A data analyst and chess enthusiast Rafael Milk has been posting very confidently that he has found irrefutable evidence that Hans Niemann was not playing clean.
When you look at his analysis it basically all relies on analyses the linear relation between average centipawn loss and Elo. He assumes it to be true and then proceeds to show how Niemann's results disprove his assumption.
He doesn't show us an rigorous empirical evidence that his average centipawn loss theory is true or neither does he show us any tolerance levels or limits for the linear regression he is doing.
He also doesn't use the timescale. He assumes the timeline has no impact on the analysis. Hans Niemann for instance spent over a year at 2400+
It seems that it is an interesting approach but may be confirmation bias, since he creates a rule of thumb and says Niemann breaks the rule without showing that the rule works in on legit cases and doesn't have legit exceptions.
Chess drama continues...
www.youtube.com/watch?v=Q5nEFaRdwZY&t=1s
When you look at his analysis it basically all relies on analyses the linear relation between average centipawn loss and Elo. He assumes it to be true and then proceeds to show how Niemann's results disprove his assumption.
He doesn't show us an rigorous empirical evidence that his average centipawn loss theory is true or neither does he show us any tolerance levels or limits for the linear regression he is doing.
He also doesn't use the timescale. He assumes the timeline has no impact on the analysis. Hans Niemann for instance spent over a year at 2400+
It seems that it is an interesting approach but may be confirmation bias, since he creates a rule of thumb and says Niemann breaks the rule without showing that the rule works in on legit cases and doesn't have legit exceptions.
Chess drama continues...
www.youtube.com/watch?v=Q5nEFaRdwZY&t=1s