Visualising player data for video game designers

The collection and analysis of videogame players' actions in the game world, known asgame telemetry, is a common technique for understanding the behaviour of players. Thisprocess, known as Game Analytics, often uses data visualisation to allow designers tomanually analyse features of the data. Heatmap visualisation, a grid-based visualisationshowing how often an event occurs across the game world (e.g. ?ring of weapons), isused widely in the games industry for visualising aggregated data, but has limitationswhen used to classify player behaviour at an individual or group level. Existing worksusing clustering to identify player behaviour yield results that must be interpreted by anexpert, a problem acknowledged by existing research. Motivated by these limitations,this work presents the novel application of dendrogram visualisation as a means tointerpret large datasets of heatmaps, through the use of hierarchical clustering, to aiddesigners in exploring and analysing player behaviour. This allows an intuitive and well-understood visualisation technique (heatmaps) to be used for cluster analysis, presentingintelligible results to a game designer, in a format they are familiar with.To evaluate dendrograms as a design tool, a system was designed and implemented tovisualise player data, using heatmaps, with hierarchical clustering being performed onthese heatmaps, the results displayed as a dendrogram. A feasibility study was con-ducted with a set of game designers, to understand the opportunities and limitationsof dendrograms as a game analytics tool. The results a?rmed the utility of heatmapsfor visualising aggregate data, but visual complexity increases in large quantities. Den-drograms were found to be initially di?cult to read, but showed promise for analysinglarge sets of data and guiding the designer to interesting areas of the data, providedthey could \drill down into the base data (heatmaps). In light of these ?ndings, a us-ability study was designed and conducted with a set of 40 game development students,where they were presented with realistic game design scenarios, and asked to ?nd an-swers to analytics questions using heatmaps and dendrograms. The results showed thatwhilst dendrograms were initially di?cult to understand, they were used to successfullyexplore and understand cluster relationships, with participants providing the correctanswers grounded in the data. Furthermore participants reiterated the need to explorethe base data (heatmaps) to understand the cluster relationships of the dendrogram.This work concludes that dendrograms represent a viable and useful tool for identifyinginteresting behaviour patterns within a heatmap dataset. Whilst some familiarity isrequired with the tool, it is possible to use dendrograms to explore behaviour clusterswithin a large dataset, and this work presents a solution to the limitations of analysingplayer behaviour through the use of heatmaps in large datasets. This work highlightsa number of avenues for future work, such as deploying and studying dendrograms in agame production setting, or evaluating the dendrogram visualisation in di?erent gamegenres.