Enhancing Battle Maps through Flow Graphs

So-called battle maps are an appropriate way to visually summarize the flow of battles as they happen in many team-based combat games. Such maps can be a valuable tool for retrospective analysis of battles for the purpose of training or for providing a summary representation for spectators. In this paper an extension to the battle map algorithm previously proposed by the author and which addresses a shortcoming in the depiction of troop movements is described. The extension does not require alteration of the original algorithm and can easily be added as an intermediate step before rendering. The extension is illustrated using gameplay data from the team-based multiplayer game World of Tanks.

[1]  Fei-Yue Wang,et al.  A Survey of Traffic Data Visualization , 2015, IEEE Transactions on Intelligent Transportation Systems.

[2]  Christopher Griffin,et al.  Data Visualization in Games , 2018 .

[3]  Jon Crowcroft,et al.  Group movement in World of Warcraft Battlegrounds , 2010, Int. J. Adv. Media Commun..

[4]  Katrien Verbert,et al.  Real-Time Dashboards to Support eSports Spectating , 2018, CHI PLAY.

[5]  Yves Jean,et al.  Visualization of sports using motion trajectories: providing insights into performance, style, and strategy , 2001, Proceedings Visualization, 2001. VIS '01..

[6]  P. Hanrahan,et al.  Flow map layout , 2005, IEEE Symposium on Information Visualization, 2005. INFOVIS 2005..

[7]  Christopher D. Shaw,et al.  Visualizing and understanding players' behavior in video games: discovering patterns and supporting aggregation and comparison , 2011, Sandbox '11.

[8]  Guenter Wallner Automatic generation of battle maps from replay data , 2018, Inf. Vis..

[9]  Andrew Vande Moere,et al.  Towards Classifying Visualization in Team Sports , 2006, International Conference on Computer Graphics, Imaging and Visualisation (CGIV'06).

[10]  Niklas Elmqvist,et al.  Toward Visualization for Games: Theory, Design Space, and Patterns , 2012, IEEE Transactions on Visualization and Computer Graphics.

[11]  Truong-Huy D. Nguyen,et al.  G-Player: Exploratory Visual Analytics for Accessible Knowledge Discovery , 2016, DiGRA/FDG.

[12]  Günter Wallner,et al.  Aggregated Visualization of Playtesting Data , 2019, CHI.

[13]  Simone Kriglstein,et al.  Visualizations for Retrospective Analysis of Battles in Team-based Combat Games: A User Study , 2016, CHI PLAY.

[14]  Günter Wallner,et al.  Visualization-based analysis of gameplay data - A review of literature , 2013, Entertain. Comput..

[15]  Gennady L. Andrienko,et al.  Spatio-temporal aggregation for visual analysis of movements , 2008, 2008 IEEE Symposium on Visual Analytics Science and Technology.

[16]  Sam Devlin,et al.  Narrative Bytes: Data-Driven Content Production in Esports , 2018, TVX.

[17]  Gennady L. Andrienko,et al.  Spatial Generalization and Aggregation of Massive Movement Data , 2011, IEEE Transactions on Visualization and Computer Graphics.