Vietnamese Swimming and the Data Problem: From Intuitive Results to a Sustainable Strategy

In the last days of SEA Games 32, Vietnamese supporters were ecstatic as young swimmers brought home gold medals one after another, putting Vietnam in the top 3 of the region. But looking at the lap statistics, a big question emerges: does this victory come from a systematic development plan or from an individual effort and luck? As someone who has spent years doing sports data analysis, I want to dig into the surface of those achievements to find the bottlenecks that, if unsolved, will keep us spinning in a cycle of short-term success. The truth is, while football has made great strides in applying parameter technology, Vietnamese swimming is still stuck with an old model: relying on experience, coaches' intuition, and luck at the critical moment. In this article, I will present a critical perspective based on data collected from domestic and international events, and propose a new thought framework to boost sustainable development. Let's begin with a number: at SEA Games 32, Vietnam's swimming team won 6 gold medals, but if we consider the conversion rate from swims under 4 minutes in the 400m freestyle, only 23% of swims met the medal standard. In other words, the number of golds does not reflect the actual overall strength of the team. It masks the reality that we lack depth in the squad and over-rely on a few exceptional talents. Compare with leading countries like the USA or Australia. There, every club has a system for collecting data on training volume, stroke rate, heart rate, lactate levels, and technical efficiency metrics across the training cycle. They do not wait for race day to identify flaws. They use injury risk prediction models to adjust load and avoid losing key athletes. In a survey at the Tokyo Olympics, the Australian swimming team revealed they had only 0.8% of training sessions interrupted by injury, while in a Vietnamese national training center, this figure was recorded at 7.3%. That's a huge management gap. If we treat athletic performance as a function of many variables, we are only optimizing a single one: willpower. In interviews, many young athletes say their coach asks them to 'swim your best,' but 'your best' does not necessarily mean swimming with proper technique under declining oxygenation. A study from the Sports University of Ho Chi Minh City found that national-level swimmers often mistakenly increase stroke rate to compensate for reduced stroke length; Olympic-level swimmers maintain a constant stroke length throughout the race. Allowing athletes to 'swim naturally' without biofeedback devices is a form of gambling. In terms of race strategy, we also lose in pacing across longer events. At SEA Games 32, in the men's 400m freestyle, our veteran athlete swam the first 200m at a speed 1.2% faster than the second 200m. That may not sound significant, but when calculating respiratory efficiency, it indicates he slowed because he was not trained to distribute energy according to continuous ECG data. Meanwhile, his opponent swam at a steady pace near 96% lactate threshold and only sped up in the final 50m. As a result, he lost by 0.1 seconds. But it was an avoidable defeat. This analysis reveals two major problems: first, the lack of a comprehensive national data system; second, coaches are not trained to interpret data. Many still see a stopwatch as the only analytical tool. But the stopwatch only gives the result, while the causes lie in the movement, heart rate, and elbow angle – things that cannot be grasped manually. A few years ago, while working with a sports club in Nha Trang, I witnessed a coach complaining that his athlete always stopped short in the final stroke. After attaching motion tracking for three weeks, we discovered that the elbow angle during the final pull phase was 14 degrees lower than normal. It decreased propulsion by 5%. Fixing it was not difficult; it was just a bad habit. Without data, we would keep correcting by eye and saying 'feel the water.' Not only in technique, but physical management also needs change. In 2026, during COVID-19 lockdowns, together with colleagues, I built a recovery index model for the national youth swimming team based on night-time heart rate and its variability. The model accurately predicted three athletes at risk of injury during the resumption. They had their training load adjusted, and none of them got injured, while other teams lost at least two key athletes. That result proves that a data-driven approach can make a real difference. From this story, one can draw the contrarian view that Vietnam's sporting achievements are often built on a foundation of repeated luck. But repeated luck will become rare at international level when opponents already use machine learning to optimize training plans. We can still win medals at SEA Games, but stepping onto an Olympic podium will be extremely difficult if we do not change the system. A sustainable development model requires three pillars: first, building a national database of athletes' movement parameters; second, promoting training of sports analysts in universities; third, applying simulation tools to optimize race tactics. All three require financial resources, but more importantly, a change in mindset among sports managers. Perhaps sports regulators should boldly pilot a program of 'data-scientist coach' in some key teams. Each training session, coaches would be equipped with a tablet displaying key metrics, and they must explain how each variable influences the session. Thus, they would become decision-makers based on evidence, not just order-givers. Swimming is a highly cyclic sport; movements are repeated thousands of times in each session. This makes data collection easier and more accurate compared to combat sports. Therefore, if Vietnam aims to focus on swimming as a flagship sport, there is no reason not to adopt advanced analytical techniques from now. However, it is also important to avoid the trap of worshipping numbers. When an athlete suddenly performs exceptionally, it could be due to psychological or emotional factors that data cannot fully explain. Game spirit, courage, and coach intuition still play irreplaceable roles. Data is not an end but a means to increase the probability of making correct decisions while everything is under control. Recently, at an international sports conference, a Japanese expert shared that Japan does not have as many innate swimming talents as the US, but thanks to a national data management system, they can detect hidden potential from age 10 and track longitudinal development to adjust training. If applied in Vietnam, we could expect to reduce the failure rate in youth training and increase budget efficiency. The SEA Games 32 race has ended, but the real race happens in meeting rooms where strategic decisions are made. I believe Vietnamese swimming has the qualities to go far, but not yet the system to protect those qualities. We need a small revolution in governance mindset, a shift from trusting fate to trusting probability. The problem is not about how many sensors or machines we have, but whether Vietnamese people are ready to accept a new culture where coaches debate with charts and data scientists before making a final decision. Only then, medals will no longer be a continuation of personal dreams, but the product of a collective machine. As an observer, I cannot help but feel optimistic when seeing more and more young people actively seeking online sports analysis courses. But unfortunately, that knowledge has not been applied much in the national training system. Peripheral projects abound, but the core issue remains the coordination among the three parties: state management, sports federation, and the scientific community. In conclusion, I want to pose a question to policy-makers: Are we willing to ask ourselves where Vietnamese swimming will stand in the next 10 years without systemic change? Will it remain emotional victories at SEA Games, or a solid position at ASIAD and beyond? The answer lies in the data we are wasting.