Visualizing event sequence game data to understand player's skill growth through behavior complexity

Wei Li (Corresponding author), Mathias Funk, Quan Li, Aarnout Brombacher

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)
139 Downloads (Pure)


Analysis of game data is used to study player behavior. For puzzle based games where solutions are usually defined by their action sequences, player behavior can also be studied by their solution complexity. In this paper, we present a visualization system to help learning expert to understand how actions, timing and the resulting strategy change with regard to the solution complexity. To establish a novel perspective into the patterns not only in action choices but also in behavior complexity, we designed an interactive, customized line chart to track how complexity and performance change at each stage of skill acquisition. Specialized glyph system (Strategy Signature) is implemented to find strategy differences easily with simple visual cues. Contextual information can be explored by switching the view modes to see potential links between complexity and raw attributes. Evaluation with expert users shows that the system effectively reduced their time and effort in finding interesting sub-groups and gave them unexplored angles of behavior complexity to contemplate player’s skill growth. In summary, this paper illustrates a visualization approach to enable analysis into the subtleties of behavior complexity in video games.
Original languageEnglish
Pages (from-to)833–850
Number of pages18
JournalJournal of Visualization
Issue number4
Publication statusPublished - 1 Aug 2019


  • Application
  • Event sequence
  • Game visualization
  • Information theory


Dive into the research topics of 'Visualizing event sequence game data to understand player's skill growth through behavior complexity'. Together they form a unique fingerprint.

Cite this