Stop Calling the Mexico City GP a 'Football Event': A Lesson in Reading Sports Economics

There is a mistake in sports analysis that I have witnessed for four decades: mislabel an event, then build an entire framework of reasoning on a faulty foundation. The latest case is the report on the economic impact of the Mexico City Grand Prix. Many outlets file it under 'football.' It is not football. It is Formula 1. And precisely because of that, any tactical analysis, any squad model, any league comparison applied to it produces nothing but noise.

I am not writing this to catch anyone out. I am writing because I have done exactly this myself. In 2026, when Spain dominated 74% possession against Russia and generated just 0.9 xG, I posted a line: 'Possession is an illusion; pressing and transitions are real.' 47 traditional journalists criticised me. Six hours later, 2,300 retweets. The lesson I took was not 'I was right,' but this: if you mislabel the data, you will argue in the wrong place. The Mexico City GP report is a perfect example of that.

Look at the numbers. The projected economic impact is 22,228 million pesos, up 6.5% from the 19,840 million pesos baseline in 2026. That is a clean, comparable growth metric, valid until the 2026 event concludes. But right next to it is a figure that made me stop: lodging revenue is stated as 366,954 million pesos. That is roughly 16.5 times the total economic impact of the entire event. Arithmetically, that is impossible. If the total impact is 22,228 million, a component cannot exceed the total. Most likely this is a unit or decimal error, and the correct figure should be 366.954 million pesos — about 367 million. I have seen this kind of error in football event reports for years. It is not fraud. It is carelessness, and carelessness in sports economic data is more dangerous than a missed shot, because it propagates.

The second point worth noting: the source. Nearly all quantitative claims in the report trace back to Canaco, Mexico City's chamber of commerce and services. Canaco is a business-lobby body. Economic-impact estimates from such organisations tend to skew high systematically. That does not mean they are wrong. It means that if you use their figures for planning, you should apply a discount factor. I learned this while working in Japan: reports on the impact of J.League matches often come from local government or the organiser, and both have an incentive to present favourable numbers. A good analyst does not dismiss a figure because it comes from an interested party. They use it, but label it clearly: 'single source, advocacy bias, requires independent cross-check.'

The most valuable thing in this report, to my mind, is the 401,326 attendance figure over three days. This is the most operationally verifiable data point. It is equivalent to the capacity of a mid-sized football stadium over three consecutive matches. And it gives us a comparison sample: if a football tournament wants to measure economic impact, it can use the analytical structure of this report — lodging, ticketing, guides and transfers — as a template. Ticketing is around 8,420 million pesos, guides and transfers around 4,518 million pesos. Those are figures reusable for any major sports event.

But here is where I want to challenge myself. Where could I be wrong? I am applying a football analytical framework to a non-football event. That is precisely the error I just criticised. The difference is: I am not claiming this is tactical analysis. I am claiming it is methodological analysis. And in methodology, there is a weak point: the report says nothing about actual versus projected hotel occupancy. It only says 85–95%. If the actual figure falls below 85%, the entire 6.5% growth forecast needs revisiting. I have seen this in football: attendance projections tend to be more optimistic than reality, especially when the organiser is the publisher.

One more point. This report contains no sporting content whatsoever. No results, no line-ups, no tactics. It is purely event economics. That means if someone feeds it into a football analytics pipeline, the system will generate noise. I have seen transfer data models overvalue youth potential and undervalue dressing-room chemistry. The same error occurs when you mislabel the domain: you get conclusions that sound plausible but are meaningless.

So what is the lesson? Stop asking 'how does this event affect football.' Ask 'how does this event affect the local economy, and what can we learn from how they measured it.' The answer lies in the structure: a major event generates cash flow through lodging, ticketing, services and transport. Football is the same. But football has additional channels that Formula 1 does not: academies, player agents, broadcasting rights, and the national-team ecosystem. If you ignore those channels, you are measuring half the truth.

At 61, I no longer have time for polite football on paper. But I also no longer have time for mislabelled analysis that marches confidently forward. The Mexico City GP report is a reminder: before you analyse, check the label. And before you trust a number, check whether it is larger than its own total. If it is, you are reading a typo, not a trend.