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ThomasCM | 2 years ago
If anyone wants more info on how this works, check out this post with more details: https://www.chessmonitor.com/blog/2023-elo-calculation
ThomasCM | 2 years ago
If anyone wants more info on how this works, check out this post with more details: https://www.chessmonitor.com/blog/2023-elo-calculation
usgroup|2 years ago
I suspect that the online population — especially at lower ratings — is significantly different to the over the board population. I also expect — especially in the FIDE case — that ratings stratify the players into hobbyists, serious amateurs, professionals, etc and so different FIDE rating ranges are likely to scale to online ratings differently.
All of the above should be implicitly accounted for in an isotonic regression so long as monotonicity holds globally. You can easily do it with sklearn and I suspect it may give you better results.
ThomasCM|2 years ago