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Author Topic: More data mining: Answering Dominion questions with data  (Read 11397 times)

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theright555J

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Re: More data mining: Card "strength"
« Reply #25 on: January 31, 2015, 12:51:53 pm »
+1

Ironmonger is bad on Mountebank boards? Really? And you think it's significantly worse than, say, silver?

I'm pretty sure it's not that Ironmonger is a bad card, but rather if your opponent doesn't open with it, s/he probably got. 5/2 and just bought Mountebank.

EDIT: Ninja'd by Awaclus.
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TheExpressicist

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Re: More data mining: Card "strength"
« Reply #26 on: January 31, 2015, 01:08:03 pm »
0

Yeah. I think this list has a very (very) rough relationship with how good the cards are, but that isn't really good for much at all.

More important, these are overall rankings. On any given board, you can throw them out the window - it doesn't matter that 195 other cards exist which might make card X good or bad. You only have the other 9 which exist right then and there, and that's basically always going to be a lot different than the general case.

Agreed. I think what it's good for is looking at the cards with high gain rates and say, "Okay, so, good people buy this card in 8 out of 10 kingdoms. Is this kingdom I'm playing in really the exception to that?"

Quote
Re: the metric itself. The source of my head-scratching is, you applied a normal CDF to it. People do this all the time, and I'm not sure why - my guess is that it's because they did it all the time in their one stats course. But the thing is, most data isn't normally-distributed. So I can kind of understand wanting to do some kind of normalization to get things on the same scale, and I can kind of understand how how often the card is gained and how much you win when it is vs when it isn't are related to how good the card is, but even beyond the limitations of the approach from that perspective, I can't really get behind applying the Gaussian transformation.

It's normal-ish. The main reason for applying the CDF was to minimize the impact of the outliers; cards that were gained <10% of the time or so. Something that's, say, 5 SD away from the mean is accounted for roughly the same as something that's 3SD away from the mean. As I mentioned earlier, a much simpler way of doing it would have just been to take the actual ranking of the card (e.g. the 2nd least gained card has a score of 2, the 10th least gained card has a score of 10, etc.). I re-ran the numbers doing it that way and the scores are more or less the same. The most any card gained or lost was 4 "points" and the average difference was like 1.5 points.
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WanderingWinder

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Re: More data mining: Card "strength"
« Reply #27 on: January 31, 2015, 01:42:20 pm »
0

Yeah. I think this list has a very (very) rough relationship with how good the cards are, but that isn't really good for much at all.

More important, these are overall rankings. On any given board, you can throw them out the window - it doesn't matter that 195 other cards exist which might make card X good or bad. You only have the other 9 which exist right then and there, and that's basically always going to be a lot different than the general case.

Agreed. I think what it's good for is looking at the cards with high gain rates and say, "Okay, so, good people buy this card in 8 out of 10 kingdoms. Is this kingdom I'm playing in really the exception to that?"

Quote
Re: the metric itself. The source of my head-scratching is, you applied a normal CDF to it. People do this all the time, and I'm not sure why - my guess is that it's because they did it all the time in their one stats course. But the thing is, most data isn't normally-distributed. So I can kind of understand wanting to do some kind of normalization to get things on the same scale, and I can kind of understand how how often the card is gained and how much you win when it is vs when it isn't are related to how good the card is, but even beyond the limitations of the approach from that perspective, I can't really get behind applying the Gaussian transformation.

It's normal-ish. The main reason for applying the CDF was to minimize the impact of the outliers; cards that were gained <10% of the time or so. Something that's, say, 5 SD away from the mean is accounted for roughly the same as something that's 3SD away from the mean. As I mentioned earlier, a much simpler way of doing it would have just been to take the actual ranking of the card (e.g. the 2nd least gained card has a score of 2, the 10th least gained card has a score of 10, etc.). I re-ran the numbers doing it that way and the scores are more or less the same. The most any card gained or lost was 4 "points" and the average difference was like 1.5 points.


It's really not the same as taking ranks. I suppose it 'smooths outliers', but that presumes those things shouldn't be so far out, and my intuition doesn't tell me that's correct.

If you have things 5 st dev from the mean, it's NOT normal-ish.

And I fully understand how the Gaussian CDF works - I work as a statistician, and I went to school for physics - you compute the integrals  for Quantum Mechanics.

TheExpressicist

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Re: More data mining: Card "strength"
« Reply #28 on: January 31, 2015, 04:17:54 pm »
0

It's really not the same as taking ranks. I suppose it 'smooths outliers', but that presumes those things shouldn't be so far out, and my intuition doesn't tell me that's correct.

In the general sense, it's not. But in this case, it does approximate just taking ranks. Which as I mentioned before, was the effect I was shooting for. (See my previous post regarding the fact that using rankings resulted in approximately the same score +-2 points). We're not trying to draw any standard statistical conclusions here; it's an invented metric that's deliberately abstract in order to discourage people from trying to apply the score where it's not appropriate to do so.

P.S. I also do stats for a living.
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popsofctown

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Re: More data mining: Card "strength"
« Reply #29 on: January 31, 2015, 04:26:24 pm »
0

Incidentally, if you take the "Gain % Rank" and subtract the "Win % Rank" you get a pretty reasonable illustration of the "swingiest" cards:

1. Ironmonger (?? I don't quite get this one.)
2. Urchin (Makes sense; whoever collides their Urchins first has a huge advantage).
3. Tournament (duh.)
4. Swindler (also duh.)
5. Mountebank (also also duh.)

The justification being; these are cards powerful enough to justify top-tier players buying them more often than not. But also brainless enough that anyone can play them and have a decent shot at winning.

IN OTHER WORDS: WHEN YOU PLAY GOOD PEOPLE BUY ALL THE URCHINS AND SWINDLERSSSS
This is a very useful post, and it's interesting to see these commonplace beliefs statistically verified somehow.

Ironmonger makes a lot of sense if you consider how it can be kind of braindead to buy it instead of Silver.  Maybe even braindead to buy it over most other <5$ engine pieces for your engine.  That probably has more to do with it than randomly hitting Estates, although that might be a factor too.
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WanderingWinder

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Re: More data mining: Card "strength"
« Reply #30 on: January 31, 2015, 04:37:44 pm »
0

It's really not the same as taking ranks. I suppose it 'smooths outliers', but that presumes those things shouldn't be so far out, and my intuition doesn't tell me that's correct.

In the general sense, it's not. But in this case, it does approximate just taking ranks. Which as I mentioned before, was the effect I was shooting for. (See my previous post regarding the fact that using rankings resulted in approximately the same score +-2 points). We're not trying to draw any standard statistical conclusions here; it's an invented metric that's deliberately abstract in order to discourage people from trying to apply the score where it's not appropriate to do so.

P.S. I also do stats for a living.

Eh, that's fair I suppose. This isn't how I would do it, but I don't have anything to particularly say that the way I would do it is any better.

Throwaway_bicycling

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Re: More data mining: Card "strength"
« Reply #31 on: January 31, 2015, 05:44:08 pm »
0

Yeah. I think this list has a very (very) rough relationship with how good the cards are, but that isn't really good for much at all.

So I find some additional usefulness in the two components that I don't get from the composite. Knowing what cards are more likely to be gained by the strongest players (modulo the high situation-dependency you note) can be useful for the rest of us, and the hard data are better than our fallible memories. So if Qvist's rankings have two $4 villages in one order and the objective data has them in the opposite order by a decent margin...stuff like that would be revealing.

The other component, which shows how much more mileage strong players get out of specific cards, may also be interesting. This is really even more interesting for the more rarely gained cards (e.g., what are you all doing with Harvest? Maybe I should look.) But a lot of it seems to indicate how much better engine building gets for the Level 40 crowd, which many of us aspire to.

Quote
More important, these are overall rankings. On any given board, you can throw them out the window - it doesn't matter that 195 other cards exist which might make card X good or bad. You only have the other 9 which exist right then and there, and that's basically always going to be a lot different than the general case.

I agree in the general case, but there are some splits (Attacks present vs. not; Villages present vs. not, maybe others) where difference in gain rates and success given gain could be instructive.

(I skip the Magic references and shout out to Stef.)

Quote
Re: the metric itself. The source of my head-scratching is, you applied a normal CDF to it. People do this all the time, and I'm not sure why - my guess is that it's because they did it all the time in their one stats course.

That baffled me, too, which is why I mentally inserted a call to an empirical CDF function instead of the normal in my comment above. :-) I suppose if we were going to plug this into some analysis that really really cared about normality...but we're not.

So again: I see some value in the two rates separately (gain rate and win|gained), but no strong rationale for normality or for forming a single index. And I would like to see win|not_gained.
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SCSN

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Re: More data mining: Card "strength"
« Reply #32 on: January 31, 2015, 06:04:15 pm »
0

Incidentally, if you take the "Gain % Rank" and subtract the "Win % Rank" you get a pretty reasonable illustration of the "swingiest" cards:

1. Ironmonger (?? I don't quite get this one.)
2. Urchin (Makes sense; whoever collides their Urchins first has a huge advantage).
3. Tournament (duh.)
4. Swindler (also duh.)
5. Mountebank (also also duh.)

The justification being; these are cards powerful enough to justify top-tier players buying them more often than not. But also brainless enough that anyone can play them and have a decent shot at winning.

IN OTHER WORDS: WHEN YOU PLAY GOOD PEOPLE BUY ALL THE URCHINS AND SWINDLERSSSS
This is a very useful post, and it's interesting to see these commonplace beliefs statistically verified somehow.

I've always considered people complaning about Urchin's swinginess to be idiots. My winrate in Urchin mirrors is 63%, guess I'm just very lucky when it comes to colliding them!

I don't think Mountebank is very swingy either, as the blocking levels the playing field quite a bit. Looking at my own stats I'm winning 58.7% of Mountebank mirrors, versus just 51.8% for Witch.

Quote
Knowing what cards are more likely to be gained by the strongest players (modulo the high situation-dependency you note) can be useful for the rest of us

I doubt this is very useful, if someone 20 levels below me were to copy my exact gain %s he'd almost certainly be getting worse results than he's getting now.
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WanderingWinder

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Re: More data mining: Card "strength"
« Reply #33 on: January 31, 2015, 06:05:06 pm »
+1

Here's a fairly simple metric I'd like to see: Take the games in which exactly one player gains a card, then find in what percentage of those games the player who got the card won. Obviously this won't tell the entire story (true of any metric), but I like simple, intuitive things in general, when people can both understand the metric and its limitations.

dondon151

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Re: More data mining: Card "strength"
« Reply #34 on: January 31, 2015, 06:12:19 pm »
+3

I've always considered people complaning about Urchin's swinginess to be idiots. My winrate in Urchin mirrors is 63%, guess I'm just very lucky when it comes to colliding them!

I've always considered people complaining about people complaining about Urchin's swinginess to be idiots. I mean, they could just be better players, go figure.
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TheExpressicist

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Re: More data mining: Card "strength"
« Reply #35 on: January 31, 2015, 06:51:07 pm »
+4

Here's a fairly simple metric I'd like to see: Take the games in which exactly one player gains a card, then find in what percentage of those games the player who got the card won. Obviously this won't tell the entire story (true of any metric), but I like simple, intuitive things in general, when people can both understand the metric and its limitations.

I have that data. I'll post it shortly.
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SCSN

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Re: More data mining: Card "strength"
« Reply #36 on: January 31, 2015, 06:52:26 pm »
0

I've always considered people complaning about Urchin's swinginess to be idiots. My winrate in Urchin mirrors is 63%, guess I'm just very lucky when it comes to colliding them!

I've always considered people complaining about people complaining about Urchin's swinginess to be idiots. I mean, they could just be better players, go figure.

Next time you try to pick a fight make sure you actually have a point, lol. Having an above average winrate with a card is pretty damning evidence against its being swingy if your average opponent is worse than you.
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Throwaway_bicycling

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Re: More data mining: Card "strength"
« Reply #37 on: January 31, 2015, 07:01:10 pm »
0

Here's a fairly simple metric I'd like to see: Take the games in which exactly one player gains a card, then find in what percentage of those games the player who got the card won. Obviously this won't tell the entire story (true of any metric), but I like simple, intuitive things in general, when people can both understand the metric and its limitations.

Yes, that would be interesting. It would give you something like the relative risk of winning with Card X when there is a difference of opinion on strategy. A lot of that could be a wash, but some of it might be revealing. I think also the RR of winning|gain X vs. winning|not_gain X could be interesting.
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pacovf

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Re: More data mining: Card "strength"
« Reply #38 on: January 31, 2015, 07:08:22 pm »
0

I've always considered people complaning about Urchin's swinginess to be idiots. My winrate in Urchin mirrors is 63%, guess I'm just very lucky when it comes to colliding them!

I've always considered people complaining about people complaining about Urchin's swinginess to be idiots. I mean, they could just be better players, go figure.

Next time you try to pick a fight make sure you actually have a point, lol. Having an above average winrate with a card is pretty damning evidence against its being swingy if your average opponent is worse than you.

No. It is pretty damning evidence that you average opponent is worse than you. A swingy card can not lower your average winrate below 50% (edit: or increase your average winrate above 50%).

EDIT: after rereading your post, I see you weren't saying what I thought you were saying, so my point doesn't apply. Still, there are other explanations for what you are saying.
« Last Edit: January 31, 2015, 07:21:02 pm by pacovf »
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dondon151

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Re: More data mining: Card "strength"
« Reply #39 on: January 31, 2015, 07:14:35 pm »
+1

Next time you try to pick a fight make sure you actually have a point, lol. Having an above average winrate with a card is pretty damning evidence against its being swingy if your average opponent is worse than you.

Next time you choose to pursue a fight make sure you actually understand the point, lol. CR stats show that I had an above average winrate with Swindler on Iso; it's still a swingy card even if I could be expected to beat less able opponents to a pulp with or without it in the kingdom. You could be better than the average opponent at adapting to less favorable outcomes with Urchin, which makes up for the occasions where you have worse Urchin luck than your opponent, but that doesn't make Urchin less swingy.

But dude, you've been way more caustic than usual lately.
« Last Edit: January 31, 2015, 07:17:50 pm by dondon151 »
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Donald X.

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Re: More data mining: Card "strength"
« Reply #40 on: January 31, 2015, 07:29:40 pm »
+2

You could do lists that evaluate basic interactions. What is the win rate for a card sans +2 Actions, vs. the win rate when paired with +2 Actions? Or +1 Buy?
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Throwaway_bicycling

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Re: More data mining: Card "strength"
« Reply #41 on: January 31, 2015, 07:31:12 pm »
+1


Quote
Knowing what cards are more likely to be gained by the strongest players (modulo the high situation-dependency you note) can be useful for the rest of us

I doubt this is very useful, if someone 20 levels below me were to copy my exact gain %s he'd almost certainly be getting worse results than he's getting now.

Absolutely true, but that's not what I would be using it for.

One thing I noticed from the previous posted list of gain stats for stronger players and my personal gain stats is that I over-gain the "strong" cards and under-gain the "weak" cards, in a statistical sense. This could potentially happen for a lot of reasons, but looking a bit more closely, I think it usually means one of three things:

1) I under-appreciate the situational utility of some cards that are generically weak, maybe because I don't quite realize what they really could do. So I think more about those cards, re-check the wiki, maybe look up some games where they were in the kingdom and gained by strong players, and look at my own games where I gained or ignored them. So it can give me something concrete to think about while contemplating the general reasons why I am 20 levels weaker than (say) you.

2) I sometimes buy what could be "strong" cards without a complete understanding of how they would fit into my eventual plan. So there seems to be some evidence that I am way too enthusiastic about Farming Village. Might want to look into that.

3) Sometimes with some cards I apparently have No Idea. You buy it at 80%, I buy it at 30%. Or vice versa. No way should I gain it at the same rate as you until I figure it out, but that's an obvious place to look in general.
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TheExpressicist

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Re: More data mining: Card "strength"
« Reply #42 on: January 31, 2015, 07:48:42 pm »
+6

Win Rates for cards when they are only gained by one player. *Note: The average win rate for top-20 players is 65%. Naturally, the average win rate for all players is 50%.
Card NameAll Players%Top-20 Players Only%
Colony:78.6%93.5%
Goons:68.2%87.5%
Butcher:67.4%85.3%
Province:66.7%85.3%
Minion:66.6%77.1%
Vineyard:65.3%80.2%
King'sCourt:65.3%77.6%
Witch:62.5%77.7%
Baker:61.5%74.4%
Journeyman:61.3%76.3%
GrandMarket:60.8%73.2%
Masterpiece:60.6%67.6%
Mountebank:60.2%80.7%
Peddler:59.9%79.6%
Platinum:59.3%81.8%
BorderVillage:58.1%80.4%
Wharf:57.9%72.7%
Margrave:57.8%75.3%
WishingWell:57.5%69%
Catacombs:57.2%70.6%
Governor:57.1%73.9%
MerchantGuild:57%74.2%
Beggar:56.8%75.6%
GhostShip:56.2%77.1%
Explorer:55.9%72.5%
HornofPlenty:55.8%76.3%
Mint:55.8%78.8%
Library:55.8%69.9%
HuntingParty:55.7%70.3%
HuntingGrounds:54.7%78.6%
Ill-GottenGains:54.5%66.3%
MerchantShip:54.4%69.2%
Estate:54.1%69.9%
Laboratory:54.1%75.9%
MiningVillage:53.5%70.4%
Bazaar:53.3%72%
Masquerade:53.2%76.3%
Rogue:52.9%75.4%
Warehouse:52.8%61.6%
Pawn:52.8%73.3%
Festival:52.8%75.6%
Nobles:52.8%71.2%
Farmland:52.8%72%
ScryingPool:52.7%72.1%
Armory:52.7%70.6%
Apothecary:52.6%73%
Stonemason:52.6%63.2%
Possession:52.5%73.2%
Crossroads:52.3%68.8%
CountingHouse:52.2%69.7%
Menagerie:52.1%71.4%
JackOfAllTrades:52%63.4%
Copper:52%67.8%
CandlestickMaker:51.9%66.2%
Embassy:51.7%68.5%
WanderingMinstrel:51.6%66.7%
Hamlet:51.4%64.8%
Apprentice:51.3%71.6%
Altar:51.3%68%
BanditCamp:51.2%66.7%
Chancellor:51%69.6%
Familiar:51%74.7%
Scheme:50.9%69.3%
Mystic:50.9%65.5%
Hermit:50.7%64.3%
Scavenger:50.6%66.7%
Conspirator:50.5%72.2%
Quarry:50.5%67.4%
Highway:50.5%68.3%
Oracle:50.3%57.6%
HorseTraders:50.3%62.5%
Vault:50%60.2%
Fairgrounds:50%61.5%
ThroneRoom:50%64.8%
Harem:49.9%67.1%
Bridge:49.9%74.3%
Herald:49.9%62.9%
Counterfeit:49.8%70%
Workshop:49.8%62.3%
PearlDiver:49.8%65.4%
Worker'sVillage:49.8%66.7%
PoorHouse:49.7%62.7%
TradingPost:49.7%68.7%
JunkDealer:49.7%66.7%
Market:49.7%63.6%
City:49.5%80.9%
GreatHall:49.5%61.9%
FishingVillage:49.5%68.1%
Duchess:49.4%65.3%
Watchtower:49.3%68.1%
Inn:49.3%72%
Duke:49.1%64.6%
Treasury:49%71.2%
Contraband:49%75.8%
Rabble:48.9%72.9%
Fool'sGold:48.8%64.1%
Venture:48.7%67.7%
FarmingVillage:48.7%74.1%
Herbalist:48.6%72.1%
Ironmonger:48.6%62.5%
Stables:48.6%62.7%
Steward:48.6%54.8%
Courtyard:48.6%64.7%
Salvager:48.5%72.6%
Tournament:48.5%80%
Torturer:48.4%67.9%
Fortress:48.3%66.7%
Ambassador:48.2%62.5%
Sage:48.1%61.6%
SeaHag:48%63.1%
Squire:47.9%69.8%
Village:47.9%62.3%
Moneylender:47.9%75.6%
RoyalSeal:47.8%60%
Chapel:47.8%63.2%
Haggler:47.8%66.2%
BandofMisfits:47.8%65.8%
Feast:47.7%64.8%
Plaza:47.7%62.7%
Count:47.6%56.8%
Duchy:47.6%62.7%
Haven:47.5%58.1%
Swindler:47.4%65.2%
Woodcutter:47.4%66.1%
Gardens:47.2%62.2%
Remodel:47.2%65.4%
Mine:46.9%61.5%
BlackMarket:46.9%69.1%
Hoard:46.9%61.7%
Adventurer:46.8%73.9%
Gold:46.8%66.9%
ShantyTown:46.7%62.1%
Embargo:46.6%68.9%
Outpost:46.4%69.2%
Bank:46.3%65.3%
Urchin:46.2%57.6%
Smithy:46.1%66.4%
Cultist:46%72.1%
Lighthouse:46%58.8%
Procession:45.9%63.5%
NativeVillage:45.9%58%
Remake:45.8%70.6%
CouncilRoom:45.8%59.1%
Doctor:45.8%59%
NomadCamp:45.6%61.2%
Loan:45.6%62.1%
Mandarin:45.5%68%
Rebuild:45.4%61.5%
Vagrant:45.4%59.5%
Tactician:44.9%63%
Cartographer:44.9%62.8%
Expand:44.9%64.1%
TradeRoute:44.8%63.9%
Ironworks:44.7%62%
FortuneTeller:44.7%55.3%
Militia:44.6%57.5%
Marauder:44.5%68.3%
Baron:44.4%63.1%
Navigator:44.3%56.3%
Cellar:44.1%68.1%
Monument:44%71%
Bureaucrat:43.9%58.3%
Upgrade:43.8%57.1%
Taxman:43.6%71.2%
Potion:43.6%64.2%
Storeroom:43.6%59.7%
Moat:43.5%66.7%
Graverobber:43.3%51.9%
MarketSquare:43.2%60.5%
Caravan:43.2%69.2%
Island:43%57.9%
Lookout:42.7%64.6%
Smugglers:42.6%61.6%
Cutpurse:42.6%56.5%
Cache:42.5%46.4%
Harvest:42.2%71.4%
YoungWitch:42%64.7%
Advisor:41.6%64.4%
Alchemist:41.6%71.4%
Silver:41.5%54.8%
Golem:41.5%58.9%
Soothsayer:41.5%57.4%
TreasureMap:41.4%54%
Bishop:41.3%61%
Curse:41.3%54.3%
Feodum:41.2%55.4%
Trader:41%66.7%
DeathCart:41%56.8%
Develop:40.9%63%
Tunnel:40.8%62.5%
SpiceMerchant:40.7%63.2%
Pillage:40.7%60.3%
Rats:40.5%46.5%
Oasis:40.4%56.2%
Spy:40.3%53.1%
SilkRoad:40.2%43.3%
Philosopher'sStone:39.3%53.1%
SecretChamber:38.8%50%
Forager:38.7%52%
Forge:38.2%57.6%
Jester:38%59.4%
NobleBrigand:37.7%47.3%
Talisman:37.5%53.3%
Transmute:36%60.9%
Saboteur:35.9%50.9%
Thief:35.7%38.9%
Scout:35.6%62.9%
University:33.1%41.1%
Coppersmith:32.5%54.2%
Tribute:31.1%54.1%
PirateShip:24.3%46.4%
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Throwaway_bicycling

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Re: More data mining: Card "strength"
« Reply #43 on: January 31, 2015, 09:19:47 pm »
+2

Okay, so this might be getting interesting. First, I will note that there are *no* cards where the Top 20 have a lower win rate than everybody when they are the only buyer.

But there are some cards where they do appear to (in some cases grossly) underperform when they are the only buyer, which makes these potential "trap" cards. Unfortunately, there is an important confound in the data here present also in the dataset provided: the Top 20 play a very different set of people than the population at large. If the Top 20 were to play the same mix of people that the population played, their win rate on average would be *much* higher. So although below there are columns for Everybody, Top 20, and the difference between them, the two performance columns really aren't directly comparable and so their difference is a bit suspect, too. But I think it is reasonable to point out that if there are cards where Top 20 players achieve a win rate less than 0.500 against any competition (even or particularly just each other), than this should give one pause, for sure.
Card                All    Top 20  Diff

Thief                0.357 0.389 0.032
University           0.331 0.411 0.080
SilkRoad             0.402 0.433 0.031
Cache                0.425 0.464 0.039
PirateShip           0.243 0.464 0.221
Rats                 0.405 0.465 0.060
NobleBrigand         0.377 0.473 0.096

So for the above cards, something was almost certainly wrong with your strategy if you were the only buyer, no matter who you were. The only card here where there is really strong evidence of vastly superior use by stronger players is...Pirate Ship! Apparently still very frequently a mistake overall to buy it, but the Elite almost scrape back to even when they buy it. More could be gleaned, but not by me tonight.
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Merudo

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Re: More data mining: Card "strength"
« Reply #44 on: February 01, 2015, 01:44:07 am »
0

I'm surprised how well Scout, Transmute & Adventurer can be according to this last list.

Then again, I always believed Adventurer can be amazing on some boards :).
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Awaclus

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Re: More data mining: Card "strength"
« Reply #45 on: February 01, 2015, 03:52:09 am »
0

My winrate in Urchin mirrors is 63%, guess I'm just very lucky when it comes to colliding them!

Is that higher or lower than your overall winrate?
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Rabid

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Re: More data mining: Card "strength"
« Reply #46 on: February 01, 2015, 07:23:11 am »
+2

SilkRoad             0.402 0.433 0.031

I think this will be because if Silk Road is good it can be mirrored.
Or at least a few will be denied.
So a lot of the time if you are the only player to buy one, it was a late game $4 hand that you wish was a duchy.
« Last Edit: February 01, 2015, 07:27:02 am by Rabid »
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WanderingWinder

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Re: More data mining: Card "strength"
« Reply #47 on: February 01, 2015, 07:54:33 am »
+2

My winrate in Urchin mirrors is 63%, guess I'm just very lucky when it comes to colliding them!

Is that higher or lower than your overall winrate?
It's lower by about 5%. The thing you have to realize, though, is that just because a card is swingy doesn't mean there can't also be some skill. Clearly there is some skill with the card, it's not 'roll a die, if you get higher you win'. We had the same discussions with Tournament (though I think Urchin is worse). And SCSN deals with the card better.

Actually, I think the argument SCSN should be making isn't that Urchin isn't swingy, it's Mic_qsenoch's common point that everything is swingy. And he's right. I just think the Urchin is a bit more swingy, because it makes a pretty big difference and, importantly, you're very close to 50% hit rate on that first shuffle, which gives you close to maximum percentage to the two players having significantly different outcomes by turn 5.

SilkRoad             0.402 0.433 0.031

I think this will be because if Silk Road is good it can be mirrored.
Or at least a few will be denied.
So a lot of the time if you are the only player to buy one, it was a late game $4 hand that you wish was a duchy.

The thing about SR in high-level games is, it's a card you often go to if you're way behind. "I'm very far behind - if I'm going to win, it will have to go long enough for SR to be good (better than duchy anyway), so SR it is". Desperation moves are going to look bad, even if they may up your winrate in the situation you get them.

TheExpressicist

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Re: More data mining: Card "strength"
« Reply #48 on: February 01, 2015, 08:21:51 am »
+1

Quote from: Wandering Winder
The thing about SR in high-level games is, it's a card you often go to if you're way behind. "I'm very far behind - if I'm going to win, it will have to go long enough for SR to be good (better than duchy anyway), so SR it is". Desperation moves are going to look bad, even if they may up your winrate in the situation you get them.

Yes, this. I've been trying to think up a way to account for this. Something I'm considering is establishing an arbitrary turn limit, like, only counting cardS purchased before turn 10 or something. I *think* this should sufficiently account for deliberate strategies, and weed out ad hoc desperation tactics. Thoughts?
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Awaclus

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Re: More data mining: Card "strength"
« Reply #49 on: February 01, 2015, 08:33:18 am »
0

It's lower by about 5%. The thing you have to realize, though, is that just because a card is swingy doesn't mean there can't also be some skill. Clearly there is some skill with the card, it's not 'roll a die, if you get higher you win'. We had the same discussions with Tournament (though I think Urchin is worse). And SCSN deals with the card better.

Well, I don't think Urchin itself is a very difficult card, but trashing and hand size attacks usually make skill-intensive strategies better.
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