I confirm abstractapplic’s finding of three groups. However I have also classified ATW into the MPR group, BD into the GLS group, and F into the CHJ group.
I’ve mostly looked at the dataset restricted to teams (on both sides) that have one character from each group. These teams generally do better than teams with other arrangements, but I could be missing some more narrow counter using a different arrangement.
With this restriction, most winrate variation seems to me to be related to the strength of individual characters, though I could be missing more complicated interactions since I’ve mostly been looking at two-character interactions only. I do note that Lamellar Legionary (already the highest winrate melee) seems to counter Flamethrower Felon which is on the other team.
I also note that not all characters are equally common but this doesn’t seem to be skewing the results all that much (at least in the restricted set of games).
Conveniently, CLP is the highest winrate team with the restriction of games to ones with both teams having one from each group, and the L should counter the enemy F, so I’ll go with that for PVE, though it seems a somewhat bland answer. Edit: oops C seems to be countered by enemy S, I’ll switch to J instead (which also does poorly against S but not unexpectedly so given raw winrates), as JLP is the second highest winrate team in the restricted set of games. I’ll keep my PVP pick the same for now. Flamethrower Felon would counter S but does not have as high a winrate full team combo with L (FLM being the highest such in twelfth place).
abstractapplic’s PVE team is the eighth highest winrate with this restriction, and could well be a superior pick if exploiting some interaction that I didn’t notice.
Thus my PVE pick (for now):
Jaunty Javelineer, Lamellar Legionary, Professor Pyro
Further edit: I looked at who beats FSR and it looks like it actually does fairly well against one from each group in general. The best comp type against it seems to be 2 melee + one from the CFHJ group, second is 1 melee plus two long range, third is two melee, one long range. In particular, Bludgeon Bandit+Daring Duelist + one from CFHJ have never lost to FSR (out of, like, 8 examples, so I’m really risking randomness here) despite both B and D being “bad” picks usually. Thus, I’ve gone mad and switching to:
Captain Chakram, Lamellar Legionary, Professor Pyro
For PVP—for now I’m just going to use my (pre-edit) PVE pick as my tentative PVP pick (retained above) and challenge others to counter it. But I may later swap out to a secret pick with more analysis. If I do, I’ll cross out my PVP pick declaration in this comment.
I checked out what happens if you remove games that include any “trash picks” (A,B,D,T,W), in addition to requiring teams to include one character from each group. This further reduces the dataset significantly, but I noticed that in this set of games, the opposing team FSR has the highest winrate, which suggests it is a very strong team against other conventionally strong teams, even if it doesn’t exploit weaker teams that well.
In this further reduced set, the second highest winrate is JLM, then CLP, then JLP.
Given the low amount of data points, however, these winrate variations between the top teams in the further restricted set could easily be random, so I don’t think there’s all that strong a case to change my picks, and my choices above are unchanged for now. However, this does suggest JLM as an alternate candidate against FSR, and the opposing team FSR itself as a possible PVP pick (if people don’t just submit their PVE picks, or you think people will fail to counter it).
edit:
oh wait. For the top teams, the wins are higher if you include trash picks, but the losses often aren’t. This means that these teams are basically always winning against trash picks, and the apparent higher number of data points is effectively an illusion, and the trash-pick-including win rates are distorted by how often teams were matched against bad teams.
examples (strong = has one character from each group, no trash picks, weak = has one character from each group, but at least one trash pick)
team | wins against strong | losses against strong | wins against weak | losses against weak
CLP | 24 | 14 | 118 | 0
JLP | 20 | 12 | 92 | 0
CSP | 23 | 17 | 102 | 0
but on the other hand:
HLP | 21 | 19 | 96 | 3
JLM | 28 | 15 | 100 | 7
FSR | 26 |12 |99 |10
I don’t know to what extent failing to defeat all the weak teams should be taken as evidence that a team isn’t good in general (so that the good numbers against strong teams are more likely to be a fluke).
Takeaways: my data is really thin even in the larger restricted set and I should pay little attention to these winrate variations between full teams; I should try to find more general patterns. I should also maybe look at what particular “trash” picks can beat FSR, in case it is losing reliably to some narrow counter as opposed to just not reliably beating weaker teams in general.
Update in view of the answer likely being soon to be posted:
I got sidetracked among other (non-D&DSci) things by trying to semi-automatically categorize the team compositions in the games with only the restricted team compositions (one character from each group, no trash picks) into similarity clusters. This was tricky because there is a lot of noise in this much smaller dataset, and I didn’t take into account games outside this restricted set at all.
Ultimately, I did get three clusters which seemed to have a rock-paper-scissors interaction. One cluster is Felon-heavy (indeed seems to maybe have all Felon teams) and FLR seems to be a fairly archetypal example. Another cluster is Samurai-heavy and Golem-light; HSM seems to be a fairly archetypal example. The third cluster is Pyro-heavy and JGP seems to be a fairly archetypal example.
Anyway, the FLR cluster tends to beat the HSM cluster which tends to beat the JGP cluster which tends to beat the FLR cluster.
The PVE opposing team, FSR, mostly seems to be in the FLR cluster but is not very central, leaning a bit to the HSM cluster. It hasn’t faced the JGP cluster a lot (maybe 5-6 games depending on cluster definition) and has won maybe 3 or 4 of those, atypical for an FLR cluster member, but that could easily be random due to the low number of games.
Notably, my current PVP pick, CLP, seems to be in the JGP cluster and, as is typical for members of this cluster, tends to lose to members of the HSM cluster. In the absence of reasons to believe that other players have picked teams from the HSM cluster (hmm, but yonge picked HMP (which isn’t in this restricted dataset since it has two characters from the same group) - would that behave like HSM??) I don’t see a compelling reason to switch, though I might change my mind if I post this comment and then the answer isn’t posted for a long time.
Anyway, I’m not sure whether the rock-paper-scissors effect seen in the clustering derives from some collective interaction or is just a result of character pair interactions. Some apparent counters in this restricted dataset:
F>S;P>F;G>F;F>R;J>P;S>J;R>J;S>C;P>L;S>P;C>F
Also:
I’ve now gone and looked at what FSR wins against and adjusted my PVE pick accordingly. I’ll likely adjust my PVP pick as well if I end up having time to check what sort of things candidate PVP picks (and other players’ PVP picks where posted) do well against.
edit: looks like this comment was after aphyer posted the answer, but I checked for any new posts after my PVE edit above and didn’t see aphyer’s post of the answer.
Sorry, wasn’t expecting anything today! I’ll update the wrapup doc to reflect your PVE answer: sadly, even if you had an updated PVP answer, I won’t let you change that now :P
my findings so far:
I confirm abstractapplic’s finding of three groups. However I have also classified ATW into the MPR group, BD into the GLS group, and F into the CHJ group.
I’ve mostly looked at the dataset restricted to teams (on both sides) that have one character from each group. These teams generally do better than teams with other arrangements, but I could be missing some more narrow counter using a different arrangement.
With this restriction, most winrate variation seems to me to be related to the strength of individual characters, though I could be missing more complicated interactions since I’ve mostly been looking at two-character interactions only. I do note that Lamellar Legionary (already the highest winrate melee) seems to counter Flamethrower Felon which is on the other team.
I also note that not all characters are equally common but this doesn’t seem to be skewing the results all that much (at least in the restricted set of games).
Conveniently, CLP is the highest winrate team with the restriction of games to ones with both teams having one from each group, and the L should counter the enemy F, so I’ll go with that for PVE, though it seems a somewhat bland answer. Edit: oops C seems to be countered by enemy S, I’ll switch to J instead (which also does poorly against S but not unexpectedly so given raw winrates), as JLP is the second highest winrate team in the restricted set of games. I’ll keep my PVP pick the same for now. Flamethrower Felon would counter S but does not have as high a winrate full team combo with L (FLM being the highest such in twelfth place).
abstractapplic’s PVE team is the eighth highest winrate with this restriction, and could well be a superior pick if exploiting some interaction that I didn’t notice.
Thus my PVE pick (for now):
Jaunty Javelineer, Lamellar Legionary, Professor PyroFurther edit: I looked at who beats FSR and it looks like it actually does fairly well against one from each group in general. The best comp type against it seems to be 2 melee + one from the CFHJ group, second is 1 melee plus two long range, third is two melee, one long range. In particular, Bludgeon Bandit+Daring Duelist + one from CFHJ have never lost to FSR (out of, like, 8 examples, so I’m really risking randomness here) despite both B and D being “bad” picks usually. Thus, I’ve gone mad and switching to:
Jaunty Javelineer, Bludgeon Bandit, Daring Duelist
retaining for PVP:
Captain Chakram, Lamellar Legionary, Professor Pyro
For PVP—for now I’m just going to use my (pre-edit) PVE pick as my tentative PVP pick (retained above) and challenge others to counter it. But I may later swap out to a secret pick with more analysis. If I do, I’ll cross out my PVP pick declaration in this comment.
Also:
I checked out what happens if you remove games that include any “trash picks” (A,B,D,T,W), in addition to requiring teams to include one character from each group. This further reduces the dataset significantly, but I noticed that in this set of games, the opposing team FSR has the highest winrate, which suggests it is a very strong team against other conventionally strong teams, even if it doesn’t exploit weaker teams that well.
In this further reduced set, the second highest winrate is JLM, then CLP, then JLP.
Given the low amount of data points, however, these winrate variations between the top teams in the further restricted set could easily be random, so I don’t think there’s all that strong a case to change my picks, and my choices above are unchanged for now. However, this does suggest JLM as an alternate candidate against FSR, and the opposing team FSR itself as a possible PVP pick (if people don’t just submit their PVE picks, or you think people will fail to counter it).
edit:
oh wait. For the top teams, the wins are higher if you include trash picks, but the losses often aren’t. This means that these teams are basically always winning against trash picks, and the apparent higher number of data points is effectively an illusion, and the trash-pick-including win rates are distorted by how often teams were matched against bad teams.
examples (strong = has one character from each group, no trash picks, weak = has one character from each group, but at least one trash pick)
team | wins against strong | losses against strong | wins against weak | losses against weak
CLP | 24 | 14 | 118 | 0
JLP | 20 | 12 | 92 | 0
CSP | 23 | 17 | 102 | 0
but on the other hand:
HLP | 21 | 19 | 96 | 3
JLM | 28 | 15 | 100 | 7
FSR | 26 |12 |99 |10
I don’t know to what extent failing to defeat all the weak teams should be taken as evidence that a team isn’t good in general (so that the good numbers against strong teams are more likely to be a fluke).
Takeaways: my data is really thin even in the larger restricted set and I should pay little attention to these winrate variations between full teams; I should try to find more general patterns. I should also maybe look at what particular “trash” picks can beat FSR, in case it is losing reliably to some narrow counter as opposed to just not reliably beating weaker teams in general.
Update in view of the answer likely being soon to be posted:
I got sidetracked among other (non-D&DSci) things by trying to semi-automatically categorize the team compositions in the games with only the restricted team compositions (one character from each group, no trash picks) into similarity clusters. This was tricky because there is a lot of noise in this much smaller dataset, and I didn’t take into account games outside this restricted set at all.
Ultimately, I did get three clusters which seemed to have a rock-paper-scissors interaction. One cluster is Felon-heavy (indeed seems to maybe have all Felon teams) and FLR seems to be a fairly archetypal example. Another cluster is Samurai-heavy and Golem-light; HSM seems to be a fairly archetypal example. The third cluster is Pyro-heavy and JGP seems to be a fairly archetypal example.
Anyway, the FLR cluster tends to beat the HSM cluster which tends to beat the JGP cluster which tends to beat the FLR cluster.
The PVE opposing team, FSR, mostly seems to be in the FLR cluster but is not very central, leaning a bit to the HSM cluster. It hasn’t faced the JGP cluster a lot (maybe 5-6 games depending on cluster definition) and has won maybe 3 or 4 of those, atypical for an FLR cluster member, but that could easily be random due to the low number of games.
Notably, my current PVP pick, CLP, seems to be in the JGP cluster and, as is typical for members of this cluster, tends to lose to members of the HSM cluster. In the absence of reasons to believe that other players have picked teams from the HSM cluster (hmm, but yonge picked HMP (which isn’t in this restricted dataset since it has two characters from the same group) - would that behave like HSM??) I don’t see a compelling reason to switch, though I might change my mind if I post this comment and then the answer isn’t posted for a long time.
Anyway, I’m not sure whether the rock-paper-scissors effect seen in the clustering derives from some collective interaction or is just a result of character pair interactions. Some apparent counters in this restricted dataset:
F>S;P>F;G>F;F>R;J>P;S>J;R>J;S>C;P>L;S>P;C>F
Also:
I’ve now gone and looked at what FSR wins against and adjusted my PVE pick accordingly. I’ll likely adjust my PVP pick as well if I end up having time to check what sort of things candidate PVP picks (and other players’ PVP picks where posted) do well against.
edit: looks like this comment was after aphyer posted the answer, but I checked for any new posts after my PVE edit above and didn’t see aphyer’s post of the answer.
Sorry, wasn’t expecting anything today! I’ll update the wrapup doc to reflect your PVE answer: sadly, even if you had an updated PVP answer, I won’t let you change that now :P