When Football Analysis Is All 'N/A': A Journey to Find Truth in Data

At a small stadium in the Southwest region of Vietnam, I stood near the touchline and observed the left-back of the home team. He was not fast, not skilled at dribbling, but during the 90 minutes, he executed 12 interceptions and 4 tackles at precisely the right moment. No article mentioned him. Just as no tactical analysis in Vietnam dares to dig into those numbers. Instead, people favor emotion-filled pieces, or worse, analyses where the main criteria are left blank with the phrase 'insufficient information.' That reminds me of an American adage: 'If you cannot measure it, you cannot improve it.' But in Vietnamese football, are we using mystique to disguise the lack of data? I am a sports data consultant living in Singapore and following Vietnamese football from afar. Every week, I read match reports on domestic football sites. Lately, some sites have begun using modern analytical models such as xG, PPDA, or transfer valuation. But when I open the details of an analysis, I find plenty of metrics stuck in 'insufficient information.' The article seems to be generated from a beautiful template, but in reality, it is an empty shell. Look at the aspects a thorough analysis needs: tactical, financial, results, league position, compliance, dressing room, risk, media, and industry transmission. A valuable analysis must address every dimension. Yet, in many articles I read, sections like 'tactical assessment' are merely generic comments: 'the team plays pressing,' 'the defensive line pushes high,' without concrete data. As for finances, there is almost no trace of revenue, wage bills, or transfer fees. In V-League, that might be acceptable because clubs rarely disclose financial numbers. But when even basic data on passes, touches, or distance covered is unavailable, it is truly concerning. The mantra of modern analysts goes: 'There are figures that do not appear on the scoreboard; they lie between two touches.' That reminds us that data is not cold symbols, but a way to see what happens in the quiet spaces. I once applied that philosophy to a match of Vietnam's U19 women's team, where they only had 12 games in the year. Their goalkeeper had a penalty save rate of 43%, thanks to reading the shooter's stride, despite lacking ideal height. Without data, she would never be valued correctly. That is why I emphasize: 'Do not look at the one with the most ball possession; look at the one standing where the ball is about to arrive.' That information is not easily found in ordinary summaries, but it decides the outcome. However, data is not always absolute truth. I recall the 2026 World Cup match between Spain and Portugal. Cristiano Ronaldo reached a top speed of only 9.8 km/h, below the team average. Someone might conclude he was lazy or slow. But if we examine each play, all five shots on target came from quick bursts inside the box, where only one stride is enough. As Arnold Schwarzenegger said, 'Strength does not come from muscles, but from will' – yet he was not talking about sprinting for the entire match. Neither was Ronaldo. Data analysis should not be twisted into hunting for shocking stats, but instead connect them with tactical context. An empty analysis is not just useless; it is counterproductive. It creates the illusion that we understand football, while in fact we are only applying tools mechanically. In 2026, when several Vietnamese clubs faced financial crisis during the pandemic, I saw an analysis of a V-League club which marked 'dressing room assessment' as 'no information.' That was laughable, because no one could understand internal pressure by just looking at the standings. Especially in Vietnamese football, which relies heavily on spirit and the coach's tactics, yet those aspects lack even a single reference number. In my opinion, Vietnamese sports journalists and analysts should boldly request data from clubs, or build their own data-collection systems. We don't need to be a big club to do so. With a laptop and a smartphone, I can code every event in a match, create xG charts, or measure player distances. It takes time, but it yields valuable insights. I remember in 2026, when I was starting out, I analyzed 17 key passes by Mesut Özil in the Premier League. My article was criticized as 'lacking evidence,' so I added three charts with per-match data. That ended up sparking a lot of discussion. That experience taught me: when data does not say anything, do not force it. A season is not the sum of 38 matches; it is the repetition of 17 forgotten passes. That is my mantra. But to see those 17 passes, we need honest data. Do not be afraid to present raw numbers, do not fear concluding that 'we do not know yet,' and do not turn analysis into a place for embellishment. In a corridor, if you only look toward the light, you will miss what stands in the darkness. Likewise, if we only look at goals and scores, we will never understand why a team wins consecutively or loses drastically. The question is: Are Vietnamese football analysts willing to abandon the habit of writing by instinct and accept data-driven observation, even when the data is incomplete? I do not have a definite answer. But I believe a new generation of football people is emerging, and they will not settle for empty articles. They want to see truth excavated from numbers, and they want to understand what 'uncertainty' in data means. Then, football journalism will no longer be a place for clichés, but a battlefield of evidence. And I hope, one day soon, the 'N/A' section will transform into expressive metrics that tell the story of forgotten people on the back benches.