Re-reading Vietnamese Athletics: Wind, Altitude and the Gaps in the Data

At three in the morning in Nha Trang, my screen showed a results table with exactly one row. The athlete's name was correct. The distance was correct. But the most important field, wind speed, was blank. The 100m, 200m and 400m split fields were blank. The track condition, temperature and humidity fields were blank. A single mark stood alone on the page with nothing holding it up. I have sat with tables like that for years, and I learned something counterintuitive: a table with wrong numbers is easier to handle than a table with missing numbers. Wrong numbers can be cross-checked, corrected, traced. Missing numbers get filled in by the reader's imagination, and in sport the imagination always leans toward the prettiest version of the story. That night I wrote nothing. I stared at the empty field labelled wind speed and thought about a Vietnamese athletics season just gone, in which the most important parentheses of the sport were left behind on the track. Vietnamese athletics lives on SEA Games medals. Every Games, our sprinters, jumpers and throwers bring home enough medals to keep the country among the regional leaders, and each medal sets off a familiar cycle: celebration, bonuses, sponsorship, then expectation for the next Games. Behind the medal, the data is usually thinner than people assume. A result is published with a time and a name. Rarely does it come with wind speed, venue altitude, temperature, humidity, shoe model or detailed splits. In developed athletics systems, almost every run carries a data packet: per-heat wind, reaction time, peak speed, speed over the final ten metres, stride count and stride frequency. That gap creates a paradox. We have medals but not enough data to understand why. We have marks but not enough data to know how long they will hold. And when we do not understand why, we do not know what to repeat. I remember 2026, when I worked as a data consultant for a football site and was attacked for using metrics to say a team would win the title while it was being mocked as boring. Over their first fifteen matches they averaged 1.2 xG but scored 2.1 goals per game; the gap of nearly a goal came from shots inside the box. When they lifted the trophy I understood something I carry to this day: the data does not lie, only the reader has not learned how to listen. Since then I never publish a judgement without underlying metrics. With athletics I want to do the same: build a verification frame. Not to diminish marks, but to make them stand firmer. A SEA Games medal is worth more when placed beside wind speed, temperature and its position in the training cycle. A national record means more when we know the track, the hour, and how many weeks of heavy work preceded it. In other words, contextualisation is the identity. A mark stripped of context is only a string of characters. WIND: GENEROUS FRIEND, POLITE DECEIVER Athletics has a clear wind rule: in sprint and jump events, a mark counts for a record only when the assisting wind does not exceed two metres per second. Beyond that a star appears, and the star says the mark is real but cannot enter the record books. Two metres per second is not small. A 100m runner at 10.30 seconds can lose nearly two tenths if the wind flips. Over 200m the difference is bigger. In long jump, a well-timed tailwind can add twenty or thirty centimetres, enough to turn an ordinary attempt into a memorable one. In Vietnam most meets are held outdoors on tracks without synchronised wind gauges. Some meets have them, some do not. Some measure one heat and leave the next blank. Fans receive a list of times; analysts receive a list of questions. I once sat beside a young coach at a domestic stadium. He pointed at the track and said the wind was blowing down the straight, so his athlete would run faster. He was right. But when the board flashed the result, nobody recorded that the wind helped. A few months later the same athlete ran slower, and public opinion began to question the form. In both cases the data stayed silent, and people had to guess. When the numbers speak, I only have to listen. When a number has had its wind cut away, it no longer knows how to speak. ALTITUDE AND THIN AIR Above a thousand metres, the air is thinner, drag falls, and sprints and jumps gain a systematic advantage. Mexico City sits about 2,200 metres above sea level, which explains why so many sprint and jump records set there in the late 1960s stood for decades. Most Vietnamese stadiums, by contrast, sit near sea level. That means our marks are set under physically harder conditions. A milestone achieved in Hanoi or Ho Chi Minh City is theoretically more valuable than the same milestone at a high-altitude venue. I stress this because it is often ignored in international comparisons. When two athletes are placed side by side, one at altitude and one on the plains, we are comparing two different conditions. To be fair we must convert to the same reference frame, which means adjusting. I have seen many comparisons between athletics nations with no adjustment at all. One side trains at altitude and competes at altitude, gaining twice from thin air. The other side, Vietnamese athletes, train on the plains and compete on the plains, and must manufacture the advantage through coaching. Placing the two numbers side by side and concluding who is better is a comparison that is wrong at its root. THE DIVIDEND OF CARBON SHOES Over the past decade, racing shoes with carbon plates and supercritical foam have shifted the baseline of performance, especially over long distances, half marathon and marathon. The systematic gain is generally recorded at one to three percent depending on distance and athlete. Three percent sounds small, but over a marathon it is minutes. The problem is that this gain is a dividend of equipment, not of muscle. Comparing a mark today with a mark ten years ago without accounting for shoes mixes two generations in one table. World Athletics had to cap sole thickness and require that shoes be available on the mass market for a set period, to stop a prototype giving a handful of athletes an unfair edge. That is how rules try to keep up with technology. In Vietnam, recording shoe model in a competition report barely exists. Leading athletes have access to good shoes, which is a positive signal. But without records, we will have a generation of marks whose own creators do not know what produced them. A national record without equipment information is a half record. ONE BRILLIANT DAY IS NOT CLASS This is the principle I hold tightest. A single mark does not show an athlete's class. It shows one good day. To form a diagnosis you need at least two runs, better three, ideally a series spread across months. I do not believe in luck; I believe in what has been repeated enough times. An athlete who runs well once may have done so because of wind, shoes, a rival pulling them along, or a good night's sleep. An athlete who runs well five times in five months has formed a trend. The trend is what deserves analysis. Alongside that principle comes a warning about unratified training marks. In athletics, the story that an athlete has run faster than a record in a closed session spreads easily. It is exciting, it feeds the imagination, and it has no comparative value, because training conditions are not standardised like competition conditions: no officials, no wind gauge, no shoe checks. In Vietnam I have heard training numbers passed around like legend. They may be true. But true in a session is not the same as true on the track. A data analyst must keep a distance from beautiful stories. THE PERSONAL-BEST EXPLOSION TEST When I study an athlete's file, the first thing I do is redraw the personal-best curve year by year. That curve usually rises slowly, with small jumps when the athlete matures physically, and flat years during injury or a coaching change. The test I apply is simple: if a single year's gain exceeds roughly three times that athlete's own historical annual average, it deserves a question mark. A question mark is not a verdict. It means I must look for the cause: a new coach, a new event, new shoes, new conditions, or simply a psychological lift. What I like about this test is that it judges nobody. It compares an athlete only with their own past, never with others. For Vietnamese athletics, where historical data is sparse, the test can run on just a few seasons, as long as we keep proper records. And I will say it plainly: a normal, slowly rising curve may look less exciting in the papers, but it is the most durable thing there is. Explosive curves tend to be followed by equally abrupt collapses. SPLITS: WHERE DATA GETS CUT A finishing time is the end of a process. The splits are the process. Without splits we know only who finished first, not why. In the 400m, the classic split is the first 200 and the last 200. An athlete who goes out too fast pays in the final stretch, and the splits show exactly where the break happens. In the 800m, 400m splits show pace distribution. Over long distances, pace per kilometre is the true measure of endurance. At many domestic meets, splits are not published. Debates after the race therefore circle the final time, and every analysis stops at the level of feeling. Every number is a confession the race cannot deny. But to hear that confession we need enough numbers to cross-check. A final time standing alone is a statement with half the sentence cut off. AN INJURY MAP BY EVENT When assessing an athlete's risk, I start by fixing the event, because each event has its own injury map. Sprints concentrate risk in the hamstring and Achilles, where the load is greatest during acceleration and at top speed. Middle-distance events share risk between the Achilles, plantar fascia and ankle. Long distance leans toward stress fractures, ankle pain and lumbar pain. Throws concentrate on the shoulder, elbow and lumbar spine. Jumps spread across the knee, ankle and back. This map lets me read an injury file far faster. If a 100m runner has hamstring pain, that is a very different story from a marathon runner with hamstring pain. Same location, different cause and treatment. In Vietnam, injury data is barely public. Athletes often stay silent for fear of losing a place. The result is that when someone suddenly runs slowly, opinion blames a form slump, when the truth may be an unhealed injury. Without an injury map, every diagnosis is a guess. QUALIFYING STANDARDS AND THE WORLD RANKING At international level there are two routes into a major meet: hitting a qualifying standard set by the federation, or accumulating points through the world ranking. The second route lets an athlete who never hits the absolute standard still compete, as long as their series is consistent enough inside the qualification window. For Vietnamese athletes the second route is often more realistic. But it demands something we are still weak at: consistent presence. To earn points you must compete often, travel, and have results properly recorded in the system. One detail to remember is the three-per-country quota in many events. In deep athletics nations this creates brutal internal selection, where a single trial decides everything and an athlete who has met the standard still stays home because three compatriots are faster. For Vietnam that pressure is not yet large in most events, but it is worth preparing for the future, when a few distances begin to develop depth. PEAKING AND THE TRAINING LOG Peak form is not a natural state. It is a planned one. To peak in a given week, an athlete must pass through cycles of accumulation, intensity, taper and release. Miss one beat and the peak lands when it is not needed, turning a major meet into a missed run. So I read the training log before I read the results. Total mileage, average pace, number of high-intensity repetitions, number of hard sessions per week. Mileage never lies; we simply have not been patient enough to listen. An athlete whose total mileage falls for three straight weeks before a meet is usually in a deliberate taper, not declining. Telling the two apart is a profession in itself. I once analysed a middle-distance runner whose sprint speed dropped sharply over the final two hundred metres. A colleague concluded the athlete had run out of fuel. I went back to the training log and found a large block of threshold sessions stacked across the previous four weeks. What had fallen was not fitness but short-term carbohydrate reserve, spent on a bigger goal. At minute seventy the crowd sees collapse; I see a structure being rebuilt. In athletics that minute seventy is the final two hundred, the last lap, the last throw. Where others see a fall, a data analyst must ask which structure is being built. An example I still tell younger colleagues is Nguyen Thi Oanh at SEA Games 32 in Phnom Penh in 2026, when she completed four gold medals, including two events contested on the same day. Looking only at the final results, you see a winning athlete. Looking at the schedule and the distance run across those two days, you see a pacing problem solved almost perfectly. The part not written on the scoreboard is the part most worth studying. By the same logic, Nguyen Thi Huyen and Quach Thi Lan in the 400m and 400m hurdles, Le Tu Chinh in the sprints, Nguyen Van Lai over long distances and Pham Tien San in the 800m are all files whose real value lies in the splits and the training log, not in the final time. Those are SEA Games medals already won, and how they were made matters more than the medals themselves. CORRELATION IS NOT CAUSATION Here I must add the warning I give myself every time I open a spreadsheet. Everything above is correlation. An athlete wears carbon shoes and runs faster: correlation. An athlete does more threshold work and finishes better: correlation. An athlete changes coach and the marks rise: correlation. There is no controlled trial in elite sport that lets us claim clean causation, because no one can make the same athlete run twice under identical conditions. The most dangerous moment in this profession is when we forget that limit. A coach sees an athlete improve after a new programme and concludes the programme is the cause. It may be true. It may also be sleep, a rival, cooler weather, or a psychological release after a conversation. Mistaking correlation for causation is the fastest way to repeat a mistake for years. And this is the lesson from that blank table. An empty dataset does not mean zero risk. When I see a blank in the wind column, the correct conclusion is not that there was no wind, but that it is unknown. When there is no injury data, the correct conclusion is not that nobody was injured, but that nobody recorded it. Emptiness has a strange pull: it invites us to fill it with plausible stories. A data analyst must resist that pull. Better to say we do not know than to say something that sounds good without evidence. SIGNALS FOR THE NEXT CYCLE The regular season is not a time to wait for medals. It is a time to accumulate evidence. For Vietnamese athletics I propose three minimum signals to track and record starting now. First, wind speed. Every meet with sprint and jump events should publish wind alongside results, even without an automatic gauge. A rough wind reading beats a blank field. Second, splits. For events of 400m and above, splits are the minimum condition for analysis. Without them, post-race commentary is only retelling. Third, an aggregated training log, not so detailed that it invades privacy, but enough to show weekly volume and intensity. Mileage and repetition counts are the most durable indicators a data analyst can have. An empty stadium does not make me lonely, because data is the echo of thousands of people. Each time a results table is filled in a little more fully, that echo travels a little further, and next time we do not have to guess from scratch. The task is not grand. It is simply to fill the blank fields before they are filled by imagination.