Nine Dimensions of Analysis, Not a Single Cell of Data

In March 2026, an esports organization in Ho Chi Minh City sent me a 42-page report on its roster ahead of VCS Spring. Nine analytical sections: meta, tournament format, lineup, region, finance, competition rules, risk, communications, industry value chain. Every data cell printed exactly three characters — N/A. Not a few blank cells. Nearly all of them.

I read the whole thing in one evening. What bothered me was not the missing numbers. The report had a table of contents, charts, a four-tier risk scale, and a two-page synthesis conclusion. An empty skeleton packaged so carefully that a skimming reader would mistake it for deep analysis.

Based on my experience tracking matches across domestic leagues over the past four seasons, I believe this is not an isolated case. It is a symptom.

Context: when the framework arrives before the data

Since 2026, the number of Vietnamese esports teams with at least one person holding the title of analyst has grown from a handful to more than twenty, based on what I have observed attending tournaments. Alongside that is a trend of buying or copying multi-dimensional analytical frameworks from abroad. The frameworks sound impressive: nine dimensions, twenty metrics, four risk levels.

The problem is that the input data does not come with the framework.

In major leagues like the LCK or LPL, every metric has a public source: league websites, publisher APIs, independent statistics sites. In the VCS, most granular data — lane metrics, objective control rates by phase, teamfight numbers by blood group — is not fully published. An imported framework runs on a largely empty data source, and the system automatically fills every cell with "N/A."

Someone should have said at that point: we do not have the data. Instead, it was presented as a complete report.

Domestic basketball repeats the story differently. The VBA publishes basic box scores after each game: points, rebounds, assists. But what decides wins and losses — shot quality, shot location, who creates the open look — appears in no table. Teams also import tracking frameworks, also fill half the sheet, and leave the other half blank.

Analysis: where the data actually lives

I once kept a spreadsheet tracking every match of a group of VCS teams across two seasons. My work was purely manual: rewatch the VOD, log the first teamfight, log the kill trades, log the tower timings, log the dragon timings. One match took about 50 minutes. More than 180 matches, meaning more than 150 hours in front of a screen.

That nine-dimension framework cannot be run by hand like that. It needs automated data, and automated data does not exist at that scale. Vietnamese esports bought an analytical tool from an ecosystem with open data, then used it inside a closed ecosystem.

A lost teamfight is worth more than a boring win. But to know whether a teamfight was lost to a positioning error or to an opponent reading the play well, you need data on where players stood ten seconds earlier — something the end-of-game scoreboard does not carry.

The real data lives in three places. Inside scrim VODs, which are team private property, neither shared nor aggregated. Inside official scoreboards, which hold only KDA, damage dealt, resources. And inside the heads of head coaches and veteran players.

None of those three places is the kind of raw material an imported nine-dimension framework can consume. So a report full of "N/A" is not the result of laziness. The staff ran the right process on the right tool; the tool simply needs materials that are not here.

I have seen a good report. It was four pages long, with no nine-dimension framework. It read: the opponent wins 68% of teamfights when leading at the tenth minute, and loses 71% when trailing. From that, it drew exactly one decision: rotate mid lane at the eighth minute. Four pages, one decision, sourced from 22 VODs.

The cost of an empty skeleton

I noticed one detail at several teams: the cost of maintaining the framework and the person operating it lands somewhere in the hundreds of millions of dong per season, counting analyst salary, software, and the coach's time spent reading the report. With that budget, a team could hire one more full-time VOD analyst — someone who produces data instead of consuming data that already exists.

This is where the story leaves the analysis room. Small VCS teams are often pushed into raising semi-finished products for big teams: develop, loan out, then lose the player when the price rises. An expensive but empty framework operates on the same logic. It creates no competitive edge. It creates a professional image to convince sponsors and the parents of young players.

That 42-page report may not serve the coaching staff. It serves the meeting room.

A fact worth remembering

SofM (Le Quang Duy) is the only Vietnamese player ever to reach a World Championship final, with Suning at Worlds 2026. That run came from a roster analyzed very carefully, but not with a nine-dimension framework. It came from the Suning coaching staff reading the specific weaknesses of each opponent in each phase of the game, using data the tournament already provided.

Names like Kiaya (Tran Duy Sang) or Levi (Do Duy Khanh), who came up through domestic academies, did not get there thanks to analytical frameworks either. They got there through scrim hours and a coach willing to sit and rewatch VODs with them.

Qatar 2026 proved one thing: even the strongest side has blind spots. In esports, the biggest blind spot for Vietnamese teams right now is not skill. It is the belief that buying a tool means buying capability.

Counterpoint: where I might be wrong

I am writing this so you argue with me, not so you agree with me. There is a reading of that "N/A" report that runs the other way: it was honest. Nobody fabricated numbers. In an industry where many places still borrow data from other leagues to describe their own team, leaving "we do not have the data" untouched is a choice with a conscience.

People call it delusion; I call it a hypothesis that needs testing. It is also possible I am undervaluing the discipline of a standardized framework. A nine-dimension skeleton, even empty, still teaches newcomers which questions to ask and in what order. The framework may be a curriculum, not a product.

And the problem may not lie with the framework at all. It may lie in the VCS lacking public data infrastructure — something the organizers and the publisher must solve, not the teams.

I accept all three readings. But I do not retract the main point: a report with no data, presented as if it has data, corrupts decisions. If a coach trusts that two-page conclusion, he will decide based on a skeleton, not on an observation.

Where to go next

The empty stadium of 2026 was a data laboratory nobody asked permission for. That year I learned that when the crowd is gone, everything else shows itself. Vietnamese esports analytics is sitting in a similar empty stadium: once the noise of pretty frameworks stops, what remains is the question each team must answer on its own.

What do you think will remain once the noise stops?