When Sports Analysis Becomes Helpless: Lessons on Data Sources

On a rare morning when I had no schedule to go to the field, a young colleague pushed over a tactical analysis document. I opened it, expecting to read about the midfield's running rhythm or space occupancy rates. But the screen showed the line: 'Insufficient Information for Analysis.' The entire ten-page document contained only that single sentence, with all categories marked N/A or blank. I suddenly remembered the summer of 2026 in St. Petersburg, when I mispronounced Eden Hazard's name three times in a World Cup semifinal. At the time, I shrugged it off with a smile. But that night, I stayed awake reviewing the entire video footage and rewriting the phonetic transcriptions of all twenty-three French and Belgian players. That carefulness saved me from broadcasting misinformation. Today, facing an analysis system with no information, I felt something similar: a writer must confront the truth that no conclusions can be drawn without sufficient data. Let us address the broader context. Vietnamese sports is currently entering a regular season, where every storyline around the standings demands sharp observation. In recent years, many professional clubs have begun using advanced metrics such as PPDA—the number of passes allowed by opponents per defensive action—or expected goals (xG). But these numbers only make sense when placed within the specific context of a match. A useful analysis must start by collecting information that is accurate, complete, and verifiable. When we have no data at all, should we boldly comment? I do not think so. In the case of that empty report, my colleague explained that he had used an automated information extraction tool on an article about martial arts. Because the website malfunctioned, it could not parse anything. I nodded and told him, 'You should have read the article yourself before trusting the tool.' I was not scolding him—I too have been a victim of imprecision. Recalling 2026, when the pandemic left Nha Trang's stadium empty and Khatoco Khanh Hoa fell into financial crisis, we once received a message about a 'big contract' that would help the team survive. Yet when we verified with club leaders, it was merely baseless rumor. Had I written an article at that moment, it would have been a serious mistake. In sports, misinformation is more dangerous than having no information, because it creates false confidence. What made me reflect was that this story appeared within an article about analyzing sports content. The original author attempted to guide readers on processing documents, but overlooked the first principle: the input data must exist. This is a common problem in both sports academia and journalism today. We become obsessed with finding an optimal lineup or a perfect tactic, forgetting that every analysis begins with direct observation. Since time immemorial, sports reporters like us have recorded every minute of a match, counted passes by hand, and noted critical moments. In a football match, there are thousands of situations—if we rely solely on automated data, how can we distinguish a deliberate aerial ball from a random one? How can we know if a player clenches his fist out of tension or in preparation for a combination play? These are things we must supplement with real observations from the pitch. What is ironic is that when the system returns empty, it is actually doing something right: reflecting the insufficiency of the data source. Many people would think that makes the tool useless, but I believe the opposite. When you have sufficient information, yet the information is wrong, you will reach a convincingly wrong conclusion. But when you have no information, you know you cannot assert anything yet. I recall a saying from a veteran colleague: 'People remember the goals; I remember the sighs behind the goal.' That sigh is a form of data not found in statistics, yet it reveals the goalkeeper's psychological and physical shift. That experience cannot be gained by merely sitting in front of a screen. So what makes a good analysis? I think it must begin by asking: How many matches of this team have I observed? Was I present at the stadium? Have I verified information with coaches or players? In over four decades of journalism, I have never sent a tactical analysis piece based solely on watching television rights. Every article I write includes notes on time, place, and the information provider. To younger colleagues, I advise starting with something concrete: record a controversial situation, a bizarre substitution, or a period of opposition pressure. From there, we can infer the coach's intentions. If we have too little information, the best choice is to remain silent and continue gathering. Every season has its own heartbeat, I often tell my colleagues. Some seasons the league's heart beats in the championship race, others in the relegation battle. In 2026, the V.League's heart beat fast in Nha Trang when Khatoco Khanh Hoa overcame a difficult streak thanks to the talent of Nguyen Dinh Bao—a young midfielder who ran 1.2 kilometers more per match than the previous season, yet did not stand out in the stat sheet. Because I closely followed the team's training sessions and watched him practice long-range shots after hours, I was able to write the 'Dressing Room Diary' series that readers remember. If I had focused solely on a deficient data set, I would never have understood that. That empty report, in the end, was set aside after I asked my colleague to find the original source article and read it carefully. He discovered that the source was actually a tactical analysis of a league that had ended two years prior, with entirely outdated information. Had the system run and produced results, it would have generated a judgment completely irrelevant to the present. This further reinforced the 'write after verification' philosophy I have followed throughout my life. It may be slower to produce analysis, but every piece of information is accurate. For a sports journalist, credibility is the greatest asset. Once you write something wrong, readers will doubt all subsequent articles. Truth is what we owe our readers, and if we lack sufficient facts to assert something, we should wait another beat. The final lesson I have drawn is that no analysis, however sophisticated the algorithm, can replace being present on the sidelines. The current trend is toward big data and artificial intelligence, but that intelligence must be nourished by the ability to observe and sense the atmosphere of a match. I once read a report on esports that said: 'Esports also has seasons, stoppage time, and silent figures who make history.' Similarly, in a football match, a single emotional tweet can cause a storm, but to understand tactics, you must examine every small detail. When data is absent, stop and look around. The stadium may have no spectators, but I can hear the applause of those who do not give up. Today, I did not go to the pitch because of rain. But I still took out my notebook and wrote a few lines of work diary. And I told myself: both that analysis and I need a true listener—someone who can separate the noise from the sound of the ball, waiting for the moment when the entire stadium holds its breath to record the heartbeat of the match. That is my job, and I will not stop no matter how much it rains.