Ben Griffis Profile picture
Nov 25, 2022 β€’ 10 tweets β€’ 4 min read β€’ Read on X
Post-Match Report πŸ§΅πŸ“Š

Qatar πŸ‡ΆπŸ‡¦ 1-3 πŸ‡ΈπŸ‡³ Senegal

#QATSEN #Qatar2022 #FIFAWorldCup Image
Qatar starting XI passing sonars Image
Senegal starting XI passing sonars Image
Qatar's expected threat (xT) via pass, with the player in each zone being the top xT player in that zone, and all the players' total xT via pass in the table to the right Image
Senegal's expected threat (xT) via pass, with the player in each zone being the top xT player in that zone, and all the players' total xT via pass in the table to the right Image
Qatar all passes by zone Image
Senegal all passes by zone Image
Qatar's main passing flows. Each arrow represents at least 3 completed passes from the arrow's origin zone to the arrowhead's zone.

A darker color indicates more passes Image
Senegal's main passing flows. Each arrow represents at least 3 completed passes from the arrow's origin zone to the arrowhead's zone.

A darker color indicates more passes Image
Expected Threat (xT) from passes, zone control.

Areas shaded in a team's color means they had more xT from passes in that zone Image

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More from @BeGriffis

May 6
My sample of shots for my xG model is at 313,319 (and growing, I'll likely double that soon), so I can dig into some non-xG data...

And I found that the more a team leads by, the more likely they are to score with their shots. It's statistically significant as well Image
The graph shows all non-penalty shots in my sample taken when the team was losing by 4/3/2/1, drawing (gamestate = 0), or winning by 1/2/3/4

Conversion rates when losing are all effectively the same (10.5%)

Shots are statistically more likely to go in when drawing than losing..
.. and at almost every step, shots are statistically more likely to go in when winning

11.8% when drawing, 15.3% when winning by 1. Significant

16.9% when winning by 2 & significantly more likely than even when winning by 1

And so on until +4 isn't statistically more than +3
Read 14 tweets
Feb 7
why the hell do the USMNT stans care so much about shouting into the void that the US would win the Asian Cup?

Being in the concacaf gold cup final almost by default has made them so entitled
Like, yes, we are a very good team.

But so is Japan

And Korea

And Iran. & Iraq. Saudi Arabia, Qatar, Australia... And then teams like Uzbekistan, UAE, Jordan, Oman, they can beat anyone on their day

Thailand, Vietnam, Kyrgyzstan, Tajikistan, Lebanon, Bahrain... not easy!!!
Pretend we just swapped places with Japan. Since they were pre-tourney faves and USMNT Stans think we would be to. Straight swap.

Iraq, Indonesia, Vietnam is the group.

Indonesia we beat, sure. Vietnam too. But we'd struggle vs Iraq like Japan did. Iraq can SCORE, man
Read 9 tweets
Oct 21, 2023
🚨🚨 Python package update

I have a treat for y'all today!

I've added a new function to my python package. It is code to create a post-match dashboard for a given match on Whoscored

Please see this link for more info on the package

πŸ‘‰ github.com/griffisben/gri…

Image
Image
Please note that you will need to uninstall and then re-install the package if you've already installed it before

And IMPORTANT NOTE, you will need ChromeDriver for this to work. I apologize, but I can't be tech support for everyone. Here is that link
chromedriver.chromium.org/downloads
The github page has the code you can copy/paste.

Please note that there are several file paths that you'll need to update. Particularly, the path to where you have ChromeDriver installed, as well as team logos (I get mine from wikipedia)

Just need to paste Whoscroed match HTML Image
Read 6 tweets
Aug 3, 2023
My thoughts on FBRef's standard scouting report metric when using it on a CB

Can really only look at 4-6 metrics, and they're all on-ball, in-possession ones

Not really a reason to look at almost all the attacking metrics, and nearly every defensive metric is bad Image
Non-penalty goals: not really useful. Most CBs only score when up for corners, so dependent on too many factors

npxG: same as npG

Shots: fine to look at but will by and large be shots from corners, so keep that in mind. Still not good to *compare* off just this metric
Assists: doesn't matter for a CB overall, only extremely select systems. Ignore

xAG: same as assists

npxG_xAG: I shouldn't need to say why now

Shot-creating actions: really only matters for high-possession systems the CBs are pretty involved in
Read 19 tweets
Jun 12, 2023
If Khvicha Kvaratskhelia ends up leaving Napoli, are there any possible replacements similar to Kvara?

Here are the top 20 similar style players, in leagues with relatively similar styles to Serie A, and teams in those leagues with relatively similar styles to Napoli...

🧡 Image
If we look at Kvaradona, he was a young, high-potential prospect that, while incredible, may not have been expected to be THIS good in season 1 in Naples.

Any on this list that meet that? I think so.

I'll look at a few U22 talents with somewhat similar styles to Kvara
Mohamed Daramy. He's on loan from Ajax, and has absolutely killed it in Danmark this season

Ajax bought him for 12 million last summer. So it might be unrealistic, but definitely possible although if Ajax are open to selling... clubs with likely more resources will be in for him Image
Read 10 tweets
Jun 12, 2023
For a little expansion, some vizzes of the data

Brighton are a good example because the goal kicks and their long passes right after short goal kicks tend to come from similar areas (central)

A bit higher cmp% on long after short GK than on long GKs Image
Fulham another example, but with different areas of the pitch both passing from and being targeted. Image
Adelaide United another good example of this.

Passes do tend to be shorter than goal kicks, so they're usually more accurate but have the same effect as a long goal kick Image
Read 4 tweets

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