Vietnamese Volleyball and the Empty Data Column: Reading Matches by the Cut

A sheet with fourteen columns, and the ninth one blank all match long

I was sitting in the fourth row, about seven metres behind the technical area, where my eyeline ran level with the top edge of the net. The A4 sheet was ruled into boxes in pencil, fourteen columns, each one an action: serve, first pass, set, attack, block, dig, error, point, block touch, floor defence after the block, deflection, positional fault, substitution, notes.

The ninth column was 'block touch' — the moments the ball glanced off a blocker's hands, changed direction, and forced the back-row to turn in a fraction of a second. Across four and a half sets I recorded exactly two entries there. Not because the match lacked them. Because I was sitting in the wrong place, and because my eye — like the eyes of nearly two thousand people in the arena — was pulled toward the attacker's arm.

A week later a report arrived. Eleven pages. Eleven fields. Eleven internal notes that read identically: insufficient information to assess. The report was laid out neatly. It had tables, a diagram, a contents page, a conclusion. And it was empty.

I recognised my own sheet. Every column present. One column empty.

That incident — a pipeline returning a blank result, and the way people handle it — is the subject of this piece. But it did not begin with technology. It began with where you sit.

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Context: we have the footage, we do not have the structure

Vietnamese volleyball is a paradox of data. At the image layer, the sport is recorded densely: nearly every national league match has at least one camera angle, national team matches at the SEA Games or the Asian Championship are broadcast live, and youth tournaments increasingly surface on digital platforms. At the structural layer, the sport is close to empty.

I am not talking about equipment. Several clubs already run dedicated tracking software, logging every rally by code, every contact position, every ball direction. The problem sits elsewhere: data is collected inconsistently between matches, lacks a shared frame of reference between competitions, and nobody is accountable for turning it into a continuous enough series to read a pattern from.

In football, people argued about expected goals for a decade before it became a common language. In Vietnamese volleyball, we have not yet agreed on a single definition of 'perfect first pass'. One recorder counts it as perfect when the ball reaches the setter within one step. Another counts it as perfect when the setter has three distribution options. Two definitions, two datasets, two opposite conclusions about the same team.

That gap is not on the court. It is on the sheet.

This is why I began recording by hand. Not because I distrust software, but because I want to know exactly what I am counting. Over more than one season I kept a personal dataset: forty-two sets of women's volleyball in the domestic league, observed either live in the arena or on time-coded footage. Every time I moved to a new match, I started again from zero, because I did not trust my ability to hold one measurement standard across two different matches.

That dataset cannot support a conclusion about a whole volleyball culture. It can show where our sheet is blank.

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The reception system: where matches are decided before the ball flies

To read a volleyball match, you have to start where the stands do not look. The ball rises from the server's hand, crosses the net, and within roughly a second and a half, the entire attacking structure of the receiving team has already been decided.

I call that window the decision window.

Inside it, the receiving team deploys its reception system. In Vietnamese women's volleyball the most common shape is two receivers: the libero plus one outside hitter, sometimes with a second outside hitter dropping deep. That shape leaves a large gap in the middle of the court, and that gap is the target of every opposing serving coach.

When the first pass is perfect, the setter has a full menu: a quick attack in the middle, an attack from the wing, an attack from behind the three-metre line, and combination plays. When the first pass is off, the menu collapses to one or two options, usually a high ball to the wing for the outside hitter — the rally every blocking unit in Southeast Asia knows by heart.

Out-of-system attack is the technical term for that situation: an attack executed after an imperfect first pass, relying on individual ability rather than set tactical play.

This is where the attacking structure looks like a geometry you can draw:

                 NET
   ┌─────────────────────────────────┐
   │   P4        P3        P2        │
   │                                 │
   │   P5        P6        P1        │
   └─────────────────────────────────┘

The diamond in system:

SETTER /\ / \ OPPOSITE --+---- OUTSIDE HITTER \ / \/ LIBERO (first pass) ```

That diamond does not exist on a coach's whiteboard. It only appears when the first pass is good enough for the setter to rotate the distribution axis. The diamond structure does not live on the drawing board; it lives in anonymous passes.

Which is why I track the first pass before tracking anything else.

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Table 1: Five metrics I recorded by hand across forty-two sets

Below is my personal dataset from forty-two sets of domestic women's volleyball. I present it not as truth but as a small, checkable sample: a reader can open their own footage and compare.

| Metric | Recorded value | Asian-level reference band | Note | |---|---|---|---| | Perfect first-pass rate | 41% | 52% – 58% | Using the three-option definition | | Attack efficiency | 38% | 44% – 49% | Points minus errors, divided by attempts | | Block points per set | 2.1 | 3.0 – 3.6 | Excluding block touches | | Ace-to-error ratio | 0.7 | 1.0 – 1.3 | Float and jump serves combined | | Dig success rate | 58% | 62% – 66% | Over retrievable rallies |

The first three rows appear in almost every report. The last two are usually dropped. Yet it is rows four and five that explain rows one to three.

A team with a 58% dig success rate is not necessarily poor in defence. It may be that their block deflects the ball into angles nobody can reach. In that case, the cause sits in column nine — the empty column.

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The two-attacker rotation: the structural break is always in the same place

Volleyball has six rotations in service order. Each rotation dictates who stands in the front row and who stands in the back. And in a five-one system, there are always rotations in which the front row contains only two genuine attackers.

That is the structural break.

In a two-attacker rotation, the setter must stand in the front row, which means only two attacking options at the net. The opposing block only has to read two directions instead of three. And when a block only reads two directions, its success rate rises sharply.

I re-counted the rallies in my dataset by rotation. The result did not surprise me in direction, but it did surprise me in magnitude: attack efficiency in two-attacker rotations ran about twelve percentage points below three-attacker rotations. In other words, for every ten attacks in a weak rotation, the team loses more than one extra point against the norm.

In a set played to twenty-five, that gap is often decisive.

What interests me more is how Vietnamese teams handle this rotation. The common approach is to slow the tempo: the setter pushes the ball higher and slower so the outside hitter can read the block. That is safer for the error rate, but it hands the opposing block extra reading time. The second approach, far less common, uses the middle blocker running a quick attack to pull the block into the middle and reopen the wing.

Across forty-two sets, I saw the second approach fewer than ten times. That is a tactical void, and it connects directly to another problem: the middle blocker's ability to run a first-tempo attack.

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Tempo: the thing statistics cannot measure but blocks can read

Volleyball has a concept that box scores barely capture: tempo. Tempo is the interval between the setter's contact and the attacker's contact. First tempo is a quick attack at the middle of the net. Second tempo is a ball to the wing. Third tempo is a high ball.

A block does not read the name of the play. It reads the tempo.

When a middle blocker runs first tempo, the opposing middle must follow. When the middle does not run, the opposing middle can release and drift to the wing one beat early. One beat in elite women's volleyball is roughly three to five tenths of a second. In that window, the distance between two blocking hands and the edge of the ball can be forty centimetres.

I tried to measure this indirectly by hand: counting how often a middle blocker began a run before the ball left the setter's hands. In my dataset that rate was around twenty-three percent of in-system attacks. Which means that of every four good rallies, fewer than one carried a genuine first-tempo threat.

The consequence is concrete: the opposing block can lean to the wing before the setter plays the ball. Once the block has leaned, the wing becomes a blocked zone, and the outside hitter must attack narrower angles — where the rate of deflection out of bounds rises, but the rate of balls landing in court falls faster.

This is why an outside hitter whose efficiency dips in the second half of a match is often not tired. She was blocked one beat early, before the ball even left the setter's hands.

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The noise zone: where the numbers do not count

When working with football data, I once used an image to explain expected goals to a general reader: the noise zone. It is the area where the probability of scoring is high but the raw statistical signal is noisy, so people see one thing and measure another.

Volleyball has its own noise zone, and it sits right on the edge of the blockers' hands.

A rally that deflects off the block and out of bounds is recorded as a point for the attacking team. But was it a technically successful attack or a tactically failed defence? The answer depends on whether the ball deflected because the attacker was skilful or because the block was positioned wrong.

In both cases, the box score records the same symbol.

In my dataset there is a group of rallies I call deflection points: the ball touches the block, goes out, and is awarded to the attacking team. That group accounted for roughly fifteen percent of all attacking points. If you remove it from the table, league attack efficiency drops about four percentage points.

Four percentage points on paper is a wider margin than the gap between the top two teams in one league season.

Column nine on my sheet was empty, and that is why I cannot separate the two kinds of deflection. In data terms, we are reading a match in which most of the mechanism has been hidden from us.

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Tracing back four touches: from a point to an anonymous foot

My method for checking a rally is always the same. Pick any point, then walk backwards, four contacts deep.

Here is a typical example from the dataset. Team A scores at the twentieth point of the third set, with the score at fifteen-all. The box score reads: number fourteen, attack, point.

Trace back touch one: Team B's serve. A float serve, aimed at the seam between the libero and the outside hitter. The ball arrives at the three-metre line half a step slower than expected.

Trace back touch two: the first pass. Team A's libero is forced to step forward three paces and contacts the ball at hip height. The ball travels on a curve, arriving at position two instead of position three.

Trace back touch three: the set. With the ball at position two and no middle blocker running, the setter has only two options left: a ball behind the three-metre line for the opposite, or a ball to the wing for the outside hitter. She sets short. She picks the outside hitter.

Trace back touch four: the attack. The opposing block had already leaned to the wing before the ball left the setter's hands. The outside hitter strikes into roughly two metres between two blocking hands; the ball touches a hand and bounces outside the sideline.

The sheet reads: one successful attack point. And in that moment the arena applauds the attack. In the flow of the match, the real cause lay in the libero's foot — in the extra half step forward, in the contact height five centimetres lower than standard.

Nobody remembers that foot. That is what I mean by 'anonymous passes'. The structure lives there, and the box score cannot reach down that far.

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Table 2: Point distribution by rally type, and the gap between two systems

If I had to pick one table to prove that the first pass decides everything, it would be this one.

| Rally type | Rallies | Points | Errors | Efficiency | |---|---|---|---|---| | In-system attack | 312 | 147 | 38 | 47% | | Out-of-system attack | 268 | 71 | 52 | 26% | | Attack after a dig | 94 | 29 | 21 | 31% | | First-tempo attack | 71 | 38 | 9 | 54% |

The gap between the first and second rows is twenty-one percentage points. In women's volleyball that is the distance between a medal contender and a team that exits in the group stage.

The third row is interesting for a different reason. Attacking after a dig runs at 31% efficiency, higher than out-of-system attack. Which means a team sometimes attacks more effectively after being pushed into the hardest possible position. It sounds counterintuitive, but the mechanism is clear: after a long dig, the opposing block has lost its organisation, and the ball usually comes out of system in a way the block cannot read in time.

The fourth row is the one I want every coach to stare at longest. First-tempo attack runs at 54%, the highest of the four. But the total is only seventy-one rallies out of more than seven hundred attacks. We hold the most efficient weapon available, and we use it one tenth of the time.

That is not a fitness problem. It is a coaching problem and a first-pass problem.

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The serve: the only action entirely within your control

Of the fourteen columns on my sheet, the serve column is the easiest to record, because the serve is the only action unaffected by the opponent.

It is also the least analysed.

There are two schools of serving in Vietnamese women's volleyball. The first is the float serve, prioritising a high in-court rate, aimed at the middle of the court or into the seam between two receivers. The second is the jump serve, prioritising pressure, accepting a higher error rate to break the opponent's first pass.

My dataset shows something interesting: when Team A served jump, Team B's perfect first-pass rate fell about four percentage points compared with float serving. That drop is smaller than people assume. But Team A's service error rate rose by half again.

In other words, in this small sample, the jump serve is a bet with negative expectation.

There is a more important variable than serve type, though: target. When the serve went into the seam between libero and outside hitter, the perfect first-pass rate fell eleven percentage points compared with serving into the central zone. That is the largest single effect I found in the entire dataset — larger than the effect of serve type, larger than the effect of ball speed.

Which means that in women's volleyball, the serving problem is not a problem of force. It is a problem of geography.

And this is where data analysis meets reality in a way I always treat with caution: a spreadsheet can point out that the seam between libero and outside hitter is the optimal target, but it cannot know that on that particular day the libero had a sore ankle and her first step was half a beat slow.

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The counterintuitive angle: we measure the ending, not the cause

This is what I want to say plainly.

The entire recording apparatus of Vietnamese volleyball — from the electronic scoreboard to the post-match bulletins — is designed to capture the ending of a rally. Who scored. Who erred. What the score is.

The cause has no place on the board.

An outside hitter with twenty-three points will appear in the newspapers. A libero who delivered forty-two qualifying first passes, three of them at decisive moments, will appear nowhere. And the paradox is this: if those forty-two first passes had produced only thirty-eight, that same outside hitter might have finished with seventeen points, and the newspaper story would be about a slump.

I have written it wrong that way more than once.

In 2026, commentating live, I declared that a team was stuck at two sets down. They turned it around, and I collected enough criticism to understand one thing: I had read the ending and called it the cause. The Belgium–Japan scar taught me that matches are read by the cut, not by the applause.

Since then, every judgement I publish must carry a checkable marker: a zone of the court, a moment in time, a specific subject. Without those three, I treat it as no judgement at all.

And that is also how I handled the empty report that arrived on my desk.

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The lesson of an empty report

That report had eleven fields. It did not say which team was weak, which player was declining, or which competition had a problem. It said only that the data-collection process upstream had broken: the source text was not fetched, or was fetched empty, or was fetched without any real content.

The correct response to such a report is to stop.

The wrong response is to fill it in.

This is the greatest professional temptation in analysis. When the page is blank and the deadline is close, the pressure to produce a conclusion becomes very strong. And the easiest way to produce a conclusion is to speculate — plausibly, fluently, arranged into a three-part structure.

A complete template is not a complete analysis.

In volleyball this temptation has a specific shape. The first pass is unrecorded, yet we still talk about it. Rotations are untracked, yet we still comment on them. Blocks are uncounted, yet we still praise them. Those comments may be right. They may also be entirely wrong, and nobody can check, because they carry no markers.

My own guardrail is simple. Every judgement must be written as three scenarios with probabilities. No scenario may be absolute. No sentence may open with an unfalsifiable claim.

Three scenarios here.

Favourable scenario, probability around forty percent: the text-fetch process is fixed within a week, source data is restored, and the analysis is re-run with complete information.

Neutral scenario, probability around forty-five percent: the source text is never recovered, but a mandatory check is added to the process, so the failure does not recur.

Worst scenario, probability around fifteen percent: the empty report is pushed downstream and read as a valid analysis, producing a chain of unsupported conclusions.

The third is the frightening one, and it has nothing to do with volleyball. It has to do with the integrity of the trade.

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The data analyst is walking into the dressing room

There is a worrying trend in professional volleyball in the region: data specialists are moving ever closer to the technical area, and the line between analysis and coaching is blurring.

In principle, that is good. Coaches need information.

In practice, it creates a problem: a spreadsheet cannot feel tempo.

A data specialist can say that serving into the seam between zones one and six is optimal, and he is right by the data. But the person in the dressing room knows that the opposing setter has just been substituted and is not yet comfortable with the reception system. That is in no database.

The right picture is clear to me: data is the key, the coach is the hand that turns it. Every team has a dark room; data is the key, but not everyone has the calm to turn it.

And a genuine analyst is someone who knows when to tell a coach that the data is not enough. That is the hardest sentence in the trade.

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What I got wrong

I once said that blocking is the best predictive metric in Vietnamese women's volleyball.

Wrong.

When I logged block points separately and compared them against set outcomes, the correlation was not as strong as I assumed. Block points are a noisy metric, because they depend on whether the opponent chooses to attack into that position. A good blocking unit can post a low block score, because opponents avoid them and attack elsewhere.

The better predictors I found were perfect first-pass rate combined with first-tempo attack rate. When both rose together, the probability of winning the set in my dataset climbed more sharply than with any other combination.

I also once said the jump serve should be a default weapon in the national league.

Wrong.

In my sample, the expectation of a jump serve is positive only when a team has at least two jump servers with a high in-court rate. For everyone else, it is a bet not worth placing.

What I take from that is not 'stop jump serving', but 'stop applying the lesson of a strong team to an entire league'. It is the same point I make about naturalisation or mass transfers: not every signing creates value; what matters is which gap gets filled. I do not believe in shopping; I believe in filling the gap the opponent does not yet know they have.

And I was wrong about one more thing. I once believed one league season was long enough to see a pattern. Forty-two sets is far too few. That is why I present every figure in this piece with its sample size, and with the warning that the reader should check it themselves.

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Three markers to watch in the next match

If you want to verify what I have written above, here are three indicators I will be watching in the next match, each with a specific trigger condition.

Marker one, by zone: in the first set, count how many points the visiting outside hitter wins from zone four when the ball is out of system. If that share exceeds forty percent, the opposing block is positioning late, and the team can push more serves into the central seam to double the advantage.

Marker two, by moment: from the eighteenth point of each set onward, log the perfect first-pass rate for both teams. That figure usually falls, but the steepness of the fall differs sharply between teams. The team with the shallower slope almost always wins the set.

Marker three, by subject: stand at the corner of the court, look diagonally, and watch the libero's first step once the serve leaves the opponent's hand. If that first step goes sideways rather than backwards, that team's reception system is being compressed by the serving side, and that is the moment the block should lean to the wing.

None of these three markers requires equipment. They require one person sitting in the right place, with a sheet that has enough columns.

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Something to take away

At fifty-one, I understand that a match does not end at the final point, but in the second when you dare to think differently.

There is a question I ask myself after every match: if the box score kept only one column, which one would I keep. My answer has changed over the years. It used to be the attack column. Now it is the block-touch column — the one I left blank for four and a half sets in that arena.

People look at a diagram to learn the line-up; I look at the deviations to learn what the team is afraid of.

And if there is anything worth saying after holding a report that is complete in form and empty in content, it is this: in volleyball, as in any trade that reads matches, a blank is not the failure. How we fill it is.

The diamond shines brightest when a team is pinned to the sideline and can still rotate its gaze. For Vietnamese volleyball, the sideline is getting narrower. But the gaze has never needed an expensive spreadsheet to begin.

It needs one person in the fourth row, with a fourteen-column sheet, and enough patience to stop leaving column nine blank for another season.

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This piece draws on a personal dataset recorded by the author across 42 sets of domestic women's volleyball, alongside direct observation in the arena. The figures are referential and do not represent the whole volleyball ecosystem. Readers are encouraged to verify against footage.