Data Analysis in Vietnamese Football: Lessons from an Information-Deficient Process

In the context of modern football, data is no longer just dry numbers but has become a decisive strategic tool for top clubs worldwide. From player selection, tactical construction, to fitness management and injury risk prediction, data analysis is reshaping how we understand the beautiful game. However, in Vietnam, the application of data analysis to football remains in its infancy. This raises an important question: Are Vietnamese teams missing a crucial competitive opportunity? Looking at Europe's top leagues, clubs like Liverpool, Manchester City, or Bayern Munich have been using advanced metrics such as Expected Goals (xG), Expected Assists (xA), PPDA (Passes Per Defensive Action), or xCG (xG Chain) to evaluate attacking and defensive efficiency. These metrics not only reflect outcomes but also reveal the quality of chances a team creates or allows. For example, a team might win 1-0 but have a lower xG than its opponent, suggesting the victory relied heavily on luck. Conversely, a team losing 0-1 but with a higher xG could be playing well and will soon get deserving results. In V.League 1, Vietnam's top professional football division, the application of these metrics remains limited. The main reason is the lack of a synchronized data collection system. While major leagues have companies like Opta, StatsBomb, or WyScout providing detailed event data, in Vietnam, tracking and recording data often depends on media outlets or small independent analysis channels. This leads to inconsistency in evaluating players and teams. Another issue is the "immediate results" culture in Vietnamese football. Managers often face pressure to deliver results instantly, leading to decisions based on intuition or experience rather than objective data. We can see this in substitution decisions, foreign player transfers, or tactical choices in crucial matches. However, there are positive signs. Recently, clubs like Hanoi FC, Cong An Hanoi, and Hai Phong have begun to invest in their own analysis departments. They hire experienced data experts, use video analysis software, and try to build databases about their players. Although the scale remains small compared to world-leading clubs, these are steps in the right direction. Another factor is the development of domestic technology. Vietnamese tech companies such as Viettel, FPT, or VNPT have the potential to develop their own sports data analytics platforms. If clubs and tech companies collaborate, building a standardized data system for Vietnamese football is entirely feasible. Not only at the club level, but the national team also needs a data revolution. When the head coach of the Vietnam national team can access detailed data about each player from youth teams to the senior squad, player selection and line-up arrangement will become much more accurate. This is especially important in the increasingly competitive Southeast Asian context, where Thailand, Malaysia, and Indonesia have all made certain progress in data. However, we must acknowledge a reality: data cannot completely replace a coach's intuition and experience. Data is only a supporting tool, helping to reduce risk and increase decision accuracy. Combining quantitative analysis with qualitative evaluation from seasoned experts will create optimal results. One of the biggest challenges is cost. Equipping GPS tracking systems for each player, video analysis software, or hiring data experts is not cheap. For lower-division clubs with limited budgets, this is nearly a luxury. Therefore, the Vietnam Football Federation (VFF) can play a pioneering role in building a shared data system for the entire league, reducing the cost burden for individual clubs. Moreover, a change in mindset is needed. CEOs, coaches, and players need to understand that data is not a tool for intimidation or criticism, but part of the development process. If a player has poor physical metrics, it is not for punishment but to adjust training programs accordingly. Similarly, if a team has a low chance conversion rate, the coach can focus on shooting drills. Looking to the future, we can imagine a V.League where each match has live data on xG, number of passes, running distance, successful pressing actions... Viewers will see these statistics on television or digital platforms, helping them understand the game more deeply. Sports journalists will have more material to analyze, instead of just discussing results superficially. However, to achieve this, a collective effort is needed. Clubs must invest, media outlets must support, and most importantly, VFF needs an overall strategy. Additionally, universities and research institutes can train sports data analysts, creating a new generation of experts for Vietnam. We also need to look at experiences from other countries. Japan and South Korea, two leading Asian football nations, have built systematic data infrastructures for years. Their leagues have public databases, allowing analysts to research and coaches to reference. Vietnam can learn from this model. Of course, there will be opinions that football is a sport dependent on emotion and cannot be fully mechanized. That is true, but it does not mean we should ignore data. On the contrary, data helps us understand a match better, increasing the excitement when a team plays well, or alleviating disappointment when a team plays poorly. A specific example: in a V.League match, a team might win 2-0 thanks to two quick counterattacks, but data shows the opponent controlled 70% possession and took 20 shots. This suggests that the victory may not be sustainable, and the winning team needs to improve its ability to withstand pressure. Conversely, the losing team, despite controlling the ball well, lacked efficiency. With such data, coaches can make adjustments. In the transfer market, data also plays a vital role. Instead of only looking at the number of goals a player scores, managers can examine xG, chances created, win rate in duels, ball recoveries... This helps determine whether the player actually fits the team's tactics, avoiding costly failed signings. In Vietnam, the transfer market is volatile, and many clubs have suffered from signing players who look good on paper but fail to meet professional requirements. With standardized data, this risk will decrease significantly. Another important aspect is youth training. Football academies like PVF (Vietnam Youth Football Training Fund) have begun adopting modern methods, but data is still underutilized. If PVF and other training centers record data on physical, technical, and psychological aspects of each young player over the years, we can predict development potential and plan appropriate investments. In summary, data analysis is a path that Vietnamese football cannot avoid. The road will not be easy, but it is worth the investment. If done right, we can raise player quality, increase the league's competitiveness, and more importantly, help Vietnamese football integrate more deeply with the world. From what has been analyzed, it is clear that a deep analysis process but without input data (Stage-1) cannot produce useful results. The first lesson is the necessity of collecting and verifying information. Without accurate information, all analysis is just guesswork. This applies not only to this article but also to the entire Vietnamese football ecosystem. So, let's start today. Clubs, managers, and coaches should embrace data. Do not fear complex numbers, as they will teach us a lot. Vietnamese football deserves a solid foundation for development, and data is the first brick of that foundation.