Maps have been an essential part of video games since their early days to help player orient themselves in game spaces. However, maps fulfil various purposes beyond pure navigation tasks. In this paper, we specifically focus on diegetic maps, and look at the dimensions of storytelling and wayfinding that emerged through a thematic analysis of posts about video game maps. Our analysis also shows that diegetic maps take on different forms, ranging from passive maps displayed on walls to ’physical’ maps and fully digital maps. We then reflect on how diegetic maps support different forms of immersion, in particular spatial, narrative, and emotional immersion. Next, we highlight the relevance of different map components and elements in influencing immersion. Together, these factors can support specific types of player experiences. Based on our findings, we propose that the immersion of diegetic maps should be examined and evaluated through a multifaceted view of this phenomenon.

As player demand for information about esports games surges, live companion tools were developed to help them understand game-related knowledge, make decisions, and review post-game data.Despite growing interest, little is currently known about how different users perceive and use commercially available apps and their different features.However, this is important for creating tools that actually meet players' needs.To help fill this gap, we selected two companion apps for two different competitive game genres and explored them with respect to four dimensions -understandability, informativeness, decision making, and trustworthiness -across professional and nonprofessional players.Towards this end, we first conducted an online survey to assess users' perception around these dimensions.This was followed by online interviews to gain further insights.Through statistical and thematic analysis, our results highlight commonalities and disparities in user behavior and preferences across user groups, contributing to our understanding and future design of live companion tools.

Interest in data-informed play has accelerated in recent years across player communities, particularly within the competitive gaming scene. As such research on analytics tools for players has concentrated predominantly on popular esports games and genres. However, such tools could be of interest to players of other genres as well given a general tendency for self-tracking. In this work we focus on Metroidvania games, studying a multi-view dashboard for visualizing gameplay data from Hollow Knight. Using an insight-based evaluation methodology and interviews with 12 participants we study 1) insights players infer from the dashboard and 2) use cases such a tool can enable within the context of Metroidvania games. Our results reveal that in addition to common performance-related use cases, participants found personal satisfaction when viewing the visualizations and considered them to be an opportunity for social engagement. Participants mostly used the map and events view to infer insights but also relied on recalled data and their existing familiarity with the game. Based on our findings we further reflect on future research directions. Through this we contribute to developing a broader understanding of computational support tools for players.

Data-informed play practices are starting to be embraced by different subgroups of the player population. In the wake of this, interest in data tracking and visualization tools is growing. Player-facing visualizations often take the form of aggregated performance statistics. However, map-based analytics for players are still being comparable less explored due to the rare availability of detailed behavioral and movement data. Nonetheless, navigation is central in many games, among them, Metroidvania-like games which emphasize exploration and discovery. In this paper, we introduce HKViz, which consists of 1) a modification for Hollow Knight—a popular Metroidvania—to track players’ in-game data and 2) a website offering a dashboard for data analysis. HKViz is intended to enable user research on player-centric map-based analytics. We further present preliminary user feedback and discuss potential extensions.

With the growth of competitive gaming and esports, training support tools that offer feedback on players’ performance to assist in skill development have witnessed increased demand. These tools increasingly not only provide prospective and retrospective analyses but also live feedback during gameplay itself. Thus, such ’live companions’ provide overarching training support across the different phases of play through a variety of features. To understand how these tools work, we carried out an analysis of the features offered by commercially available live companions. For our analysis, we selected 15 live companion tools for two popular competitive games, namely Valorant and League of Legends. These games are representatives of first person shooters and multiplayer online battle arena games. Based on our analysis, we provide an overview of the various features offered by such tools, how frequent these features are, and if there are differences between the two games. Finally, we reflect on potential future research directions for this emerging topic of study.

Players increasingly adopt a data-driven approach to review and improve their gaming skills. In the wake of this, spatio-temporal visualizations gained popularity but remain challenging to design. Storyline visualizations are unique in the way they integrate time and location information into a single view to show how entity relationships develop over time. We adopt the storyline visualization technique to summarize gameplay for the purpose of post-play review. We demonstrate the method by applying it to League of Legends matches and evaluated it with 39 players of the game in a task-based online study using the triad framework for spatio-temporal queries by Peuquet. Results indicate that players responded positively to the approach and could, by and large, solve tasks well but that time-based tasks proved most challenging and least efficient to solve. Based on our findings, we reflect on possibilities for enhancing the design of storyline visualizations for game-related data analysis.

Prior research has shown how ‘content preview tools’ improve speed and accuracy of user relevance judgements across different information retrieval tasks. This paper describes a novel user interface tool, the Content Flow Bar, designed to allow users to quickly identify relevant fragments within informational videos to facilitate browsing, through a cognitively augmented form of navigation. It achieves this by providing semantic “snippets” that enable the user to rapidly scan through video content. The tool provides visually-appealing pop-ups that appear in a time series bar at the bottom of each video, allowing to see in advance and at a glance how topics evolve in the content. We conducted a user study to evaluate how the tool changes the users search experience in video retrieval, as well as how it supports exploration and information seeking. The user questionnaire revealed that participants found the Content Flow Bar helpful and enjoyable for finding relevant information in videos. The interaction logs of the user study, where participants interacted with the tool for completing two informational tasks, showed that it holds promise for enhancing discoverability of content both across and within videos. This discovered potential could leverage a new generation of navigation tools in search and information retrieval.