Data Analysis in Esports: Lessons from a Deep Analysis Framework

In the context of esports developing strongly in Vietnam, the application of in-depth data analysis methods is becoming a key factor in improving competition quality and team management. However, a worrying reality is that many current analyses still lack specific data foundations, leading to subjective and unconvincing conclusions. Recently, a deep-level esports analysis report was published, but the notable point is that the entire content of this report is empty. Experts believe this reflects a major problem in the industry: data collection and processing are still not given due attention. This report, although built on a methodical analysis framework with 9 analysis dimensions from game meta, tournament system, to finance and risk, lacks any data to analyze. This shows that even with a good theoretical framework, without real data, all analysis becomes meaningless. In Vietnam, esports teams such as Team Flash, CERBERUS Esports, or GAM Esports have begun to focus on using data to analyze opponents and improve tactics. However, compared to developed regions like Korea or China, data application is still in its infancy. Many teams still rely on intuition and coach experience, rather than using quantitative metrics such as PPDA (passes allowed per defensive action) or xG (expected goals) – metrics proven effective in football and gradually being applied to esports. One of the main reasons for the data shortage is the young tournament system and lack of systematic investment. Tournament organizers in Vietnam often do not provide detailed statistics to the public, making it difficult for analysts to access. Additionally, the cost of collecting and processing large data is also a barrier for many teams with limited budgets. However, there are solutions. Teams can start by recording and collecting data from their own matches, as well as using free or low-cost analysis tools. The development of artificial intelligence and machine learning also opens opportunities to automate the analysis process, reducing costs and increasing accuracy. An important lesson from this empty report is: data does not lie, only the interpretation is wrong. When there is no data, we cannot conclude anything. This is similar to the story of Josef Martinez at Atlanta United in 2026, when xG accurately predicted his goal-scoring ability, while many were skeptical. Data has proven its value. In this context, building a standardized data system for Vietnamese esports is urgent. Managers need to realize that investing in data is not a cost but a long-term profitable investment. Universities and research institutes can also play a pioneering role in training sports data analysis personnel, creating a foundation for sustainable development. However, we must avoid a common trap: blindly chasing numbers. Data is only a tool, not the end goal. Analysts need to combine data with deep understanding of the game and real context. As an expert once said: "Data is where I take refuge, but also where I learn to be skeptical of every claim." Looking to the future, if Vietnam can build a reliable esports data system, we can completely compete with leading regions worldwide. Teams will have clear tactical advantages, sponsors will have more confidence in investment value, and fans will experience higher quality matches. That is the sustainable development path for Vietnamese esports. The question is: When will we have enough data to make meaningful analyses? Perhaps the answer lies in the serious investment of the entire industry from today.