Empty Stat Sheets and the Transparency Question in Vietnamese Volleyball

The national volleyball season has entered its return leg, and I am again sitting in front of the screen with my notebook open. Beside me is the packet the organisers sent after the last three rounds: the official statistics sheet, clearly printed, stamped in red. The “perfect pass rate” column is empty. The “successful blocks” column has numbers, but they do not add up to the video I have just rewound twice. The “squad status” section holds a single line: “No issues.”

Three weeks ago, a head coach told me on the phone that his squad was “at full strength”. Four days later, his first-choice outside hitter came on from the bench. I counted eleven jumps across the whole match, against an average of twenty-two last season. Nobody announced anything. Nobody denied anything.

I am not writing this to accuse a specific club; I do not have enough cross-checked data to do that. I am writing about a gap that is widening in the way Vietnamese volleyball publishes its data.

Context: four minimum data sets

In volleyball, a professional league must be able to publish four data sets. Perfect pass rate — the metric that decides whether the setter can run the entire tactical menu or is left with one desperate ball. Blocks per set. Aces against service errors. And dig rate.

In the Volleyball Nations League, the FIVB publishes all four after every match, alongside attack efficiency split by position: outside hitter, middle blocker, opposite, setter, libero. In Vietnam’s national championship, I receive an abridged sheet, frequently missing columns, and almost never containing load data.

Load data is the part worth discussing. A middle blocker jumps between sixty and eighty times per match; on every landing, the knee and ankle joints absorb several times body weight. The opposite — the position designed to carry most of the scoring — usually records the highest jump count on the team. Leading opposites such as Nguyễn Thị Bích Tuyền carry that load every week; anyone who watches volleyball can see it, but there is no official figure to check it against.

When nobody publishes jump counts and nobody publishes actual rest days, every injury can be told as an accident. And an accident needs no explanation.

I used to work as a team-doctor liaison. I know the process: the team doctor examines, writes it in the book, reports to the coaching staff, and the coaching staff decides how much to publish. Between the last two steps there is a grey zone. That grey zone is not always concealment. Often it is simply the laziness of a system without standards.

The causal chain the stat sheet hides

In 2026, when every competition stopped because of the pandemic, I sat down to re-classify the injury data I had collected over the previous five seasons — by position, by point in the match, by court surface. When the league restarted on a compressed calendar, I predicted a roughly twenty-eight per cent rise in hamstring injuries, based on the precedent of the dense 2026 schedule. The end-of-season result matched at close to eighty-nine per cent.

I retell that not to boast. I retell it to say that injury data is predictable, if someone is willing to keep the records. The dataset I built during the pandemic is still recording what they do not want published.

In volleyball, the causal chain is even clearer than in football. A middle blocker reduces her jump count for two matches in a row, then suddenly sits out one, then returns with taping on her shoulder. The press writes: “shoulder injury”. In reality, that is usually the end of a four-to-six-week chain: rising load during the run-in, shortened recovery, poor sleep from long travel, and one off-axis landing. The landing is only the last drop.

There is a technical detail rarely mentioned. In modern volleyball, an optimal line-up usually uses a middle blocker only in the front row. When the middle rotates to the back row, the coach makes a two-for-three substitution to keep three front-row attackers: a back-up setter and an opposite come on. That means a middle blocker’s minutes do not reflect her real load. On the stat sheet, she plays little. On the video, she jumps the most in the set.

A stat sheet missing columns creates a player who looks lighter than she is. And a player who looks lighter than she is gets given more load.

More worrying is how numbers get chosen for use. When a team needs to explain a defeat, it produces blocking statistics. When a team needs to protect a player, it produces scoring statistics. The same match, two different sets of numbers, depending on the spokesperson. Numbers do not lie, but the people who supply them do.

At the tactical level, the reception system decides almost the entire attacking power. When the perfect pass rate falls below a certain threshold, the setter is forced to push the ball to the wing, the opposite has to handle a difficult ball, and the block-against rate spikes. A team can lose three sets in a row because one passer has lost form, yet the published sheet usually records only “attack error”, blaming the scorer.

Behind the scenes, the youth pipeline is affected too. When data is not recorded from youth level, an eighteen-year-old enters the professional league with nobody knowing her injury history. The club signing her has one medical sheet, a few on-site measurements, and trust. Trust is a good thing, but it cannot replace a file.

Contrarian view: high technology on an empty data foundation

Vietnamese sport is eager for new technology. Major competitions are starting to talk about motion-tracking systems, performance indices and real-time data. I once spent two months cross-checking such a system against the paper medical records of team doctors. The conclusion: the new indices are trustworthy, but only when someone sits beside them to read with human senses.

The problem with Vietnamese volleyball is not a lack of high technology. It is a lack of things so basic they are boring: a public injury list, a unified definition of “injury”, a clear rule on who may publish and how much.

We are easily drawn to complex metrics because they feel advanced. But an advanced metric built on an empty data foundation is only a performance. The hard part is not buying software. The hard part is maintaining a habit of honest record-keeping across many seasons, including the seasons nobody notices.

Nor do I believe absolute transparency is achievable. A club has the right to keep a player’s personal medical information private. But there is a boundary between protecting privacy and staying silent to avoid being asked. That boundary blurs when there is no standard to check against.

One more detail is worth thinking about: when leading players such as Trần Thị Thanh Thúy go abroad to play, the data on them suddenly becomes far more complete than when they play at home. The same athlete, the same body, but different information quality depending on the organiser. That shows the problem is not Vietnamese people, but the standards of the system.

Takeaway

At sixty, I still open my notebook before every match — an old habit, but the data is always new. And I still do something younger colleagues consider a waste of time: checking the official statistics sheet against the video, phase by phase.

A muscle tear never appears overnight — unless someone wants it to. Injury is a fact. The announcement of an injury is a document that requires verification. Before trusting a diagnosis, look at who benefits from it.

If next season the organisers published just one extra column — the jump count of every athlete — the picture of the league’s health would already be different. Will anyone agree to print one more column?