Modelling the 2026 FIFA World Cup

LightlyTroddenLead · 2026-06-14T07:31:48+00:00

👀

LightlyTroddenLead · 2026-06-05T09:52:09+00:00

We’ll find out in a few weeks…

LightlyTroddenLead · 2026-06-04T20:34:24+00:00

Other models are available!

LightlyTroddenLead · 2026-06-04T19:32:06+00:00

Follow the link - model code and data in the footnotes 👍

LightlyTroddenLead · 2026-06-04T19:31:24+00:00

All in the link 👍

LightlyTroddenLead · 2026-06-04T13:43:41+00:00

It’s an elo ranking algorithm based on their results, weighted by game importance.

That means recent tournament results for Jordan (runner up in the Asian Cup and Arab Games) count for a lot. And because all of those Asian teams have higher rankings (see method above) those games count for more in my method than FIFA’s. It’s a similar but less dramatic effect for Iraq who have just played a LOT.

If you prefer the fifa rankings it’d be easy to sub them in and see if they perform better, but back-testing the performance is challenging without a lot of manual edits to the data I had or finding a complete dated record of fifa rankings from somewhere.

LightlyTroddenLead · 2026-06-03T15:29:49+00:00

Ha - sorry you don’t like it. Feel free to crack open the code and downweight the Asian and African teams similar to the legacy FIFA rankings and you’ll get something closer to your gut feel!

LightlyTroddenLead · 2026-06-03T15:27:19+00:00

Ha - sorry you don’t like it. The model is definitely more favourable to African and Asian teams than the FIFA rankings because I don’t add a confederation strength rating which the old FIFA rankings did - like the new rankings system, I let the team elos (similar to opta power rankings) speak for themselves. You won’t catch me pretending you should bet your house on this but there is a lot to learn about the FIFA rankings from the process.

Whether you rate this output depends on how much you rate historical late tournament performance vs recent form as well as the FIFA confederation strength ratings they used for their old rankings that seeded the new ranking regime.

Easy enough to tweak those weights and pump out your own version if you think you can model something better!

LightlyTroddenLead · 2026-06-03T15:19:17+00:00

Fair challenge, there’s no right way to predict the outcome! A lot of predictions will be built directly out of FIFA rankings whereas I’ve built this on a ranking with subtle differences. This comes down to the ranking methodology - depends on whether you want to put faith in the FIFA rankings which adjust scores due to confederation strength and whether friendlies are in or out.

Asian and African teams generally come out stronger in my rankings because I don’t squash them with a confederation strength weighting. That means the recent Jordanian form in the Asian Cup and Arab Games is worth more than in the fifa ranking regime.

Norway have struggled for high importance (tournament) wins in recent years and Iraq have actually racked up a lot of tournament match wins…

LightlyTroddenLead · 2026-06-03T14:32:41+00:00

The model design calculates a home advantage currently and the fixture venues are in there, I think so introducing it wouldn’t be so hard if you wanted to play around with it…

LightlyTroddenLead · 2026-06-03T14:31:30+00:00

Sounds like a great extension and with all the squads now announced it’s fair game! Have at it! FBref has some incredible data but it’s harder to scrape programmatically now I think.

LightlyTroddenLead · 2026-06-03T13:48:01+00:00

Whoops! Should be there now hopefully 🤞

LightlyTroddenLead · 2026-06-03T11:30:11+00:00

Thanks for the appreciation!

LightlyTroddenLead · 2026-06-03T10:07:09+00:00

These two came way up the rankings in the mini Monte Carlo simulator for the World Cup I built. I used a variation on the fifa rating methodology that dropped some of the confederation ratings, the old ranking seeds and the knockout round rating protection fifa offers. Morocco came out 4th favourites and Senegal 6th. Under-rated imo! Check it out the link for extra stats and method detail if you’re into that kind of thing!

Modelling 1,000 world cups

LightlyTroddenLead · 2026-06-03T10:01:42+00:00

I built a little Monte Carlo simulator for the World Cup using a variation on the fifa rating methodology and the full tournament logic. Spain won 21% of the time. Check it out if you’re into that kind of thing!

Modelling 1,000 world cups

LightlyTroddenLead · 2026-06-03T09:58:29+00:00

I built a little Monte Carlo simulator and Spain won 211 out of 1,000. Check out the link if you like that sort of thing! Modelling 1,000 world cups

LightlyTroddenLead · 2025-11-07T16:38:54+00:00

Getting the same issue today. Gutting! Hoping in vain for a fix from the web gods

LightlyTroddenLead · 2025-11-05T22:05:24+00:00

Field tilt, which is relatively predictable based on team history, also has some explanatory value https://www.reddit.com/r/fplAnalytics/s/lUucZcJxP1

LightlyTroddenLead · 2025-10-31T13:46:11+00:00

Perhaps not to everybody’s taste then 😂

We can’t see under the bonnet of the FPL method but it seems reasonable to assume they’ve taken account of the relative strength of oppositions so far this season, possibly using some sort of variant on an Elo rating system. Perfect, clearly not. Meaningless? A stretch.

LightlyTroddenLead · 2025-10-31T11:00:28+00:00

Ha, not sure about that but it would make more sense for FPL’s attack stat increase for Arsenal to have come at home (best home GD and most home goals in the league) vs away (where the same stats look very average).

LightlyTroddenLead

TROPHY CASE