San Diego’s xGD trend against playoff opponents seem to be pretty close to their overall trend.

In contrast, Inter Miami’s stands out as one of the team’s whose numbers drop off the most against stronger opponents.

I have to do some estimations for extra time from match event logs, which leaves some leeway for error. This is why I favor the fbref's listed xGD/90 figure when showing the overall xGD per team.

Your math is probably not bad. It's supposed to be Leading xGD * Leading Duration % + Trailing xGD..., which does come out to -0.03. To "square" things with fbref, I end up using what they list as total xGD/90 on the right-hand side, which was +0.03 at time of scraping. (Looks like it's +0.01 now.)

lmk if this is along the lines of what you're looking for. happy to iterate

absolutely! i’ll post a follow up when i can

MLS playoffs are coming soon, so here's my cheat sheet to digest how every team has performed this season

@cata-bush.bsky.social is actually insane for this… this seems really easy to use, has great aesthetics, and includes just about every kind of plot you can imagine

i believe the author’s name is Tyson Ni. (not sure if he is on bsky.)

i was made aware of these rankings from a @rwohan.bsky.social article

it was offseason for everyone, and now i'm rusty with my viz 😅

Which Big 5 teams improved the most over the summer in the eyes of odds-makers? And which teams fell out of favor?

(Ratings from PitchRank)

That's it, folks, #VizBuzz has come to an end and we've crowned @tonyelhabr.bsky.social champion 👑👑👑

The finals was FILLED with ties, which give me life, including a tie for second between @johnbedwards.io and the mighty @qntkhvn.bsky.social

It's the end of VizBuzz, but it lives in our ❤️
#databs

i feel like this points to a selection bias that pre-shot xG may not capture. players who are good with their weak foot are more likely to take more shots with it and balance out goals with misses, and those who are poor with their weak foot will only take shots with it in very favorable positions

🔗 tonyelhabr.rbind.io/posts/soccer...

An annual must read. Happy to see my own writing linked here.

memes in 2014 vs. 2024

xGD is live from Opta here (including the ongoing matches)

Fun hypothetical: How would the EPL table look right now if the result of every 1-score match was flipped?

Biggest risers:
1. Wolves: +9 pts, 17th -> 5th
2. Crystal Palace: +9 pts, 19th -> 8th

Biggest fallers:
1. Brighton: -12 pts, 2nd -> 18th
2. Aston Villa: -9 pts, 8th -> 19th

#rstats

Game state xGD table of truth for the MLS 2024 playoff teams

❤️ the references to public studies on finishing

the great bsky migration may be enough to get me to blog again

Finally got around to trying out Observable JS in depth. It's really nifty! I used it to make some sick ⚽ plots in this post: tonyelhabr.rbind.io/posts/ball-p...

#rstats

where is my GitHub achievement badge 😈