SzieberthAdam
Joined: Aug 31, 2008
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 Posted:
Feb 08, 2019 - 11:59 |
 
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I was trying to go over the Blackbox scheduler sustainability calculation to get a better view of its method but it seems that the documented way is either wrong or I made a bug which I doubt as I checked everything many times. I would be good to get a values with a factor of 0.5.
Here is my code:
https://github.com/FUMBBLPlus/blackbox/blob/master/sust.py
It seems that the Point 5 (Apply a small random factor, and normalise) returns a value in range of 0..1000 instead of 500..1000 plus somehow the sustainability result is inverted. I get higher scores when the site scheduler got lower and in the other way.
I was particuarly interested in this draw:
https://fumbbl.com/p/blackbox?op=scheduler&r=2019-02-08+01%3A30
Smallman complained about the high TV difference and about the scheduler in general and my mono activation but that goes to another post.
For the top 3 matchups I get the following results:
FUMBBL:
TV 1030k Necromantic Horror (3)
TV 1060k Norse (1)
@971
My script:
| Code: | > python sust.py 1030 1060 3 1
dTV_0 = 29.126213592232997
dTV = 29.126213592232997
p_0 = 0.4760663100888059
factor = 0.5
p = 0.4760663100888059
d_0 = 0.0239336899111941
d = 0.0525472527395459
S_0 = 52.5472527395459
r_opp = 1
r_games = 1
S = 52.5472527395459
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FUMBBL:
TV 1240k Skaven (5)
TV 1150k Human (6)
@896
My script:
| Code: | > python sust.py 1240 1150 5 6
dTV_0 = 78.26086956521738
dTV = 134.78260869565213
p_0 = 0.3909418562318328
factor = 0.5
p = 0.3909418562318328
d_0 = 0.10905814376816719
d = 0.23520884343857418
S_0 = 235.20884343857418
r_opp = 1
r_games = 1
S = 235.20884343857418
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And finally our matchup with 920 TV difference:
FUMBBL:
TV 2550k Dwarf (70)
TV 1630k Elven Union (33)
@510
My script:
| Code: | > python sust.py 2550 1630 70 33
dTV_0 = 564.4171779141105
dTV = 1593.2515337423315
p_0 = 0.005267839562496554
factor = 0.5
p = 0.005267839562496554
d_0 = 0.49473216043750345
d = 0.9880109899154592
S_0 = 988.0109899154592
r_opp = 1
r_games = 1
S = 988.0109899154592
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I will update if I know more. |
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CircularLogic
Joined: Aug 22, 2003
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| Posted:
Feb 10, 2019 - 10:14 |
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What I noticed in the linked description of the suitability score:
The graph in the bottom as well as steps 7-9 seem backwards as low suitability scores are the best. A rookie mirror match comes out at p=.5 and so without random factor you arrive at a distance d=0 which gives you a suitability score of 0 - which should be the best match.
There is your inversion @SzieberthAdam |
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