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so you think you like stats ?

Very interesting article.
Hence my proposition. Which was meant to point out that ratios between 2 players is often far away from the theorical table.

Using the ratio of won/lost points for established players was a poor way to illustrate the "theorical" odds we had so much difficulties agreeing upon. Still, I maintain it's true for the elo rating.
In order to be rigorous, we should go back to the gaussian table. Don't we all that elo and glicko tend to a similar gaussian law? A simple gaussian table with a step of 50 or 25 pts, would be fine, as ratings change every game.

#22 Unfortunately using Bayesian inference (based on previous games) presumes that game outcomes are related! And you get dependency issues: game 1 is used to predict every other game, but game N-1 is only used to predict game N.

(Then try explaining the numbers to Beret Guy! http://xkcd.com/1252/ )

What might be fun is an "odds predictor" for the current game considering all preceding games with the same opponent, time control, variant, color, opening, etc.
Support your second amendment : refuse background checks for swimming dogs !

#22 Might be fun but that would be a little overcooked, it'd take a real lot of games between two players to be efficient. My idea was a simple normal law table.
I don't know why you want that bad to introduce Bayesian inference. Maybe i should just bow out and leave you my nerdiest nerd crown for your collection ;-)

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