Here we introduce the idea of using heuristics models in predictive mobile game analytics. Heuristics models are simple rules-sets that we construct based on machine learning-driven analysis, but which once developed can be fielded inside a game client. Heuristics models thus address part of the problem of enabling small companies to access frugal but effective prediction models…
Esports is computer games played in a competitive environment. As for any other type of sports competition, players and teams seek to improve their behavior to optimize their results. Thus, esports analytics is a new area identifying successful strategies and evaluating game play for computer games. Besides helping the players, esports analytics is also directed…
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.
As part of an on-going project on exploring player behavior via the Steam platform (see e.g. here and here) we decided to run a quick correlation analysis across games on Steam, focusing on sales (game ownership) and a two different aggregate review/ranking scores. In addition, we wanted to explore if review scores correlated with the actual amount of time people spend playing games on Steam.
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…
In the past few years university-based researchers have published a substantial amount of explorative work on MMORPG economies – the most complex virtual economic system that exists in games. In this post we take a quick look at some of the interesting research papers from the hallowed halls of academia and beyond. Virtual economies are…
Game Analytics Resources 