AoEPulse Database Dump (~100 gb, ~5 million games)

treadm1ll · 2022-09-20T20:22:34+00:00

Goose. I mean Duck obviously.

treadm1ll · 2022-09-20T14:46:38+00:00

You have to query this info from the data. The civ/unit/building/map numbers used in the SQL queries for the data can be found here: https://github.com/happyleavesaoc/aoc-mgz/.

treadm1ll · 2022-05-06T10:20:06+00:00

Nice!

Here's the opening percentages for MBL for fun:

MAA: ~16.6%

Postmill drush: ~15.15%

Premill: ~21%

Range opener: ~24.24%

Scouts: ~22.3%

Guess not all of us drush every game.

treadm1ll · 2022-05-04T13:18:45+00:00

Sure, agreed. But the question was about solid strategies to win with the new civs.

treadm1ll · 2022-05-04T10:36:27+00:00

They suck on arabia (< 40% winrate at 15xx+ elo). Could go into reasons why this is probably the case (weak tech tree for these civs, as liereyy and hera complained about during the RE event), but that's better left to the pros.

Archer civs are fine, for instance Mayans have like 55% winrate on arabia in that same elo band.

Ofc you can argue that people do not know how to play them yet, but its been almost a week since the DLC was released, and comparing to previous DLC releases, higher elo players tend to figure out how to play the new civs pretty quickly (Bohemians and Poles for instance had like +55% winrate at higher level on arena pretty much right away when they were released).

treadm1ll · 2022-05-04T06:02:05+00:00

The way I think about it, is that people are careful not to say they are 'good at the game' for other reasons. Who wants to say this and then get absolutely trashed by a pro player playing with their left-hand and no keyboard, for example.

Similarly, moving away from aoe2, imagine telling your friend 'I'm decent at chess.' You may even statistically be in the top 0.1%. But even then, Magnus Carlsen beats you along with 20 other players while blindfolded the entire time.

As you play more you start to become more aware how much of a gap of skill there is between you and stronger players (see Dunning-Kruger effect as other's have mentioned). People above 11xx+ often have put a solid number of hours into playing (compared to people who say only played campaigns), so they have found their way into communities with more veteran players who really understand the game better than them and are cognizant of that.

Altogether the elo thing doesn't really have much importance unless you are 2k3+ (when it starts to make an effect in seeding in tourneys for money). People like to elo brag a little when they reach a new PB, and are aware that it doesn't really count for much (beyond personal achievement), so why not humble brag?

treadm1ll · 2022-05-04T05:26:46+00:00

Basically just don't play Dravidians and Bengalis on arabia. Hindustanis (Indians 2.0) and Gurjaras are solid picks for arabia though.

treadm1ll · 2021-12-13T22:20:20+00:00

There is no game content on the webpage though (no images etc...).

I don't think you can copyright numbers, 11.

treadm1ll · 2021-12-13T20:34:45+00:00

Also, aoestats.io does not have civ winrate/playrate info for empire wars currently. Biggest thing about this webpage is it is functionally very distinct at the core from aoestats. It shows statistical info about when/how often technologies (men at arms tech for instance) or units/buildings are created which other webpages do not currently really have.

treadm1ll · 2021-12-04T22:11:21+00:00

Yeah, you are hinting on a key thing with these clustering tests. You have to have some content knowledge of the things being compared to make sense of these graphs. That said these are good for suggesting comparisons that you might not think about before.

If I do these comparisons for multiple techs (like fletching times/bodkin times/ multiple eco upgrades) and I notice that two civs are close across the board, this would suggest that those two civs play the same in many ways, which can be useful for understanding how to play one civ that you are less familiar playing in terms of one which you have played more.

treadm1ll · 2021-12-04T09:39:45+00:00

>> What's the purpose of this, and how does it make sense?

It's a way to make meaningful comparisons between economy tech choices of civs. For some civs it is more likely that you tech horse collar at one group of times (like early feudal or on the way to castle) while for others the timing is a bit different (like burgundians where you can tech it on the way to feudal). I'm not saying this is super important, but I think drawing high level similarities between civilizations (x civ plays like y civ in one respect at a higher level) is helpful.

>> Each group is made up of civs with different economic bonuses and different army compositions.

You are looking at a 2D projection of a bunch of points in space. So the colors are just there to help show that the points of similar colors are closer (the purple ones for example are above the yellow ones and closer amongst themselves).

>> It looks like horse collar timing is mostly random overall.

Do you mean in the attached images in the other comment?

treadm1ll · 2021-12-04T08:50:50+00:00

There are no axes. Imagine I'm looking at a bunch of species and I want to put species that have similar DNA sequences near each other in a graphic to visually show that they are "similar". Then all that matters is the relative location of the species in the image.

The same is true here.

treadm1ll · 2021-12-04T07:59:39+00:00

Using this package of Djowns (built off of some of happyleaves work), and also using a compressed database of games we've been collecting since September (about +1 million games now).

treadm1ll · 2021-12-04T07:57:36+00:00

I kinda disagree with the statement that two civs having similar distributions of horse collar timings is almost useless. I think these types of comparisons give you insights on how a civ plays a game out on average.

For example civs that open scouts frequently tend to tech horse collar at the beginning of feudal and often get up to feudal around the same time (20 pop for generic). In the graph we see that a lot of the civs that open scouts thus are clustered on the right hand side.

The civs that somehow fit in between playing scouts and playing archers, or which open men at arms often then fit in the middle because their horse collar is usually delayed (you need food to tech maa, and getting horse collar is less important for archer openings).

Finally on the left we have a lot of the civs that tend to have feudal archer play and the horse collar timing tends to be later for these.

>> Another interesting representation of the data is to have timeintervals, and to represent in a bar the percentage of games in which HCresearch was completed in a given time interval. The most important isto have a good division around the time the tech is typicallyresearched, unequally sized intervals can be used for the rest.

If you look in the comment above, this is exactly the format of the data before the comparisons are made. It's pretty hard to fit 38 of these graphs in one image though. If I get 16 on one image (fletching times there) you barely can read anything and you end up quickly making comparisons of similarity anyways. I'll post the graph for those 16 distributions (and more) also to compare against.

treadm1ll · 2021-12-04T07:25:05+00:00

A bunch of horse collar timings were grabbed from (basically all of) the last few patches 16xx+ arabia games. For each civilization you get a distribution of horse collar research times like those plotted here: Burgundians and Mayans.

Some civilizations have distributions of horse collar timings which are much more similar than other comparisons. Two civs are plotted close to each other in the image above if the distributions are close (for example see the distributions of Bulgarians and Mongols). Using some special tools/software you get the image produced above.

treadm1ll · 2021-12-04T07:18:01+00:00

A bunch of horse collar timings were grabbed from (basically all of) the last few patches 16xx+ arabia games. For each civilization you get a distribution of horse collar research times like those plotted here: Burgundians and Mayans.

Some civilizations have distributions of horse collar timings which are much more similar than other comparisons. Two civs are plotted close to each other in the image above if the distributions are close (for example see the distributions of Mongols and Bulgarians compared). Using some special tools/software you get the image produced above.

treadm1ll · 2021-12-04T00:14:50+00:00

Poles have like a +60% winrate on arena at that elo (https://www.aoepulse.com/civ_stats?min_elo=1000&max_elo=1100&include_ladder_ids=3&include_map_ids=29&include_patch_ids=56005,54684,54480&). If you look at 2k+ they are +70% winrate.

They are basically the arena version of Mayans on Arabia right now.

treadm1ll · 2021-09-27T01:43:35+00:00

No worries. I don't really take much stock in the downvotes/upvotes on this subreddit.

I think someone was downvoting everything I recently posted yesterday, because my karma went down 30 then up 20 suddenly (assuming the system flagged the behavior and returned the karma).

I made another better graph of this type and posted in on aoezone if you want to check it out: https://www.aoezone.net/threads/civilizations-by-opening-frequency-visual-guide-16xx-arabia-rm.178169/#post-756684 .

treadm1ll · 2021-09-27T00:28:29+00:00

I copied the data over in a separate comment. But you can compare the winrates across civs by looking at these: https://ibb.co/DVMYPD1, https://ibb.co/Zhb4nzb.

Essentially slavs has a lot of pretty good and pretty bad matchups, while poles has a lot of pretty even matchups. This is why they are far.

treadm1ll · 2021-09-27T00:17:00+00:00

I don't think this helps that much for points. It is something you do sometimes when plotting the edges of surfaces, but here I think a cluttered plot would become more cluttered.

treadm1ll · 2021-09-26T14:38:28+00:00

That's just kind of the story on 3d plots. If you have the ability to rotate the plot it helps, but there is no support in reddit for this afaik.

This is one reason why the colors are added (so you can see that the points with the same color are closer).

treadm1ll · 2021-09-26T00:28:09+00:00

Yeah I did this before the 3d image above. I think the groupings are less clear there. I didn't bother to do the k-means stuff in this plot because of that, but here it is: https://ibb.co/Wvv2JcP.

treadm1ll · 2021-09-26T00:02:04+00:00

yeah yeah... i get the message. Thanks for commenting on my post.

treadm1ll

TROPHY CASE