Vietnamese Volleyball and the Data Gap Nobody Wants to Measure

That night I reopened the statistical sheet of a match in the national championship. Three sets, more than a hundred rallies, twenty-five final points. Every column had a number: attack points, block points, service errors, positional faults. But when I asked for the winning team's perfect-pass rate, nobody could answer. When I asked how many block touches that team averaged per set, I was handed a rounded figure with the word “roughly” attached. When I asked for the scoring efficiency of the starting opposite in set four, the answer was: “She played well.”

I do not look for value where the spotlight is pointed, but where someone forgot to plug in the power. In Vietnamese volleyball, the unplugged socket is wide enough to hold an entire sport.

Results arrive first, measurement infrastructure arrives later

Vietnam's women's national team won gold at SEA Games 31 on home soil in Hanoi in May 2026, beating Thailand in the final. It was a milestone generations of fans had waited for, and it opened a cycle of attention the sport had never had: more live broadcasts, fuller arenas, more sponsorship, and more regular appearances in continental competitions. Attention came first. Measurement infrastructure came later. The distance between the two is the subject of this piece.

Picture the information pipeline of a volleyball match. At one end sits a scorekeeper with paper and pen. At the other sit journalists, coaches, scouts, and people who do this work for a living, like me. Between the two ends there must be a standardisation layer: a definition of what counts as a perfect pass, what counts as an out-of-system attack, who cross-checks, where the data is stored and who can open it. In Vietnamese volleyball, that middle layer is close to empty.

Across nearly three decades of watching volleyball, and more than twenty consecutive years of live commentating on finals, I have learned something that sounds paradoxical: we watch an enormous amount of volleyball and record almost none of it. A match is watched by hundreds of thousands on screen and thousands in the arena, but when it ends, what remains is a scoreline and a few summary lines. Three months later, nobody can reconstruct that match with data.

Three metrics that sit outside the light

Volleyball is a sport where every point begins with a pass. The perfect-pass rate determines how much of the attacking menu the setter is allowed to call: middle attack, back-row attack, wing isolation, or only one option left — pushing the ball to the wing for the opposite. That single metric shapes almost the entire identity of a team, yet it does not exist in the public data of the national league. Without it, nobody can separate a team with a varied attack from a team with one good attacker.

The second metric is block touches. A block that deflects the ball upward for the defence to counter is not recorded in the “block points” column, yet it is the largest source of indirect points in modern volleyball, especially for teams without a height advantage. Current box scores record only the final outcome, never the cause that produced it. That is the kind of data that teaches readers to misunderstand the match.

The third metric is attack efficiency split between in-system and out-of-system. When the first pass breaks down, the setter is forced to push the ball to the wing or send it to an attacker facing a single blocker. That is where individual value is genuinely tested. But in the statistics, that rally is counted simply as “one attack point”, identical to a rally built from a good first pass, a sound second ball and a block that stretched the opposing defence. Two actions that differ in technique, in success probability and in systemic value are collapsed into a single number.

Take an illustrative case from my own viewing experience. An opposite who routinely handles broken balls, such as Tran Thi Thanh Thuy or Nguyen Thi Bich Tuyen, creates value at precisely the moment the system has already failed: the box score records one extra point, but does not record that the team was just rescued from a situation that should have cost it a point. In the other direction, a middle blocker such as Hoang Thi Kieu Trinh can touch the ball on the block ten times in a match while the block-point column shows two. And a setter such as Doan Thi Lam Oanh can hold the tempo all match long without a single metric capturing it, because setters are measured by successful sets, not by the number of times they kept a team from collapsing.

Who records these numbers, and under what conditions

Most Vietnamese volleyball data today is recorded by hand, under real-time pressure. The scorekeeper must simultaneously track service position, rally development, technical faults, substitutions and the score. Classifying a pass accurately as “perfect” or “good” under those conditions is close to impossible — not because the recorder is weak, but because the job design does not permit anything better.

I once sat beside a scoring desk at a youth tournament. In the first two sets I counted eleven rallies I judged to be perfect passes; the sheet had six. Nobody was cheating. Human eyes have physical limits, there was no slow-motion replay to cross-check against, and the recorder had other duties. If we insist that six is correct because “it is the official number”, we have converted a systematic error into a fact.

The consequence is not a few percentage points of deviation. The consequence is that a volleyball ecosystem loses the ability to audit itself. To improve, a team must know where it loses: in the first pass, in defensive transition, in fifth-set physical management, or in reading the block. Without data, every answer falls back on perception, and perception in sport always favours whoever speaks loudest, whoever is most famous, or whoever won the most recent match.

A season compressed into a few weeks

The national championship generally runs in a compressed window, with rounds packed into short blocks and wedged between windows reserved for national teams and youth events. That compression hurts data work twice over. On one hand, the number of matches per day rises, so recorders must spread their time across more fixtures. On the other, matches are staged in different arenas with different recording crews and different standards, which makes cross-match comparison unreliable.

At youth level the gap is wider still. Under-18 and Under-20 tournaments usually publish only the scoreline. That is the paradox: the period that matters most for evaluating an athlete's development — for comparing an eighteen-year-old hitter with the same player at twenty-two — is the period with the least data. Scouts are then forced to rely on the impressions of people who watched in person, and those people cannot be at every tournament.

National team and domestic league: two different measuring systems

A player who performs well in the domestic league can face an entirely different challenge at national-team level, and there is currently no dataset that allows the two environments to be compared systematically. Block height, the tempo of the opposing setter, the first-pass quality of teammates, the number of recovery days between matches — all of it changes, but the metrics being recorded do not change with it. People compare a point tally from a domestic match with a point tally from an international match as if the two contexts were equivalent.

For Vietnamese players who move abroad, the gap is even clearer. In a foreign environment they are evaluated on metrics nobody measures at home, and it is often those very metrics that decide whether they get on court. Based on my experience following matches, successful overseas contracts tend not to belong to the highest scorers, but to those who hold the rhythm of the system: stable first pass, well-timed block movement, no errors at decisive moments. None of that is visible in the domestic box score.

An expensive gap in the transfer market

The transfer market buys stories; I only buy evidence. During the transfer window, clubs race to sign names with the most discussion around them, and contract value tracks fame more than fit. The genuinely valuable signings usually sit at smaller clubs, where the coaching staff pays for a specific role inside a system: a middle blocker who defends position three well, a libero who reads the game, a setter who can slow the tempo when the team is trailing.

To buy by role, you need data to define the role. Without data, the market can only buy aura, and aura does not block balls. The tighter the foreign-player quota, the more expensive each error becomes: every misused import slot is not only money lost, it is a development slot taken away from a young domestic player.

The counterintuitive angle

The first reaction most people have when they hear about a data gap is to demand more data. I do not believe in that direction. Football has already given us a clear enough lesson: xG has been abused to the point where many forget it does not explain a goalkeeper's decision, does not measure second-half form, and does not account for refereeing standards. A good metric used badly creates a new layer of illusion, and that layer is harder to peel away than having no metric at all.

The second risk is importing models wholesale. International models are built on leagues with different average heights, different setter tempos and different first-pass quality. Applying them directly to Vietnamese volleyball produces conclusions that sound scientific but are wrong at the root. Germany 2026 taught me the most expensive lesson of my career: clean data does not mean clean reality. I once trusted a beautiful model, ignored a human variable, and paid for it with an entire portfolio. The lesson that remains is not “do not use models”, but “know what a model cannot see”.

The third counterintuitive point: an empty dataset is more honest than a clean dataset filled in with guesswork. When there are no numbers, people are forced to say “I don't know” — and that is the beginning of all serious analysis. When there are numbers but the numbers are wrong, people will conclude, publish, buy and sell, and never go back to check the source.

Where to start

No large analytics platform is required. What is required is one agreed definition for three metrics, and a group of recorders trained to capture those three metrics correctly across an entire season, in every match, to the same standard. Those three metrics are perfect-pass rate, attack efficiency separated into in-system and out-of-system, and block touches that lead to a counterattack. They do not require expensive technology. They require patience and an agreement on definitions.

Alongside that sits storage. Data must be stored in an open format, with a match code, a date, the recorder's name and the recording conditions. A number without provenance is not data; it is a rumour presented in digits. In sport, rumours and data share the same shape but differ in whether they can be checked.

And a cultural rule is needed: publish what could not be measured. If a rally cannot be classified, write “undetermined” rather than forcing it into an available box. A mature volleyball ecosystem is not the one with the most numbers, but the one that knows clearly which of its numbers are real.

What remains

After that year, I stopped asking what the data says and started asking what the data is hiding. In Vietnamese volleyball, the data is hiding almost the entire story: it hides the first touch that decided the match, the block that produced no point but produced a win, the stretch in which an opposite had to carry the team through the fifth set. None of that needs a laboratory to uncover. It needs someone to sit down after the match, write it down, and keep the definitions unchanged until the season ends.

The data gap is bad news, because it forces every argument about Vietnamese volleyball to stop at the level of feeling. It is also an opportunity, because a gap means nobody has arrived first. Next season will bring a few dozen more matches, and they may well pass without leaving anything behind but scorelines. The question is not who will be champion. The question is whether, after that season, we will have one more page of trustworthy numbers to argue with.