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lies, damned lies, and statistics; more fun with BGG URLs

June 18, 2011 Leave a comment

Thanks to Pelle Nillson, I now have a Python script that enables me to download BoardGameGeek game data using their XML API. I hope to do a number of posts based on this data in the near future, but I first wanted to correct a post I did recently.

In more BGG stats: fun with numbers, I shared a snapshot of a spreadsheet table listing the fifty games with the highest wanted in trade / offered for trade ratio in the BGG database. I included a caveat:

I didn’t go through the entire BGG database looking for the twenty games with the highest ratio, instead I assumed that they would all be in the top 100 games wanted in trade. And this might well be a bad assumption.

It turns out it was a terrible assumption. If you look at all games in the BGG database, the top twenty come out quite a bit differently:

So now, the top 10 include Julius Caesar, Hive: the Ladybug, Big Boss, Dominion: Cornucopia, K2, Railways of the Western US, Airlines Europe, Santorini, Olympus, and German Railways. And that’s quite a different list.

Sorry ’bout that….

To end this post on a more positive note, however, I’d like to share another little URL hack anyone can use to get at the data on BGG in a slightly nonstandard way.

In fun with BGG URLs, part III, I showed how it was possible to sort the games by number owned. Did you know it’s possible to do the same thing with just games in the family category? Just add “familygames/” before “browse/” in the URL above, and you get: Cool, huh? You can also do this for strategy games, for abstracts, for party games, and for wargames.

And if you don’t want to sort by number owned, you can also sort by other things, too: number wanting (sort=numwanting), number trading (sort=numtrading), number wishing for (sort=numwish), and pageviews (sort=views).

The general principle, here, is that you can add the type of game you’re looking for before “browse/” to limit the results you get.

Now I think that’s pretty neat. :-)


fun with BGG URLs, part III (and an update on El Chupacabra)

June 5, 2011 Leave a comment

First up is a URL that takes you to a bunch of different ways to rank the games on BGG: My favorites here are sorting by number owned, by number wanted in trade, by number that users have put on their wishlist, and by the total number of pageviews. I was hoping to find a way to break down the number of views by year, to get an idea of when games were generating a lot of interest, but multiple attempts at URL hacking went exactly nowhere.

What I’d really like to do is come up with a relational analysis of all the games in, say, the top 200. Analyze the “recommends” data on each game, for example, to find links between games based on common ownership. Or find a way to do it based on “people who play / rate highly game x also play / rate highly game y.” In other words, first find out which games are “connected” to one another, then present this data graphically. If anyone has any ideas or suggestions for how to go about this (without losing what sanity I have), I’d love to hear them. I suspect that BGG’s xml api might be the way to go, but after an initial assessment of its features, I don’t quite see how. Again, though, I’d welcome any and all suggestions — enlighten me!

Since this relational analysis appears to be beyond me (for the moment), I’ll have to content myself with sharing something much more mundane: the ability to search BGG’s database for games of a particular weight, sorted in pretty much any way you want.

This, for example, looks at all the games with a weight between 1.8 and 2.0 (fairly light, includes both Carcassonne and Ticket to Ride) and sorts them by the number of people who rated the game:  And yes, it’s ugly — but the important thing is that it works.

Now for a little URL hacking:  change the 1.8 to 2.0 and the 2.0 to 2.2: This does the same search, only it bumps the weight up a little bit — this list includes Citadels, Alhambra, and 7 Wonders.

If you want to look at slightly heavier games again, then change the 2.0 to 2.2 and the 2.2 to 2.4 (this’ll get you games like Dominion, Pandemic, and Settlers of Catan). While you’re at it, change the “numvoters” to “rank” to sort the resulting games by their BGG ranking: Or change “rank” to “numowned” to sort by the number of BGG users who own the game: Easy, huh?

I’ve always thought it should be easier to get at some of this info, but it’s nothing a little URL hacking can’t take care of. :-)

And, as promised, an update on El Chupacabra. Those who have been following my blog know that the game didn’t work as well with 7 as I had hoped, so I went back to the drawing board to come up with something a little different. I decided that the opportunity to “shoot the moon” offered by the role of El Chupacabra just wasn’t interesting enough to justify its overhead in terms of rules complexity, and I also decided that the mechanism just didn’t fit very well with the push-your-luck gameplay. So I took it out.

I’ve been thinking for some time that it would be fun to design a game that encourages people to cheat, or at the very least encourages people to call one another cheaters. The first step, then, was to check to see if that name had been taken, and sadly, it had: Cheater. I always hate it when a poorly-rated game is taking up a perfectly good name, but what do you do? I mean, aside from turning your copy of Cheater into a perfectly serviceable version of The Bottle Imp.

Naming concerns aside (I can’t decide between Russian Rollette and Cheater’s Dice), I decided to gut the original game, take out all the fussy bits having to do with scoring, and make it a betting and bluffing game pure and simple. Think of it as a dice version of Bullshit (a.k.a. I Doubt It / Cheat) with gambling thrown in. It’ll fall most definitely into the Beer & Pretzels category of gaming….

More anon.

fun with BGG URLs, part II

June 4, 2011 1 comment

Okay, so I’ve been playing a bit more with the “plays” data on BGG. I went through and looked at the top 20 games from the years 2003 to 2010, sorted by the number of unique players. In other words, which games had the most unique players each year?

When I tried to track each game until it fell out of the top 100, all I got was this rather uninteresting and fairly linear mess:

I then decided to take a page out of László K‘s book and just include the top twenty games each year. The graph is both more interesting and more readable:

So what is this exactly? Take a look at 2003: there should be 20 games along that line. The ones that take up the most vertical space had the most unique players that year. Same for all the other years. If a game persists across the entire graph (quite an achievement), this means that the number of unique players for that game has been in the top 20 on BGG from 2003 to 2010.

Looking at the number of unique players of a game gives you an idea of its popularity; if a game remains popular for a long time, it’s probably a fairly good game.

So what games stand out? Ticket to Ride, Settlers of Catan, Puerto Rico, Power Grid, Lost Cities, Citadels, Carcassonne, and Bohnanza. But look also at the big impact Agricola, Dominion, Pandemic, and Race for the Galaxy have had.

Some years you get a bunch of new games cracking the top twenty; other years it all stays pretty much the same. 2004 saw the introduction of both TtR and Power Grid, while 2008 saw the introduction of both Stone Age and “the big four” above.

fun with BGG URLs, part I

June 2, 2011 2 comments

Okay, so I was having a bit of fun on BGG today, trying to figure out how to get at some of all their awesome data. I mean, yes, you can pretty easily sort by rank, or the number of voters, etc., but did you know you can sort by number of owners? Or by number of people who have the game on their wishlist? By the number of people who want a game in trade?

Anyway, I got to playing around a bit with their stats, specifically the number of plays each game has. And I found something interesting: ignoring the number of plays (since this data can be easily corrupted), you can sort by the number of unique users who played the game. Here’s a link that lists all the games in their database, sorted by the number of unique users who have played the game: Pretty cool, huh? Who knew that Carcassonne would have the most unique players, followed by Dominion, Agricola, Puerto Rico, and The Settlers of Catan?

Here’s where it gets really interesting, though: you can limit the time-frame you’re looking at, so you get just the number of unique users who played the game, say, in the year 2000.

You can tell where I’m going with this, can’t you?

First, a link or two: if you want to see how many unique users played Settlers of Catan in, say, 2000, just click here. And you can obviously do a little url hacking to change the year from 2000 to 2001 (that’s easier than picking a new range of dates with their chooser and then choosing to sort by number of unique users, though you can do it that way, too).

And you can go through and do this for 2000, 2001, 2002, all the way up to 2010. What do you get when you do all that?

You get a bunch of web pages, that’s what. But if you look at the top ten games of each year, some interesting trends emerge. And if you look at every game that hits the top ten in that period (there are 34), tracking it until it no longer cracks the top 100, you get a rather interesting little graph. But one that’s very hard to read:

A couple things to note: first, each game is just stacked on top of the next. Second, this looks an awfully lot like exponential growth, at least up until 2010. This might represent the growth of the hobby, but more likely it’s just the growth in BGG users / users who record their plays. Third, I’m not sure why things tail off for 2010 — probably it’s just that fewer players recorded their plays that year (for whatever reason).

Playing with it a little, you can “normalize” the graph by converting all the numbers to percents. Here all that dramatic growth goes away, replaced by an easier-to-read graph where each game gets a slice of 100%:

A caveat: of course there are a number of things that are suspect with this data. First, the number of users on BGG has been increasing a lot. Second, not all users record their plays. Third, there are an unknown but possibly large number of shill accounts. And so on.

Still, I think this is fairly interesting. It gives a pretty good idea as to what the big (popular) names in gaming are, and it does so in an easy-to-read way.

I’d upload the spreadsheet I made so other people can play with the data, too, but WordPress appears to be unwilling to allow me to post an ODS file. ODT, yes, but not ODS. Anyway, I can try to figure something out if folks are interested. Just let me know.