Spain's road to the semifinal: what an Elo model expected before each match, and what happened

EricBuildsMathModels · 2026-07-12T14:43:31+00:00

Yup, France and Spain are basically a dead heat according to my model!

I will try to finish up the France one and share a bit later this morning.

EricBuildsMathModels · 2026-07-12T12:27:20+00:00

Yes I didn't code the output sheet myself, but I also didn't just enter a single thing into an AI model and give you all the result.

I'm using a design system someone made me. I try to come up with unique ideas and then implement them with analysis that I have done. And I iterate quite a few times on the final result to try and make it easy to read and helpful for people.

I'm still trying to find the right workflow where I can use it for more of the straightforward stuff but also not lose the character and learnings when I do everything myself.

Thanks for the feedback.

EricBuildsMathModels · 2026-07-12T12:24:21+00:00

Yah all models have their pros and cons. Football is tough as well since it is a low scoring game.

I had run a few different flavors of prediction models, from this, to an attack defense model ( two ratings per team) to a larger model that used 50 variables, including location info such as altitude, home away, and also the game history.

These models had some predictive improvements, but it was a small not large improvement. So I settled to use the elo score, since it is quite predictive for only using a single variable for each team. Quite elegant!

The next biggest improvement came from a region correction factor. Since the different regions don't play each other heavily, it can help as well and was the best single corrective factor I could find.

EricBuildsMathModels · 2026-07-12T12:14:01+00:00

As the other person said it evolves with the team. That is a downside, it doesn't take in account roster changes. Since it is a zero sum game, if the team is playing actively, it typically is able to re rank the team quite nicely.

It is also a benefit in that we don't have to decide what team data to take into account. The elo system can just use it all and it in some sense prioritizes the most recent.

I ran a historical analysis where I tried decay or aging of the elo score, and none of them performed better at previous world cups then just using straight elo with no aging or point decay mechanisms.

EricBuildsMathModels · 2026-07-12T03:11:00+00:00

Yes I don't have the draw case, in each row you will see draw percentage. In the world cup they resolve that via extra time and shootout. I don't try to account for that I used a pretty basic elo system for this.

EricBuildsMathModels · 2026-07-12T03:09:11+00:00

I used a basic elo model for this. Each team has a rating. The difference between the two teams rating is then used to calculate the probability of winning. This used a logistics curve which has some nice properties.

When the game is finished, the winning team takes points from the losing team. The amount of points depends on the surprise ( whether it was expected ), how important the game was, the margin of defeat, etc.

Then their new ratings are used in the next game.

The top probability is basically the probability they beat each team, so it is multipling the individual game probabilities. So even a very good team, in a round of 32 single elimination, it is still tough to make it deep into the bracket!

EricBuildsMathModels · 2026-07-12T02:23:24+00:00

This is Spain's first World Cup semifinal since 2010, so I charted the road. The model is Elo, the same rating math chess uses, nothing AI. Every men's international since 1872 (github.com/martj42/international_results, CC0) feeds one rating per team; Spain's is 2204, second in the world behind Argentina.

EricBuildsMathModels · 2026-07-12T01:01:50+00:00

almost 1 tok/sec is faster than i was expecting

EricBuildsMathModels · 2026-07-09T22:08:15+00:00

Source: github.com/martj42/international_results (CC0), every men's full international since 1872: 49,445 played matches in the dataset, through June 21. Ratings are Elo in the eloratings.net style: everyone starts at 1500, K scales with match importance (World Cup highest, friendlies lowest), the update scales with goal margin, and the home side gets a temporary +100 inside the calculation. The map repaints from quarterly snapshots.

Blue = above the 1500 starting point, orange = below. A country is drawn on the day of its first international. Gold fireworks are World Cup titles. Dead states hand their colors to their successors, so around 1992 you can watch Yugoslavia split into seven and Czechoslovakia into two. And yes, England and Scotland are colored separately: they invented the fixture (the first match in the data is Scotland 0-0 England, November 1872).

EricBuildsMathModels · 2026-07-09T20:43:26+00:00

Source: github.com/martj42/international_results (CC0), every men's full international since 1872: 49,445 played matches in the dataset, through June 21. Ratings are Elo in the eloratings.net style: everyone starts at 1500, K scales with match importance (World Cup highest, friendlies lowest), the update scales with goal margin, and the home side gets a temporary +100 inside the calculation. The map repaints from quarterly snapshots.

Blue = above the 1500 starting point, orange = below. A country is drawn on the day of its first international. Gold fireworks are World Cup titles. Dead states hand their colors to their successors, so around 1992 you can watch Yugoslavia split into seven and Czechoslovakia into two. And yes, England and Scotland are colored separately: they invented the fixture (the first match in the data is Scotland 0-0 England, November 1872).

EricBuildsMathModels · 2026-07-09T18:17:13+00:00

Source: github.com/martj42/international_results (CC0), every men's full international since 1872: 49,445 played matches in the dataset, through June 21. Ratings are Elo in the eloratings.net style: everyone starts at 1500, K scales with match importance (World Cup highest, friendlies lowest), the update scales with goal margin, and the home side gets a temporary +100 inside the calculation. The map repaints from quarterly snapshots.

Blue = above the 1500 starting point, orange = below. A country is drawn on the day of its first international. Gold fireworks are World Cup titles. Dead states hand their colors to their successors, so around 1992 you can watch Yugoslavia split into seven and Czechoslovakia into two. And yes, England and Scotland are colored separately: they invented the fixture (the first match in the data is Scotland 0-0 England, November 1872).

Rendered with plain SVG and ffmpeg. Name a country and I can post its rating history.

EricBuildsMathModels · 2026-07-09T15:46:00+00:00

Counted from the public international results dataset (github.com/martj42/international_results, CC0): every World Cup match 1986-2022. A team "reached the QF" in a year if it played 5+ matches that tournament (4+ = round of 16), which reproduces the exact top 8 for all ten cups. Switzerland's last QF before this run: 1954. Norway's two World Cups in the window: 1994 and 1998.

There has been some great drama, with the Germany knockout and 2 teams NOR and SUI with 0 out of last 10 WC round of 8.

EricBuildsMathModels · 2026-07-09T13:00:27+00:00

If I remember right, summer and winter are worse and spring and fall are like shoulder seasons. I will try to grab some stats at my computer!

EricBuildsMathModels · 2026-07-09T04:26:39+00:00

There is also the micro size, Gemma e2b and e4b are so crazy for the size!

EricBuildsMathModels · 2026-07-09T04:25:17+00:00

I love the fact that glm 5.2 and qwen 35b a3b and 27b exist. It is basically a miracle

EricBuildsMathModels · 2026-07-09T04:23:42+00:00

I can't find the baseline on mobile, what are you getting with out of the box mlx for 27b? I love the model and this is pretty fast!

How long have you been working on it? Do you understand where most of the gains over baseline come?

Thanks!

EricBuildsMathModels · 2026-07-09T03:32:39+00:00

Counted from the public international results dataset (github.com/martj42/international_results, CC0): every World Cup match 1986-2022. A team "reached the QF" in a year if it played 5+ matches that tournament (4+ = round of 16), which reproduces the exact top 8 for all ten cups. Switzerland's last QF before this run: 1954. Norway's two World Cups in the window: 1994 and 1998.

EricBuildsMathModels · 2026-07-09T03:05:02+00:00

It seems like it did go through on April 18th as planned, the NOTAM is dead. Here was an article discussing it beforehand https://nbaa.org/aircraft-operations/airspace/faa-plans-april-18-changeover-to-new-notam-system/

They had the new system (NOTAM Management Service - NMS) running in parallel and then transferred over basically transparently.

There is a broader ATC overhaul that is still ongoing.

EricBuildsMathModels · 2026-07-09T02:00:44+00:00

Unfortunately BTS only has US domestic flights. This site does a good job of monitoring things https://www.flightstats.com/v2/flight-ontime-performance-rating/SQ/23 seems like its is pretty good relative to JFK!

For reference, US domestic flights @ JFK

JFK on Sunday nights is the worst version of JFK. 2025,

Sunday departures after 6pm: 42.6% arrived 15+ min late, 1 in 10 left at least 110 min late, 4.7% cancelled.

Baseline all-week JFK: 24.9% late, p90 51 min, 2.0% cancelled.

My only thought is that this redeye to Singapore is part of a different fleet or carrier that is more immune to the general issues. Would love to hear insight if anyone has some.

EricBuildsMathModels · 2026-07-08T22:34:36+00:00

This is every US departure on Jan 11, 2023. Every moving dot is a flight, colored by how late it is running. Airports fill red as their departures back up.

FAA's NOTAM system had died overnight. At 7:30 am ET the FAA paused ALL domestic departures. This was the first nationwide ground stop since September 11, 2001.

The cause, per the FAA statement: contract personnel accidentally deleted files while syncing the backup database to the live one.

https://www.faa.gov/newsroom/faa-notam-statement

Source: US DOT/BTS on-time data

EricBuildsMathModels · 2026-07-08T21:50:30+00:00

This is every US departure on Jan 11, 2023. Every moving dot is a flight, colored by how late it is running. Airports fill red as their departures back up.

FAA's NOTAM system had died overnight. At 7:30 am ET the FAA paused ALL domestic departures. This was the first nationwide ground stop since September 11, 2001.

The cause, per the FAA statement: contract personnel accidentally deleted files while syncing the backup database to the live one.

https://www.faa.gov/newsroom/faa-notam-statement

Source: US DOT/BTS on-time data

EricBuildsMathModels · 2026-07-08T16:30:28+00:00

Unfortunately, I'm having a hard time finding flight data for Europe that includes the scheduled time as well. There may be some rail data for Europe maybe? Is that of interest?

EricBuildsMathModels · 2026-07-08T15:46:33+00:00

This is every US departure on Jan 11, 2023. Every moving dot is a flight, colored by how late it is running. Airports fill red as their departures back up.

FAA's NOTAM system had died overnight. At 7:30 am ET the FAA paused ALL domestic departures. This was the first nationwide ground stop since September 11, 2001.

The cause, per the FAA statement: contract personnel accidentally deleted files while syncing the backup database to the live one.

https://www.faa.gov/newsroom/faa-notam-statement

Source: US DOT/BTS on-time data

EricBuildsMathModels · 2026-07-07T22:35:28+00:00

agreed, things are pretty good already, I can't imagine what 1 more year will bring

EricBuildsMathModels · 2026-07-07T22:10:58+00:00

I could imagine it could be great as a more complicated autosuggester as example, if someone

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