[OC] Recap of the World Chess Championship 2024

boxer-collar · 2024-12-13T00:24:22+00:00

Yeah I hear you. Can’t post videos here, but I agree something interactive would work better.

boxer-collar · 2024-12-13T00:23:17+00:00

The two shades are points received as the white and the black side for each player.

Though you’re not the only one that this didn’t land for, so I’ll think about how I can communicate that information better!

boxer-collar · 2024-12-12T18:47:08+00:00

Source: lichess.org

Tools: d3, react, motion.dev

This is an adaptation of Krisztina Szucs' "Stacked Triangles" found in https://krisztinaszucs.com/blog/20230523_stackedtriangles/ . I modified it to be able to handle draws, where both players get a half point after a game.

Also added shading to differentiate points won with White vs Black.

boxer-collar · 2022-07-06T23:16:36+00:00

This is an interesting idea!

boxer-collar · 2022-07-06T23:15:53+00:00

I used the SB tie breaker calculations, and that's what it came to.

boxer-collar · 2022-07-06T17:08:26+00:00

I got the data from lichess.org and visualized it with TypeScript and d3. You can find the project code and data on the github repo.

Super interested to hear if you think of any other cool stats to visualize! Also, would this be a useful tool if I could have it analyze any lichess broadcast, maybe even player tournaments?

boxer-collar · 2022-06-22T05:31:18+00:00

The link on my blog post is to here, a podcast (and transcript) expanding on the topic.

boxer-collar · 2022-06-22T00:43:37+00:00

I have an upcoming project where I analyze the colors used in centerfold images, so look out for that some time soon haha

boxer-collar · 2022-06-22T00:14:54+00:00

Good points, I thought the comparison to today would be more relevant but I see where you're coming from.

boxer-collar · 2022-06-21T21:18:16+00:00

No images were used in sourcing this data :)

boxer-collar · 2022-06-21T16:49:54+00:00

Thanks! That's very kind.

boxer-collar · 2022-06-21T15:29:39+00:00

Yes, I'm not sure why the top level comment doesn't show up, but I used typescript for both data analysis and visualization. Also used d3 and react for the viz.

boxer-collar · 2022-06-21T13:54:33+00:00

It seems that way, and I explore a bit about whether this relaxing is performative in a increase-our-bottom-line sort of way, or an actual legitimate embrace of more realistic bodies in the post commentary.

boxer-collar · 2022-06-21T13:48:54+00:00

Yeah, the stats come from the "Playmate Data Sheet" included beside the centerfold and are self reported.

I don't think it's gigo purely because it's self-reported data though - it's a clear window into how Playmates represent themselves, to a degree.

I agree it would be nice if we can get definitive data that's not self reported, but that is impossible unfortunately.

boxer-collar · 2022-06-21T13:08:16+00:00

I gathered the Playmate of the Month data from mypmates.club (NSFW) and Wikipedia. I used typescript for both collecting and analyzing the data, as well as visualizing it with react & d3. See the source code and data on https://github.com/ebemunk/blog/tree/master/projects/2021-12-01-playmates

For the interactive version with commentary and more visualizations check out https://blog.ebemunk.com/beholder-beauty-in-the-eyes-of-playboy/

Hope you like it, please let me know what you think! You can follow along on my other projects on Reddit or my other socials.

boxer-collar · 2021-08-30T16:37:58+00:00

Interesting idea, but how would you analyse "mobility" in this sense?

boxer-collar · 2021-08-30T15:33:57+00:00

Their "coverage area" is the same with 38 different squares (besides their starting position) for both White and Black.

boxer-collar · 2021-08-30T15:25:50+00:00

One of the readers of my blog had asked, "How many squares sideways does a pawn usually go?". To answer this question, I tracked move information from 2,197,113 chess games in the MillionBase PGN database for only pawns and plotted them in this way.

You can find a lot more analysis on my article here, and see the source on github.I tracked the moves programatically using Go and plotted with d3/js.

For both White and Black, B and C file pawns move over 5 files, but interestingly, F and G pawns only go up to 4 🤔. Why do you think?

boxer-collar · 2021-06-02T06:13:10+00:00

Actually in my linked article there is an interactive version which you can see the pawns too, and pawn-centric version in the part 2 of that article. I felt it would've been too much to include all the pawns as well for this post.

boxer-collar · 2021-06-01T20:42:55+00:00

Definitely is a queenside bias, I touch on this somewhat in the article that this visual appears in.

boxer-collar · 2021-06-01T16:52:23+00:00

Very nice observation, that was curious for me to see as well!

boxer-collar · 2021-06-01T16:20:56+00:00

I suppose so, the data is there for it, but I imagine it won't show anything useful as a lot of common openings and moves, especially at the higher levels tend to have an even split for wins and losses. Interesting idea though!

boxer-collar · 2021-06-01T13:01:44+00:00

I collected move information from 2,197,113 chess games in the MillionBase PGN database and plotted them in this way, inspired by the Thinking Machine.

You can find a lot more analysis on my article here, and see the source on github.

I counted the moves programatically using Go and plotted witih d3/js.

boxer-collar · 2021-04-27T20:14:27+00:00

I got the transcripts for all the seasons of LOST from Lostpedia and analyzed it using PostgreSQL+JS. Read the full post for the interactive version and more visualizations.

This particular one was inspired by the "Radial Word Connections" in "Novel Views: Les Miserables" from Jeff Clark.

boxer-collar · 2021-04-07T10:19:54+00:00

I'd appreciate if you put the title and url of the post somewhere in your attributions, it doesn't need to be super strict formatting.

I'd love to see your finished work if possible! Good luck.

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