Opta Supercomputer Shock: Como Above Napoli, Arsenal Top in Champions League

A newly promoted team is placed above a Serie A champion – and that comes from a supercomputer, not from emotions. As the UEFA Champions League kicks off with a new 36-team format, the Opta Supercomputer has just released its title probability rankings. What stopped me was not Arsenal at the top, but Como – a small team that has just returned to Europe after decades – ranked above Napoli, the 2026/23 Serie A champion. Looking at the numbers, I recall a principle I have learned after years of analysis: every model is wrong, but a few are usefully wrong. Opta, the data system owned by Stats Perform, uses millions of variables to estimate each team's chances. This ranking is not a result of a match, but probabilities calculated before the league phase begins. Arsenal are first, Bayern Munich second, Manchester City third. Paris Saint-Germain are fourth, Barcelona fifth, Real Madrid sixth. Inter Milan is the only Italian representative in the top 10, at ninth. Roma are 12th, Como 16th, and Napoli – a team once considered a heavy contender after their Serie A title – are only 23rd. Following European football for many years, I realized that the surprise of the original article's author is not rare. Humans cling to historical standings and reputation. But models have no such memory. They rely on data about squads, form, xG, PPDA, and dozens of other variables. A team like Como, though less famous, may have a squad quality rated higher than Napoli – if we look at data on player value and transfer investment. This leads to a big question: xG doesn't score goals, but it makes people argue more than the actual ball. Why is Napoli – a team that won Serie A and reached the UCL quarter-finals – placed behind a team that just qualified via playoff? Perhaps Opta's model reflects Napoli's decline after losing key players, or simply reflects Como's strength built through expensive deals and squad depth. But just looking at the ranking, we cannot know. Interestingly, Inter Milan is the only Italian team in the top 10. This reinforces the narrative that Italian football is no longer among Europe's elite, despite having multiple participants. If we look at Vietnamese football – where I was born – similar distribution of strength often appears. Fans always defend historic clubs, but models don't care about history. They look ahead. But be careful: we should not confuse data with reality. As I once wrote, football stopped rolling in 2026, but randomness never takes a break. Models are probabilities, not prophecies. With the new 36-team format, calculating only the title probability can be misleading. A team ranked 23rd like Napoli can still easily make it through the league phase. But from the perspective of a betting analyst, these numbers are important signals. I remember the 2026 World Cup when my model predicted South Korea would beat Germany – it made me famous. But just a few days later, the model made a wrong prediction about Brazil vs Belgium. Since then, I always note that my model can be wrong. Opta putting Como above Napoli might be one of those outliers we should be cautious about. From this perspective, I want to emphasize that a probability ranking is not a tactical verdict. It is an aggregate of many factors. We cannot say Arsenal play better than Bayern because they are ranked higher. What we can say is that the model believes Arsenal have a higher chance of winning this season, based on what has happened before. Another detail: Como being 16th – they could surprise in this tournament. If you look at how they built their squad, under the backing of wealthy owners, they could be an interesting dark horse. But it is also possible the model overrates them because they are untested in Europe. This is something we cannot know until matches are played. If you ask me what is most important in reading this ranking, I would say: treat it as a mirror, not a map. It reflects the present based on available data, but lost data is not the absence of data – it is a kind of data. The absence of Napoli in the top 10, the presence of Como, all tell us something. But we need to look beyond. Ultimately, I will watch the matches to see if the model is right. But whatever the results, this is why I love football: randomness always has the final say. Remember: a model is just a tool. And the best tool is still your own observation and independent thinking. Arsenal are number one, but football does not worship rankings. It worships the moments when all numbers are forgotten.