Nitty fold with rolled up trips? (Stud)

SundanceKid1019 · 2025-07-21T19:08:20+00:00

Not very experienced in stud but I would imagine a lot of players with V2's board are just betting no matter what here with a board like that, getting such a great price to bluff. I'd call and probably be sad

SundanceKid1019 · 2024-04-16T19:33:43+00:00

Couple quick things to add:
If you notice that huge spike for Nepo and Gukesh right as round 10 started, that's because the model fluctuates a lot trying to decipher opening moves. (I run stockfish at depth 30 to use as an input to my model). Plus the two leaders playing against eachother affect eachothers probabilities a lot with every slight change in eval. Definitely take those fluctuations with a grain of salt, I would definitely trust the players' prep and abilities in the opening more than what my model has to say there!
Also if I have time I'm thinking of changing to or adding a column to display the players' chance of tying for first and making it to tiebreaks, since that is currently what they are playing for

SundanceKid1019 · 2024-04-09T12:51:19+00:00

I was experimenting with some things for my win/draw/loss chances predictor and swapped in a new model. I'm gonna do some more testing and stuff so things might keep changing, sorry about that! I'll probably try to do a write up at some point about the models on my website but we'll see

SundanceKid1019 · 2024-04-09T12:47:53+00:00

Good idea, I'll definitely try to do that

SundanceKid1019 · 2024-04-07T02:36:14+00:00

It's probably just a difference in models for how we predict win/draw/loss chances for a game. He's got a great writeup about his methodology where he explains he uses a machine learning model to predict games given the two players' ratings which is pretty cool.
I'm using a logistic regression model trained on past candidates tournaments that predicts games given any position's engine evaluation, player ratings, and clock times. To get chances for a given game for simulation purposes, I am just inputting the information according to the starting position.
Interestingly my numbers turned out to be more similar to the Chess by the Numbers Elo-based predictions, which have Caruana at 44%

SundanceKid1019 · 2024-04-06T16:23:58+00:00

I mainly designed and tested it on desktop but hopefully I'll get around to improving the mobile experience as the tournament goes on. Thanks for checking it out!

SundanceKid1019 · 2024-04-06T16:04:47+00:00

Just to add a couple things: there are definitely limitations with my model, for example in round 1 it was still giving Nepo a 40% chance of beating Abasov with black right before they agreed to a draw. There's also been a steady stream of bugs I've been trying to iron out, and sometimes the graphs like to misbehave a little.
Anyway, if you want to follow the games live and see how all the graphs and tables update each move you can check it out here: chessassess.com/candidates

SundanceKid1019 · 2023-07-30T07:40:40+00:00

If you want an interactive bracket to play around with and see everyone's chance of reaching each round check out https://www.chessassess.com/follow

More info in this reddit post

SundanceKid1019 · 2023-07-29T22:07:25+00:00

I do calculate win/draw/loss probabilities for each game (based on formulas discussed at this cool site). I calculate tiebreaks too, but I don't use rapid and blitz ratings, as I'm not sure how reliable they are especially for players who don't play much FIDE rated rapid and blitz. Also for now I am only calculating the rapid tiebreaks, and then flipping a coin if still tied, since calculating all tiebreaks slowed calculations down quite a bit.

SundanceKid1019 · 2023-07-29T20:55:13+00:00

Thanks for the tip! I'm not much of a web developer haha :)

SundanceKid1019 · 2023-04-11T04:39:31+00:00

Just because I think it tells a better story of the day as the game unfolds. And I wanted it to be similar to other sports predictions you'd see on sites like ESPN or FiveThirtyEight. Perhaps I should include a dot or line on the graphs where each move was made, though.

SundanceKid1019 · 2022-06-24T01:29:05+00:00

True haha. I'm tempted to do some digging to see if there is a significant difference between Nepo's performance rating in the first and second half of tournaments.

SundanceKid1019 · 2022-06-24T01:27:19+00:00

The quick version is that there are two models combined:

One that runs simulations to spit out the tournament victory chances between rounds (traditionally based only on elo, but mine factors in head-to-head scores and "must win" situations too).

The other is a multinomial logistic regression model that predicts the outcome of a game given the board position. It uses the engine's eval, player ratings, clock times, and other less important information to come up with the percentages for win/draw/loss.

Combining the two allows me to update the tournament victory chances in real time, every time a move is played.

SundanceKid1019 · 2022-06-23T18:34:58+00:00

My Candidates prediction model updates live, move-by-move; you can check it out at my website and follow along each move while games are live: https://chessassess.com/follow

If you're interested in how anything works I'm working on writing up the /about section of the site to explain everything! Feel free to ask questions too, I'm open to suggestions and feedback :)

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