Good to know, thank you! I think my main takeaway is that I am really bad at judging difficulty levels on these: I actually expected this scenario to be easier than the previous Dwarves & D.Sci scenario, but that one had three different near-perfect solutions while this one only had one noticeably-better-than-random solution.
Long-winded and empirically incorrect argument that led me to that expectation follows:
I was aware of the large number of possible characters—this is why the dataset ended up being so big, because I wanted to be sure it was large enough to allow simple analyses to work in spite of that. One sample approach I tried out on my end as part of designing the scenario was this:
Take only teams that contained a Knight of Blood and a Mage of Time (but of any size).
For each possible classpect, find its winrate on those teams.
This would have given you ~4k teams, with ~120 with each possible other classpect, which wasn’t enough to get an optimal solution but would have been an excellent first step:
Page of Heart has a 59.46% winrate
Maid of Heart has a 57.01% winrate
Maid of Breath has a 51.55% winrate
...
...
Heir of Hope has a 27.10% winrate
Heir of Rage has a 26.85% winrate
Maid of Void has a 22.64% winrate
As I envisioned things playing out:
Just running this approach and grabbing the two highest characters you could:
You would have picked a Page of Heart (3-9-3) and a Maid of Breath (2-12-1)
This would have given you stats of 18-25-17, for a lowest stat of 17 and a 64% winrate.
This isn’t optimal (it over-invests in Friendship, since you’ve picked two different high-Friendship characters), but it’s noticeably better than random.
Additionally, looking at the high/low scores might point you further in useful directions:
For instance, Heart/Breath/Life showed up an awful lot in the top on a variety of different classes.
This might have pointed you in the direction of ‘there’s a specific thing I’m missing’ and gotten you to bring only one Heart-like hero.
Sadly it seems I overestimated how obvious a thing to try that was. Based on the answers it looks like:
simon did something fairly similar to this, requiring 4-person teams but only requiring one of your two starting characters on the team, and ended up with a similar outcome of ‘generally good, but overinvested a bit in Friendship’.
Yonge ran some analysis that did a good job of finding ‘generally strong characters’ but wasn’t specific to the two characters you started with.
You did some kind of ML thing I didn’t understand.
Good to know, thank you! I think my main takeaway is that I am really bad at judging difficulty levels on these: I actually expected this scenario to be easier than the previous Dwarves & D.Sci scenario, but that one had three different near-perfect solutions while this one only had one noticeably-better-than-random solution.
Long-winded and empirically incorrect argument that led me to that expectation follows:
I was aware of the large number of possible characters—this is why the dataset ended up being so big, because I wanted to be sure it was large enough to allow simple analyses to work in spite of that. One sample approach I tried out on my end as part of designing the scenario was this:
Take only teams that contained a Knight of Blood and a Mage of Time (but of any size).
For each possible classpect, find its winrate on those teams.
This would have given you ~4k teams, with ~120 with each possible other classpect, which wasn’t enough to get an optimal solution but would have been an excellent first step:
Page of Heart has a 59.46% winrate
Maid of Heart has a 57.01% winrate
Maid of Breath has a 51.55% winrate
...
...
Heir of Hope has a 27.10% winrate
Heir of Rage has a 26.85% winrate
Maid of Void has a 22.64% winrate
As I envisioned things playing out:
Just running this approach and grabbing the two highest characters you could:
You would have picked a Page of Heart (3-9-3) and a Maid of Breath (2-12-1)
This would have given you stats of 18-25-17, for a lowest stat of 17 and a 64% winrate.
This isn’t optimal (it over-invests in Friendship, since you’ve picked two different high-Friendship characters), but it’s noticeably better than random.
Additionally, looking at the high/low scores might point you further in useful directions:
For instance, Heart/Breath/Life showed up an awful lot in the top on a variety of different classes.
This might have pointed you in the direction of ‘there’s a specific thing I’m missing’ and gotten you to bring only one Heart-like hero.
Sadly it seems I overestimated how obvious a thing to try that was. Based on the answers it looks like:
simon did something fairly similar to this, requiring 4-person teams but only requiring one of your two starting characters on the team, and ended up with a similar outcome of ‘generally good, but overinvested a bit in Friendship’.
Yonge ran some analysis that did a good job of finding ‘generally strong characters’ but wasn’t specific to the two characters you started with.
You did some kind of ML thing I didn’t understand.