Seems like there’s a lot of room for easy improvement by making teams then, do Great Quests have to be a solo effort? Are they actually important to accomplish or is one person failing not a big deal for anyone but him? If this is a sort of College, is the Great Quest a Final or also the Job career itself? What do they do afterwards? Can I just dump 5 and 5 on INT and WIS and set up a matchmaking business?
Anyways checked if there were people with identical stats were one succeeded and one failed, just in case whichever system translated stats to outcomes was fully deterministic, sadly, 2 pairs met those conditions.
My first observations before I feed this data into a neural network:
the highest stats loser:
[10, 6, 13, 10, 15, 10]
the lowest stats winner:
[8, 13, 5, 8, 11, 16]
average winner specialization (standard deviation): 3.5340118495400863
average loser specialization (standard deviation): 3.6968854737691705
Stats that yield both victory and loss:
[[8, 9, 12, 15, 12, 15], [6, 8, 10, 16, 10, 15]]
Not to nitpick, but does this mean classes like fighter, wizard, etc.. were merged in a generic “adventurer” class?
If not, I get the point of the post anyway, but it seems we are missing a pretty big part of the informations we need to choose.
Your interpretation is correct: there are no character classes in this world.
Seems like there’s a lot of room for easy improvement by making teams then, do Great Quests have to be a solo effort? Are they actually important to accomplish or is one person failing not a big deal for anyone but him? If this is a sort of College, is the Great Quest a Final or also the Job career itself? What do they do afterwards? Can I just dump 5 and 5 on INT and WIS and set up a matchmaking business?
Anyways checked if there were people with identical stats were one succeeded and one failed, just in case whichever system translated stats to outcomes was fully deterministic, sadly, 2 pairs met those conditions. My first observations before I feed this data into a neural network:
the highest stats loser: [10, 6, 13, 10, 15, 10]
the lowest stats winner: [8, 13, 5, 8, 11, 16]
average winner specialization (standard deviation): 3.5340118495400863
average loser specialization (standard deviation): 3.6968854737691705
Stats that yield both victory and loss: [[8, 9, 12, 15, 12, 15], [6, 8, 10, 16, 10, 15]]