capability, technology and rehabilitation infrastructure, and staff stability. An athlete who changes coach mid-Olympic cycle typically needs six to nine months to rebuild a fitness base.

I once built a file for a swimmer and found that the only stable element across four years was a shoulder injury. Reading the training log revealed the cause: volume was increased during the recovery block. Without a log, nobody would have seen it.

The N/A sheet had no training plan, no periodisation calendar, no recovery data. To judge a season, I need to read it as a sequence of probabilities, not a sequence of events. And a probability sequence can only be built when you know how each week of training actually unfolded.

The risk matrix was empty across all six categories: competitive, doping, financial and career, rules and eligibility, public opinion and brand, systemic operations. For a rising athlete, the largest risk is usually not injury but the competition calendar.

Four meets in eight weeks, each with two maximum efforts, equals four peaks in two months. The human body does not hold four peaks. It holds one, and then a debt that the athlete pays with an injury the following season.

Finally, the media and expectation layer. A strong results sheet can generate expectations that outrun the underlying base within forty-eight hours. When the baseline data is unpublished, those expectations have nothing to anchor to, and they drift freely until they fall at a major championship.

The last station is industry transmission. Athletics data, when published with enough fields, flows into six branches: competition commercialisation, equipment technology, representation contracts, the youth talent chain, adjacent markets, and the national team ecosystem. Without data at the source, all six run on guesswork.

A sponsor does not sign on the basis of a medal. They sign on the basis of predictability. What cannot be measured cannot be priced, and what cannot be priced attracts no money.

From those nine stations I draw one minimum proposal, called the Eight Fields, mandatory in every publicly released Vietnamese athletics results sheet: electronically timed result; wind speed; temperature and humidity; surface type; split segments; name of the timing system; shoe model code; injury status in the thirty days before the meet.

These eight fields do not require expensive technology. A handheld anemometer costs under ten million dong, timing software can export split files, and a federation-issued template costs nothing. Two of those three already exist at venues that host national-level meets.

The obstacle lies elsewhere: nobody has yet seen a reason to record. And a reason only appears when someone pays a price for the absence. A sponsorship contract tied to data would make those fields appear within a single season.

The counterintuitive part of this profession is that most of the value sits in the fields left blank. Any model can generate a table packed with numbers, and in the age of automation, filling empty cells has become so cheap that people fill them with adjectives instead of measurements. “Great fighting spirit”, “deep fitness base”, “coming into form” — those three phrases can fill all nine sections without a single measurement.

The true capability of a data department lies not in how many cells it fills, but in how many it dares to leave empty. A file with thirty-one blank lines is worth more than a file stuffed with prose that contains not one verifiable row.

I worship data, but I pray through empirical testing. In this case the first and only test is wind speed — something anyone present at the track could record. When even that information does not exist, any five-star rating I could produce would be a rating built on air, and the person who pays is the athlete pushed into a major meet with the wrong expectations.

The 2026 season is approaching. The signal I am waiting for is not a new record. I am waiting for two extra lines printed at the bottom of a results sheet: wind speed and timing system. If those two lines appear at two consecutive national championships, all nine blank sections will find somewhere to stand.

And if they remain absent, the answer to every professional assessment request in the coming year will still be thirty-one letters of N/A.

Data box: Nine-section analysis framework (performance, athlete condition, qualification mechanism, competitive landscape, rules and doping, team system, risk matrix, media expectations, industry transmission). Forty-seven lines, thirty-one marked N/A. Proposed mandatory Eight Fields. Legal wind threshold: 2.0 m/s. Hand-timing error: approximately 0.24 seconds. Shoe stack limits: 20mm track, 40mm road.