In modern game development, it is crucial that we can place our players into sets of groups, where everyone in those groups shares specific traits. Without being able to do this, our ability to understand who the players are, and how they play our games, is hampered. The ability to profile the players is important…
The game industry has access to detailed data about how players are interacting with games. The data can come from a variety of channels are often high-dimensional, time-dependent and potentially very large. Profiling users has emerged across multiple data science application areas as a way of managing complex user data, and to discover underlying patterns in the…
Given a huge and varied game like Destiny, it is of interest to see if there are any patterns in how people play the game. There can be a variety of reasons for this – for developers the focus can be on monitoring the players and checking no group emerges that has issues progressing, gaining…
Kyle Polich from the Data Skeptic Podcast has released a cast on game analytics, featuring various ramblings from yours truly about analytics, games, challenges and the many opportunities in the field. Get it from iTunes, Stitcher or Direct from the web. Big thanks to the Data Skeptic Podcast team.
5 billion hours of play. 6 million players. 3000 games on Steam. 1 distribution model that explains how time spent playing games on Steam rises and falls – as a function of time. This has powerful implications: if playtime follows a specific distribution, we can predict it. This post was written by Anders Drachen, Rafet…
In this fourth and last post in the cluster analysis series, we provide a couple of examples showing how cluster analysis operates in practice on player data, as well as how to present the results of cluster analysis, in order to make them actionable. Grab a cup of coffee and sit down in a comfy…
In the previous post of this series we introduced the theoretical foundations of cluster analysis and the various categories of algorithms. In this post we take a specific look at the challenges associated with running a cluster analysis on behavioral telemetry from games. Clustering behavioral data from games does not involve any unique challenges: the…
[This post was written in collaboration with Christian Bauckhage and Rafet Sifa.] Clustering is imminently useful for finding patterns in gameplay data. In this second post in the clustering series, we briefly outline several classes of algorithms and discuss the types of contexts they are useful in. Cluster algorithms can be categorized based on how the…
In this – somewhat wordy – post, we introduce the foundations of cluster analysis, and discuss its application in finding patterns in the behaviors of players, and developing profiles of how people play your game. Recent years have seen a deluge of behavioral data from players hitting the game industry. The reasons for the data…
One of the most important challenges in game analytics is to take the power of quantitative analysis and place it into the hands of everyone, not just trained analysts. In this post we describe the process of developing a method for generating behavioral profiles of player, and visualize how they over time migrate between these…
Game Analytics Resources 