I do not believe random’s Elo is as high as 477. That Elo was calculated from a population of chess engines where about a third of them were worse than random.
I have to back you on this… There are elo systems which go down to 100 elo and still have a significant number of players who are at the floor. Having seen a few of these games, those players are truly terrible but will still occasionally do something good, because they are actually trying to win. I expect random to be somewhere around −300 or so when not tested in strange circumstances which break the modelling assumptions (the source described had multiple deterministic engines playing in the same tournament, aside from the concerns you mentioned in the other thread).
Aren’t ELO scores conserved? The sum of the ELO scores for a fixed population will be unchanged? The video puts stockfish’s ELO at 2708.4, worse than some human grandmasters, which also suggests to me that he didn’t run the ELO algorithm to convergence and stockfish should be stealing more score from other weaker players. EDIT ChatGPT 5 thinks the ELOs you suggested for random are reasonable for other reasons. I’m still skeptical but want to point that out.
NB: If you think he underestimates stockfish Elo, then you should think he underestimate Random Elo, because the algorithm finds Elo gaps not absolute Elo.
Not if the ELO algorithm isn’t run to completion. It takes a long time to make large gaps in ELO, like between stockfish and Random, if you don’t have a lot of intermediate players. It’s hard for ELO to different between +1000 ELO and +2000 ELO—both mean “wins virtually all the time”.
I do not believe random’s Elo is as high as 477. That Elo was calculated from a population of chess engines where about a third of them were worse than random.
I have to back you on this… There are elo systems which go down to 100 elo and still have a significant number of players who are at the floor. Having seen a few of these games, those players are truly terrible but will still occasionally do something good, because they are actually trying to win. I expect random to be somewhere around −300 or so when not tested in strange circumstances which break the modelling assumptions (the source described had multiple deterministic engines playing in the same tournament, aside from the concerns you mentioned in the other thread).
That shouldn’t effect the Elo algorithm.
Aren’t ELO scores conserved? The sum of the ELO scores for a fixed population will be unchanged?
The video puts stockfish’s ELO at 2708.4, worse than some human grandmasters, which also suggests to me that he didn’t run the ELO algorithm to convergence and stockfish should be stealing more score from other weaker players.
EDIT ChatGPT 5 thinks the ELOs you suggested for random are reasonable for other reasons. I’m still skeptical but want to point that out.
Good point, I should look into this more.
NB: If you think he underestimates stockfish Elo, then you should think he underestimate Random Elo, because the algorithm finds Elo gaps not absolute Elo.
Not if the ELO algorithm isn’t run to completion. It takes a long time to make large gaps in ELO, like between stockfish and Random, if you don’t have a lot of intermediate players. It’s hard for ELO to different between +1000 ELO and +2000 ELO—both mean “wins virtually all the time”.