An Empty Data Table and the Ethical Limits of Table Tennis Analysis

That night, when I opened the aggregated file from a round of the WTT system, I saw a blank page. Every field — athlete names, set scores, spin indices, ball speed, point-win rate within rallies — was empty. Not a single line. A newcomer to the trade would immediately open a fresh file and fill it with whatever they half-remembered: some player who had just won, some shot that was trending. I stayed still. That blank file taught me something my twelve years in sports data had never fully taught me: sometimes the most honest thing an analyst can do is refuse to speak.

The feeling was identical to walking into an arena with no spectators. An empty hall does not conjure ghosts; it produces the cleanest data a monk could ever dream of. With no roaring crowd to distort things, every serve, every topspin loop, every lateral footwork motion leaves a clear trace. But when the data table itself is empty, the problem no longer lies with the match — it lies with the person reading the match.

Context: table tennis enters the era of numbers

Over roughly the past decade, professional table tennis has transformed dramatically. The WTT system, with its rolling 52-week points cycle, forces every player to plan each tournament like a financial move. A title brings both a trophy and a block of time-limited points. When old points expire, a ranking can free-fall even if the player has not lost a single extra match in that period.

Alongside points pressure, the volume of detailed shot-level data has grown exponentially. One can now measure ball speed, spin, trajectory, player positioning, and point-win rate across each phase of a set. In theory, this is an analyst's paradise: the more variables, the more ways to understand a match.

In practice, however, most of the content readers encounter remains emotional storytelling. An idol wins, an idol loses, a once-in-a-lifetime shot, a curse stretching over years. Data is used only when it illustrates a pre-existing story; it becomes a postman for prejudice rather than a lamp shining into dark corners.

For Vietnamese table tennis, this gap is even wider. Domestic tournaments, youth competitions, and regional qualifiers often leave behind only a final result. There is no detailed metric sheet, no point-by-point record. Writers are forced to read matches with their eyes, take notes by hand, and accept that their data is always incomplete.

That is why the blank file made me think so hard. It forced me to face a simple but uncomfortable question: when there are no numbers, what will I do?

Core: a chain of evidence, not a pre-written story

My job is to reconstruct the truth of a table tennis match through numbers. I do not write about table tennis; I write about the dents a player leaves on a chart. A powerful loop at a decisive point is not a legend; it is a data point, and that data point only means something when placed beside hundreds of others.

Take the example of a PPDA-style metric I once used to overturn how people viewed a defensive midfielder. In table tennis, one can build an analogous index: how many strokes, on average, an opponent must execute before winning a point against a defensive player. This metric exposes what the scoreline hides. A player can lose a match and still force the opponent to pay a very steep price for every point they win.

Or another index I call "conversion rate from advantageous positions." Many players generate a great number of favorable rallies but convert only a small fraction into points. That rate reflects composure at the decisive moment — something a highlight never fully conveys. A player who wins three straight sets may still be playing a deeply inefficient brand of table tennis if you read their point distribution carefully.

Yet for a metric to carry weight, it must rest on at least two independent sources. One quantitative: score sheets, sensor data, stroke-by-stroke records. One qualitative: direct observation, expert notes, slow-motion video analysis. When one is missing, I say it plainly: I do not yet have enough evidence.

The interesting thing is that in table tennis, what is usually missing is not the number but the context. A player scoring many points on their serve does not automatically mean they serve well; it may simply be that their opponent that day was far too weak at handling spin. A player with a high win rate at one tournament may simply have had an easier draw. Context is what a score sheet will never tell on its own.

That is when the two sources must complement each other. I sit before the screen to attack, but what I defend against is the arrogance of numbers. A beautiful model is not allowed to be stronger than an unverified truth.

The counterintuitive angle: correlation is not causation

The most intractable problem in modern table tennis analysis is the illusion of pattern. Given enough data, a computer will always find patterns — including patterns that do not exist in reality. Most of them are noise, but they are very persuasive because they carry numbers.

For instance, we observe that players who win a lot tend to execute more topspin loops. Hasty conclusion: the topspin loop is the winning formula. It sounds very reasonable. But this correlation may only reflect a different mechanism: when leading, players choose a safe approach; when trailing, they are forced into risky attacks. The same data, two opposite mechanisms, and one completely wrong conclusion.

The story of a major knockout match I once analyzed for an outlet several years ago is a textbook case. A player lost, yet posted a higher expected-value index than the opponent for most of the contest. The media looked only at the scoreline and saw a collapse. The data showed something else: their midfield line was isolated by a matching scheme, not by individual incompetence. The loser was the system, not the person.

That was when I was criticized. People said I was defending the loser, "smearing" the winner. But I defend no one. I only read the dents on the chart, and those dents tell a story the scoreline refuses to tell.

The biggest blind spot among table tennis fans is not a lack of technical knowledge. It is the belief that a single metric can explain an entire match. A player who wins thanks to luck at decisive points is still a player who won, and that is not wrong. But if we look only at the "wins" column, we will miss the truth that their created value was lower than the opponent's — and that next time, when luck no longer favors them, the result will differ.

The gap between what we know and what we tell

The craft of sports data analysis now faces a major temptation. When a blank file appears, when a model yields nothing, when data sources contradict each other — the easiest response is to fill the gap with plausible-sounding speculation. And once speculation is written in a confident voice, it lives on forever. It seeps into other articles, gets cited again, and finally becomes a "fact" no one bothers to verify.

I once watched a false statistics table spread across dozens of articles simply because no one cared to trace its origin. The first person who invented that figure probably only wanted to fill a blank cell in their report. The last person to cite it believed they were quoting a credible source. Between those two people lay a blank no one filled, and that blank was the real problem.

In table tennis, where deep data remains scattered across federations, tournament organizers, and commercial platforms, the risk is even greater. Each party holds one puzzle piece, and no piece is enough to reconstruct the full picture. The most clear-headed analyst is the one willing to say: this piece, I do not have.

A forward-looking take

I do not believe in plugging data gaps with imagination, however beautiful that imagination may be. What I believe in is a new generation of table tennis analysts who treat the refusal to conclude as a skill rather than a weakness. They will build models with publicly stated "limits," say clearly when there is not enough evidence, and let readers reach the final judgment themselves.

That blank data table was eventually filled — after I called three different sources and confirmed every number. But the memory of it stayed. It reminds me that in a sport that unfolds at the speed of a breath, where every point passes in seconds, the slowness of the person verifying the data is an expensive but necessary thing.

The question I leave for myself, and for anyone who reads table tennis through the lens of numbers: if tomorrow you receive a blank page, will you fill it with evidence — or with a story good enough that no one dares question it?