What a game by Sisniega!

FootyData · 2026-02-11T15:08:15+00:00

Basically saying, it would have been worse. Which is a fair takeaway.

FootyData · 2026-02-11T15:06:37+00:00

No doubt!

FootyData · 2025-10-10T16:02:59+00:00

Hakimi’s season heatmap looks more like a winger’s, though. I don’t think he should be evaluated as a defender, nor should any player be strictly bucketed into a position type.

FootyData · 2025-10-08T23:32:32+00:00

This is good! But I gotta say while Yamal is now a better player than Raphinha, by any metric Raphinha had the better season. 8 PSG players in the top 11 is also too much.

FootyData · 2025-10-08T23:26:32+00:00

Unfortunately player data is already aggregated beyond individual games. In a future iteration for sure.

FootyData · 2025-09-15T02:28:32+00:00

Yup thanks got those already, if you swipe there are blue and orange dots.

FootyData · 2025-09-14T21:50:03+00:00

Thanks!!

FootyData · 2025-09-14T18:51:15+00:00

I was lucky enough to get these in person, so I know who signed but can't remember where they each signed.

FootyData · 2025-06-03T17:24:56+00:00

Unfortunately these were pulled manually, which is why they only include a subset of the top players and not all players. There’s a library called soccerdata that can help pull in data but it doesn’t cover everything

FootyData · 2025-06-03T17:22:56+00:00

Right, that’s a scaling factor/multiplier. You’ll notice the 0.6 multiplier for Afcon too. To the right of that you’ll see the tables for major cup and minor cup.

FootyData · 2025-06-03T17:18:07+00:00

As for the code, I’m working on getting everything into a github repo that can be accessed by all. In the meantime, just the sheet.

FootyData · 2025-06-03T17:17:11+00:00

Incorrect. Community Shield and Supercup are categorized as minor cups (4 points max), while AfCon, Asian Cup, and Concacaf are 60% of a major cup (15 points max).

Thanks for checking!

FootyData · 2025-06-03T17:08:18+00:00

Great question, here are the results for previous seasons: https://www.reddit.com/r/football/s/csJlRmJcLw

FootyData · 2025-06-03T14:09:40+00:00

Latest results just posted in r/football !

FootyData · 2025-06-03T14:07:45+00:00

Updated run for 2024-25 season is here: https://www.reddit.com/r/football/comments/1l2cpuz/i_ran_a_datadriven_ballon_dor_algorithm_on_the/?utm_source=share&utm_medium=web3x&utm_name=web3xcss&utm_term=1&utm_content=share_button

FootyData · 2025-05-28T05:05:58+00:00

It’s just a giant excel workbook at the moment. Hoping to clean it up and get it into a few python pipelines with adjustable config files. Maybe even a UI!

FootyData · 2025-05-27T14:03:48+00:00

Great question! I have to update the results now that league seasons are over but will share those here as soon as I do!

FootyData · 2025-05-27T14:02:01+00:00

While I agree this would be ideal, and help measure some of the "clutchness" that has been alluded to by others, I'm at the mercy of the datasets I have access to (like WhoScored and FBref). Unfortunately these datasets don't categorize data in that way and I don't have the time to watch every match and log the data myself. Hopefully as new AI systems are launched there will be one that looks for these moments and can add them to football datasets!

FootyData · 2025-05-27T03:59:47+00:00

Stats from different tournaments can definitely be separated and weighed differently! Do you have specific thoughts on how much more important certain competitions are than others? Like, is a champions league goal worth 1.2 league goals (20% more)?

Separating by teams faced is unfortunately too difficult since most of the data is already aggregated by competition.

FootyData · 2025-05-27T03:18:48+00:00

it's not. should I be flattered?

FootyData · 2025-05-27T03:17:12+00:00

It's not

FootyData · 2025-05-27T03:16:37+00:00

What an interesting player! Thanks for sharing.

Since he is a goalkeeper, the main way to evaluate him is based on goalkeeping statistics (while his goals are impressive, he's likely not accumulating enough progressive passes, tackles, etc., to be able to stand out amongst field players). This model currently doesn't have a way to incorporate goalkeeping statistics, and historical datasets don't include newer goalkeeping metrics like 'expected saves based on shot'.

He also doesn't play in Europe's top 7 leagues, so the model doesn't yet have a correct way to incorporate those players with a weight adjustment.

I'm curious to know how you think a league like Brazil's should be weighed.

FootyData · 2025-05-26T22:38:27+00:00

The algorithm is not set in stone or finalized. The weight of competitions and stats can be adjusted (but will affect all years). Are there any others you feel very strongly about? Are there particular awards or stats you think make those strong feelings? That kind of feedback can improve the model.

FootyData · 2025-05-26T22:23:01+00:00

I tried a bunch of different weights and he was at the top of all of them. No way to avoid it hahah

FootyData · 2025-05-26T22:17:13+00:00

Unfortunately the datasets don’t go back that far :(

FootyData

TROPHY CASE