LeagueBot: A Voice LLM Companion of Cognitive and Emotional Support for Novice Players in Competitive Games

TL;DR

This paper presents LeagueBot, a voice-based large language model designed to support novice players in competitive games by providing informational and emotional assistance, thereby reducing challenges and psychological stress during gameplay.

Contribution

Introduces LeagueBot, a novel voice LLM chatbot that offers real-time cognitive and emotional support to novice players in competitive gaming environments.

Findings

LeagueBot reduces perceived tension and gameplay challenges.

Participants reported improved access to game information and emotional relief.

LeagueBot demonstrates potential for real-time support in high-pressure contexts.

Abstract

Competitive games pose steep learning curves and strong social pressures, often discouraging novice players and limiting sustained engagement. To address these challenges, this study introduces LeagueBot, a large language model-based voice chatbot designed to provide both informational and emotional support during live gameplay in league of legends, one of the most competitive multiplayer online battle arena games. In a within-subjects experiment with 33 novice players, LeagueBot was found to reduce cognitive challenge, performative challenge, and perceived tension. Qualitative analysis further identified three themes: enhanced access to game information, relief from cognitive burden, and practical limitations. Participants noted that LeagueBot offered context-appropriate guidance and emotional support, helping ease the steep learning curve and psychological pressures of competitive gaming. Together, these findings underscore the potential of voice-based LLM companions to assist novice players in competitive environments and highlight their broader applicability for real-time support in other high-pressure contexts.