This is very interesting btw, thanks. I’ve downloaded your code but I haven’t used R before so am having some trouble figuring things out.
Does this output from your code relate to generic win probability (i.e. not against that specific team)?
# Groups: V1, V2, V3, V4 [14] V1 V2 V3 V4 V5 p <chr> <chr> <chr> <chr> <chr> <dbl> 1 Blaze Boy Greenery Giant Nullifying Nightmare Rock-n-Ro~ Tidehol~ 0.805 2 Blaze Boy Greenery Giant Nullifying Nightmare Phoenix P~ Tidehol~ 0.802 3 Blaze Boy Greenery Giant Landslide Lord Nullifyin~ Tidehol~ 0.795 4 Blaze Boy Greenery Giant Nullifying Nightmare Oil Ooze Tidehol~ 0.790 5 Blaze Boy Greenery Giant Nullifying Nightmare Quartz Qu~ Tidehol~ 0.789 6 Arch-Alligator Blaze Boy Greenery Giant Nullifyin~ Tidehol~ 0.787 7 Blaze Boy Greenery Giant Nullifying Nightmare Tidehollo~ Volcano~ 0.784 8 Blaze Boy Greenery Giant Inferno Imp Nullifyin~ Tidehol~ 0.784 9 Blaze Boy Dire Druid Greenery Giant Nullifyin~ Tidehol~ 0.781 10 Blaze Boy Greenery Giant Nullifying Nightmare Tidehollo~ Warrior~ 0.781 11 Blaze Boy Captain Canoe Greenery Giant Nullifyin~ Tidehol~ 0.778 12 Blaze Boy Greenery Giant Nullifying Nightmare Siren Sor~ Tidehol~ 0.775 13 Blaze Boy Earth Elemental Greenery Giant Nullifyin~ Tidehol~ 0.773 14 Blaze Boy Fire Fox Greenery Giant Nullifyin~ Tidehol~ 0.769 15 Blaze Boy Greenery Giant Maelstrom Mage Nullifyin~ Tidehol~ 0.769
I also got “object not found” errors and commented out the following lines to fix. I figured they looked likely duplicative of the code generating the above, but am concerned that I might have commented out the code that shows the best teams against the specific enemy team.
That’s nice to hear, thanks! Yes, those outputs in your first output block are the generic win probabilities, averaging over all possible Blue teams.
I’m not sure what those two lines were doing there. They’re not important. I’ve just now deleted them and updated the code at the link—I think everything should run without errors now.
This is very interesting btw, thanks. I’ve downloaded your code but I haven’t used R before so am having some trouble figuring things out.
Does this output from your code relate to generic win probability (i.e. not against that specific team)?
# Groups: V1, V2, V3, V4 [14]
V1 V2 V3 V4 V5 p
<chr> <chr> <chr> <chr> <chr> <dbl>
1 Blaze Boy Greenery Giant Nullifying Nightmare Rock-n-Ro~ Tidehol~ 0.805
2 Blaze Boy Greenery Giant Nullifying Nightmare Phoenix P~ Tidehol~ 0.802
3 Blaze Boy Greenery Giant Landslide Lord Nullifyin~ Tidehol~ 0.795
4 Blaze Boy Greenery Giant Nullifying Nightmare Oil Ooze Tidehol~ 0.790
5 Blaze Boy Greenery Giant Nullifying Nightmare Quartz Qu~ Tidehol~ 0.789
6 Arch-Alligator Blaze Boy Greenery Giant Nullifyin~ Tidehol~ 0.787
7 Blaze Boy Greenery Giant Nullifying Nightmare Tidehollo~ Volcano~ 0.784
8 Blaze Boy Greenery Giant Inferno Imp Nullifyin~ Tidehol~ 0.784
9 Blaze Boy Dire Druid Greenery Giant Nullifyin~ Tidehol~ 0.781
10 Blaze Boy Greenery Giant Nullifying Nightmare Tidehollo~ Warrior~ 0.781
11 Blaze Boy Captain Canoe Greenery Giant Nullifyin~ Tidehol~ 0.778
12 Blaze Boy Greenery Giant Nullifying Nightmare Siren Sor~ Tidehol~ 0.775
13 Blaze Boy Earth Elemental Greenery Giant Nullifyin~ Tidehol~ 0.773
14 Blaze Boy Fire Fox Greenery Giant Nullifyin~ Tidehol~ 0.769
15 Blaze Boy Greenery Giant Maelstrom Mage Nullifyin~ Tidehol~ 0.769
I also got “object not found” errors and commented out the following lines to fix. I figured they looked likely duplicative of the code generating the above, but am concerned that I might have commented out the code that shows the best teams against the specific enemy team.
The specific lines I commented out were:
arrange(desc(win_proba)) %>% head(20) %>% name_teams()
op_matchups_dat %>% head()
nvm, found the output about matchups with that specific team (below), still curious if the above was anything important
person_1 person_2 person_3 person_4 person_5 win_proba
<chr> <chr> <chr> <chr> <chr> <dbl>
1 Arch-Alligator Greenery Giant Landslide Lord Nullify~ Phoenix~ 0.755
2 Arch-Alligator Landslide Lord Nullifying Nightmare Phoenix~ Rock-n-~ 0.750
3 Arch-Alligator Landslide Lord Phoenix Paladin Rock-n-~ Warrior~ 0.748
4 Arch-Alligator Blaze Boy Landslide Lord Phoenix~ Rock-n-~ 0.738
5 Arch-Alligator Greenery Giant Landslide Lord Nullify~ Oil Ooze 0.726
6 Arch-Alligator Landslide Lord Phoenix Paladin Rock-n-~ Tidehol~ 0.724
7 Arch-Alligator Landslide Lord Nullifying Nightmare Oil Ooze Phoenix~ 0.719
8 Arch-Alligator Landslide Lord Phoenix Paladin Rock-n-~ Volcano~ 0.719
9 Arch-Alligator Landslide Lord Phoenix Paladin Rock-n-~ Siren S~ 0.718
10 Arch-Alligator Greenery Giant Landslide Lord Phoenix~ Rock-n-~ 0.712
That’s nice to hear, thanks! Yes, those outputs in your first output block are the generic win probabilities, averaging over all possible Blue teams.
I’m not sure what those two lines were doing there. They’re not important. I’ve just now deleted them and updated the code at the link—I think everything should run without errors now.
Thanks. Well, now that you’ve given this out I’ll steal it for my own use for this problem :)
I’ll comment on my answer on the main D&D.sci post.
Edit: linked comment