TactiVis: Towards Better Understanding of Team-based Combat Tactics

Keywords

Team-based combat, storyline visualization, MOBA games, tactic analysis.

Abstract

Team-based combat scenarios are prevalent in various real-world applications like video gaming. Analyzing tactics in these scenarios is essential for gaining insights into game processes and improving combat behaviors. The decision-making data in team-based combat include character actions, movement trajectories, and event sequences. Existing studies face challenges in visualizing and analyzing combat tactics due to the complexity and the multifaceted characteristics of the decision-making data. To address these challenges, we introduce TactiVis, a visual analytics system designed for analyzing combat decision-making behavior. Using MOBA game as a representative case of team-based combat, TactiVis adopts a macro-to-micro tactics visual analytics framework consisting of three stages: match-level analysis, event-level understanding, and character-level comparison. In the TactiVis system, we introduce the v-storyline visualization, which encodes positions along the vertical axis to reveal tactical patterns. Case studies and a usability study demonstrate the utility and usability of TactiVis for helping analysts understand combat patterns and analyze tactics.