You are more likely to see a sheep on the cover of a board game box than you are to see a group of women. —Erin Ryan, of the Cardboard Republic
I used this Iron Viz as an excuse to explore some data I’ve been meaning to work with for a long time. A friend of mine shared this article on Gender Representation in Board Game Cover Art a few months ago, and I’ve been looking at my games slightly differently ever since.
Of course, while the gender stat is somewhat shocking – and it only gets worse for people of color – few people are interested in buying a game simply for the fact that it features a woman on the cover. A lot of the follow-up discussions we’ve had has been about representation more broadly – Do I have any games by female designers? How do I find more stuff created by women?
And finding games you might enjoy is enough of a challenge in and of itself! There are thousands of new games published every year and while Board Game Geek can be a helpful reference, the proliferation of titles like “Top Game of [unit of time],” “help me find a game,” “2-players my wife will enjoy?,” and “Masterpost of [game type] games!” speak to the difficulty of using it as a recommendation tool.
In this Tableau visualization, I have experimented with using visual analytics to inform and guide board game selection. Selecting games you know and enjoy at the top (or the top left on desktop) will give you an overview of some of the game designers and game mechanics you enjoy, as well as the ability to see how many of the selected games fall into the various bins of game length and number of players. Each of these categories works as a filter, so you can see which of your games are by a particular designer (are they the really good ones or the kinda meh ones?) or quickly narrow down your options for board game night based on the games available, how many people you have, and the time commitment they’re willing to invest.
As you scroll, you pass a few visualizations that range from informative to comical on the gender representation of your game library. I did quite a bit of digging into the depths of the Board Game Geek website to find how and where women were involved in the back end of game design. I wanted to paint a slightly more nuanced picture of the industry, and to give people the tools to explore that nuance for themselves.
In the middle of the dashboard – whichever device you use – you find the radar chart overview. Earlier this year, Edward Kung did a Principal Components Analysis of Board Game Geek rankings and identified four “genes” that mark particular kinds of players. He shared the top 10 positive and negative indicators for each category on his blog, which I applied to the list of games I had compiled to build a high-level overview of the selected games. My visual encoding choice was directly informed by Kung’s original, here, but I also wanted it to have the look and feel of a personality test, which tells you about yourself in a way that you can (theoretically) use to inform your decisions going forward. The graph on the left (“Your Results”) shows the result of the selections and filters that were applied based on your original knowledge and input; the graph on the right (“Selected Game(s)”) gives you an overview of the new recommendations so you can assess the fit (the theory being that it’s a lot easier to compare one shape to another shape than to remember the intersecting sets and filters that inform a recommendation!).
At the bottom – or the right side of the screen on desktop – you can use the information you’ve learned (or already knew) to find new games. Selecting mechanics on this side applies an intersection filter; a selection of “Co-operative games” and “Bluffing” will show you only games that have both mechanics, rather than all co-operative games and all bluffing games. The same filters for designer; number of players; length of game are available here, to minimize the scrolling.
As this was a mobile contest, I wanted to limit the need for filtering as much as possible. While the initial input on both sides is fairly user/filter-intensive, the rest of the interaction is all done through dashboard actions and calculations (…I had to figure out LOD Expressions for this!). In case the number of games or the length of the filter was still too intimidating, I’ve provided a few pre-selected lists as buttons underneath so you can get a feel for how it works before tediously checking and unchecking a preferences list.
There are some major limitations to this dashboard as a recommendation tool. I’m still disappointed that I could not figure out a way to turn the selection filter at the top into an exclusion filter at the bottom. Because of that, there’s really no way to prevent games you already know and like from appearing as recommendations. While I imagine that makes the preference analysis seem more accurate, it’s can be pretty frustrating if you’re really searching for something new.
There is also no weighting of your selection – every game you select factors evenly into the analysis below. You may kinda like one game and LOVE another, but all of the “Top” categories are determined by number of games that fall into the group, not the strength of preference.
Still want to check it out despite the limitations? Check it out by clicking here or on the image below!
Other Board Game Recommenders
Don’t like RecommEngine? That’s fine! we’re sad to see you go, but here are some other tools that might be more to your liking:
- /u/boardgamerecommender https://www.reddit.com/r/boardgamerecommender/comments/3eafay/the_new_home_of_uboardgamerecommender/
- Choose Your Own Adventure recommender: https://www.boardgamegeek.com/geeklist/22619/optimum-game-selection-tool and 2.0: https://www.boardgamegeek.com/geeklist/70179/optimum-game-selection-tool-v20
- Board Game geek “ReplaceThisWithYourUserID”: https://boardgamegeek.com/user/ReplaceThisWithYourUserID/recommendations
- Taxonomy of Board Games tool: https://www.boardgamegeek.com/geeklist/58098/taxonomy-board-games-part-4-examples-and-recommend
Tools and Data
While the final dataset required a lot of hand-compiling and curation, the following tools and sources were essential for inspiration, technique, and methodology:
- Board Game Geek: https://boardgamegeek.com/
- bgg2pdf: http://bgg2pdf.com/
- Ludometrica: http://www.ludometrica.org/gamer-genotypes-pca/
- Cardboard Republic: http://www.cardboardrepublic.com/articles/extra-pieces/gender-representation-in-board-game-cover-art
- Cardboard Republic Gender Representation data: https://docs.google.com/spreadsheets/d/11P3lxUldy9slqAPFz0Wag-n-ZClY-_1NyDTg9RvnpRs/edit?usp=sharing
- ThaWeatherman BGG Data scrape: https://raw.githubusercontent.com/ThaWeatherman/scrapers/master/boardgamegeek/games.csv
- Brunel BGG data scrape: http://brunel.mybluemix.net/sample_data/BGG%20Top%202000%20Games.csv
Finally, special thanks to everyone who tested the dashboard, gave me feature suggestions and game suggestions, links to compelling articles, and generally kept me playing board games all these years: Matt, Ryan, Brie, other Ryan, Chloe, Andy, Noah, Jared, Brandon, Keith, Cole…it takes a village – which incidentally looks like a fun game we should try 🙂