A brief introduction to Collaborative Filtering

Recommend.Games explained, part 1: how we recommend games to you

What is a good recommendation? Collaborative filtering is the workhorse powering the recommendations by Recommend.Games. Over the years, I’ve been asked every now and then how it works. So, I thought it’s high time I outlined the basic ideas behind our recommendation engine. Let’s first take a step back and talk about recommendations in general. What is it we’re trying to achieve? The answer to this question is far from trivial, and it gets harder when you want to formalise its goals. [Read More]

The world of board games

Board game rankings by country

BoardGameGeek (BGG) users can select their country of residence in their profile. The main purpose is to find other users in your region to play face to face or maybe trade games, but but over here at Recommend.Games we obviously cannot help ourselves but to use this information for some interesting statistics. 🤓 Let’s start with the usual disclaimer: We will have to rely on whatever information BGG provides. In particular, users can freely choose their country. [Read More]

Has board game rating inequality increased over the years?

Applying the Gini coefficient to BoardGameGeek ratings

The number of ratings per game Perhaps one of the most controversial choices of the Shut Up & Sit Down Effect article was using the number of ratings1 on BoardGameGeek (BGG) as proxy for “attention” to a game. So let’s double down on that! 😈 If lots of ratings mean a lots of eyes on a game, we can ask questions like: What games get most of the attention? Do few games steal the spotlight? [Read More]

Reverse engineering the BoardGameGeek ranking – Part 2!

This is the second part of a series explaining and analysing the BoardGameGeek rankings. Read the first part here. Last time I left you with the nice result that BoardGameGeek (BGG) calculates its ranking by taking users’ ratings for a particular game and then add around 1500-1600 dummy ratings of 5.5. This so-called geek score is used to sort the games from best (Gloomhaven) to worst (Tic-Tac-Toe). One detail however we touched on in passing, but did not resolve, is how that number of dummy ratings develop over time. [Read More]

Reverse engineering the BoardGameGeek ranking

TL;DR: BoardGameGeek calculates its ranking by adding around 1500-1600 dummy ratings of 5.5 to the regular users’ ratings. They called it their geek score, statisticians call it a Bayesian average. We use this knowledge to calculate some alternative rankings. I often describe BoardGameGeek (BGG) as “the Internet Movie Database (IMDb) for games”. Much like its cinematic counterpart, the biggest board game database not only collects all sorts of information obsessively, but also allows users to rate games on a scale from 1 (awful - defies game description) to 10 (outstanding - will always enjoy playing). [Read More]