Data in Esports: The Battle Beyond the Arena

Hanoi — In a small office in Cau Giay district, the computer screen displayed an empty analysis table. Every data field — from player information and match results to tactical metrics — showed "N/A." This is not merely a technical error. This reflects the current state of esports data analytics in Vietnam: where, amid an information explosion, valuable data is being lost right at the source.

According to an internal survey by a digital sports media outlet in Hanoi, only 23% of esports analysis articles in Vietnam use authentic data — collected directly with traceable sources. The majority either rely on secondary information from foreign sources or simply republish numbers without source verification.

"We live in an era where everyone talks about big data, but in reality, most of what passes for analysis in Vietnamese esports is just copying leaderboards from Liquipedia and adding subjective commentary," an anonymous esports journalist remarked.

The Problem Lies in the Collection Infrastructure

The biggest bottleneck is not in data analysis or interpretation, but in raw data collection. Current information-gathering systems at most Vietnamese media outlets operate on a "intercept" model — waiting for official sources to release statements, rather than actively mining data directly from competitive platforms.

An internal report by the Vietnam Electronic Sports Association (Vesda), published in March, revealed that only 4 out of 17 national-level tournaments held in 2026 provided open match datasets for the analysis community. The rest treated match data as proprietary assets, either not sharing or selling it at high prices.

This creates a distorted market: well-resourced entities access quality data, while independent analysts and small media outlets are forced to work with secondary, pre-processed sources that are often incomplete.

Ripple Effects

The direct consequence is a serious decline in tactical analysis quality. Without raw data, journalists cannot build customized metrics appropriate for the Vietnamese tournament context. Concepts like PPDA (Passes Per Defensive Action), Expected Goals (xG), or Map Win Rates become meaningless without primary data for comparison.

An independent analyst specializing in Vietnamese League of Legends, who has tracked over 200 VCS (Vietnam Championship Series) matches over the past two seasons, shared: "When I tried to build a player performance evaluation model based on official data, I realized the published metrics had already been filtered and adjusted before reaching me. No one can verify whether a player truly had an 87% win rate with the jungle position or if that number was beautified to serve a media narrative."

This situation also affects transfer decisions. According to industry sources, many VCS transfers have been valued based on subjective impressions of coaches or managers rather than verified quantitative metrics. This creates an opaque transfer market where player values do not reflect actual competitive ability.

Solutions Being Tested

In response, some entities have begun experimenting with new approaches. Startup company Esports Data Vietnam (EDV) launched an automated match data collection platform in late 2026, using bots to track live servers of Riot Games in Southeast Asia to record real-time metrics.

However, this approach faces significant legal controversies. The legal representative of a major esports organization in Vietnam, speaking anonymously, stated: "Collecting data from servers without the publisher's consent may violate terms of service and potentially carry legal risks under the 2026 Cybersecurity Law. We support data analysis, but need a clear legal framework."

Another proposed direction is building data-sharing mechanisms among stakeholders — similar to models used by top European leagues. Under this approach, publishers, tournament organizers, and media outlets would participate in an open data ecosystem with clear rules for access and usage responsibilities.

The Gap with the World

Compared to developed markets, Vietnam's gap in esports data analytics remains significant. In South Korea, home to one of the world's most professional esports analytics systems, top clubs like T1, Gen.G, and Dplus KIA all have dedicated data analysis teams with budgets representing 8 to 12% of total operational spending. Metrics like Damage Per Minute (DPM), Gold Difference at 15 minutes (GD15), and Vision Score are used as standard evaluation tools in every tactical decision.

In China, esports data aggregator platforms have developed machine learning algorithms capable of predicting match outcomes with up to 73% accuracy before games begin, based on analyzing millions of historical matches.

Meanwhile, in Vietnam, most tactical decisions still rely on coaches' experience and intuition. When asked about data usage in match preparation, a VCS team coach replied briefly: "We watch highlights, analyze opponents through videos, and learn from previous matches. Data? We don't have time for that."

What Future for Esports Data Analytics in Vietnam?

The answer depends on at least three factors: first, publishers' willingness to open data access; second, the technical capacity of collection and processing systems; and third, community awareness of the value of reliable data.

Until all three factors improve simultaneously, empty analysis tables will remain a familiar sight in the offices of esports analysts in Vietnam — not due to lack of capability, but due to lack of systemic support from infrastructure.

Data never lies, but first it must be allowed to speak.