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Date Editor Before After
4/16/2014 9:51:34 AMEErankAdminAnarchid before revert after revert
4/16/2014 9:51:16 AMEErankAdminAnarchid before revert after revert
4/16/2014 9:50:30 AMEErankAdminAnarchid before revert after revert
4/16/2014 9:49:11 AMEErankAdminAnarchid before revert after revert
4/16/2014 9:48:53 AMEErankAdminAnarchid before revert after revert
Before After
1 [quote] Now to formalise the betting part:[/quote] 1 [quote] Now to formalise the betting part:[/quote]
2 Note that the proponents of a balancing change do not dispute fair victory chances. 2 Note that the proponents of a balancing change do not dispute fair victory chances.
3 \n 3 \n
4 That entire argument is that high stdev causes unpleasant while still winnable games, which implies that stdev should also be optimized against. Current algorithm completely disregards the second parameter, so we can tentatively consider it to sacrifice stdev in favor of win-chance. 4 That entire argument is that high stdev causes unpleasant while still winnable games, which implies that stdev should also be optimized against. Current algorithm completely disregards the second parameter, so we can tentatively consider it to sacrifice stdev in favor of win-chance.
5 \n 5 \n
6 Thus the change-proponent side should produce an algorithm that optimizes both win chance and stdev, which will likely lead to reduced accuracy of win-chance optimization. The question is how much winchance-fairness will be lost to procure extra bits of stdev-fairness. 6 Thus the change-proponent side should produce an algorithm that optimizes both win chance and stdev, which will likely lead to reduced accuracy of win-chance optimization. The question is how much winchance-fairness will be lost to procure extra bits of stdev-fairness.
7 \n 7 \n
8 Unfortunately, you cannot resolve the efficacy of such an algorithm simply by betting on historical data, because you cannot rearrange the teams and see what happens. At best, you can calculate "what i would have done" for each of those games and see if they are indeed fairer (either/or by winchance or stdev) 8 Unfortunately, you cannot resolve the efficacy of such an algorithm simply by betting on historical data, because you cannot rearrange the teams and see what happens. At best, you can calculate "what i would have done" for each of those games and see if they are indeed fairer (either/or by winchance or stdev)
9 \n 9 \n
10 Also note that any bets you make on this dataset will be tainted by operating under modern, not historical, elo values. 10 Also note that any bets you make on this dataset will be tainted by operating under modern, not historical, elo values.
11 \n 11 \n
12 Last but not the least, consider that under current algorithm, if zk would grow 10-fold, you would get paired with [u]better[/u] people the better you play. The ideal solution is still procurement of an infinite playerbase, which would allow a 1600 elo player to play 10v10 where each other player is 1600. 12 Last but not the least, consider that under current algorithm, if zk would grow 10-fold, you would get paired with [u]better[/u] people the better you play. The ideal solution is still procurement of an infinite playerbase, which would allow a 1600 elo player to play 10v10 where each other player is 1600.
13 \n
14 So... if you want to see changes, [u]impart algorithm[/u].