Less is More: : Analysing Communication in Teams of Strangers

Teamwork is challenging in cooperative digital games, especially between strangers. In many online cooperative games, teams have a short-lived existence and ever-changing membership. Our study explores how short-lived, ad hoc teams of strangers communicate and investigate its effect on team performance. We use the commercial cooperative digital game, Portal 2 and analyse 2256 text message instances produced by teams during a 45-minute interaction. Our findings show that team communication is negatively related to performance, and affects performance over and beyond prior experience. A content analysis shows that teams generally have higher task-related communication than socio-emotional communication. This pattern is consistent throughout the duration of the interaction period. The results are discussed in the context of previous research on team communication and performance, and we draw parallels with communication patterns in real-world groups such as aviation crews

DAX: Data-Driven Audience Experiences in Esports

Esports(competitivevideogames)havegrownintoaglobalphenomenon with over 450m viewers and a 1.5bn USD market. Esports broadcasts follow a similar structure to traditional sports. However, due to their virtual nature, a large and detailed amount data is available about in-game actions not currently accessible in traditional sport. This provides an opportunity to incorporate novel insights about complex aspects of gameplay into the audience experience – enabling more in-depth coverage for experienced viewers, and increased accessibility for newcomers. Previous research has only explored a limited range of ways data could be incorporated into esports viewing (e.g. data visualizations post-match) and only a few studies have investigated how the presentation of statistics impacts spectators’ experiences and viewing behaviors. We present Weavr, a companion app that allows audiences to consume datadriven insights during and around esports broadcasts. We report on deployments at two major tournaments, that provide ecologically valid findings about how the app’s features were experienced by audiences and their impact on viewing behavior. We discuss implications for the design of second-screen apps for live esports events, and for traditional sports as similar data becomes available for them via improved tracking technologies

Wait, But Why? Assessing Behavior Explanation Strategies for Real-Time Strategy Games

Work in AI-based explanation systems has uncovered an interesting contradiction: people prefer and learn best from 'why' explanations but expert esports commentators primarily answer 'what' questions when explaining complex behavior in real-time strategy games. Three possible explanations for this contradiction are: 1.) broadcast audiences are well-informed and do not need 'why' explanations; 2.) consuming 'why' explanations in real-time is too cognitively demanding for audiences; or 3.) producing live 'why' explanations is too difficult for commentators. We answer this open question by investigating the effects of explanation types and presentation modalities on audience recall and cognitive load in the context of an esports broadcast. We recruit 131 Dota 2 players and split them into three groups: the first group views a Dota 2 broadcast, the second group has the addition of an interactive map that provides 'what' explanations, and the final group receives the interactive map with detailed 'why' explanations. We find that participants who receive short interactive text prompts that provide 'what' explanations outperform the other two groups on a multiple-choice recall task. We also find that participants who receive detailed 'why' explanations submit the highest reports of cognitive load. Our evidence supports the conclusion that informed audiences benefit from explanations but do not have the cognitive resources to process 'why' answers in real-time. It also supports the conclusion that stacked explanation interventions across different modalities, like audio, interactivity, and text, can aid real-time comprehension when attention resources are limited. Together, our results indicate that interactive multimedia interfaces can be leveraged to quickly guide attention and provide low-cost explanations to improve intelligibility when time is too scarce for cognitively demanding 'why' explanations

Metagaming and metagames in Esports

The metagame is a convoluted term with no unified definition despite its importance and its common occurrence across different fields such as game design and behavioural economics. In our paper we provide a unified and compact definition of the term metagame and metagaming by firstly highlighting their historical evolution. Although, the metagame meant multiple things such as the environment surrounding the game, it has come to mean a perceived optimal or dominant playing strategy that is usually popular with an esport at that specific point in time. "Metagaming" as a verb is distinct and refers to a number of ways a player can affect the outcome of a game that are external to the game’s environment. We focus on how these terms crystallised in the world of digital entertainment (esports) by providing multiple examples of metagames and metagaming in competitive settings. Finally, we provide a theoretical framework on the life cycles of metagames as well general guidelines of understanding the current metagame of LoL and Dota 2. We conclude that by understanding and cataloguing the highly fluctuating metagame(s) of an esport at specific points in time, researchers will gain a historical context of that game’s space which in turn will give them insight into the decision making of professional esports players along with a possible future understanding of how the game will progress

Role Identification for Accurate Analysis in Dota 2

Esports is an organised form of video games played competitively. The esports industry has grown rapidly in recent years, with global audiences estimated at the hundreds of millions. One of the most popular esports formats is the Multi-Player Online Battle Arena (MOBA), which sees two teams of players competing. In MOBAs and other team-based games, individual players take on different roles or functions to help achieve victory for their team. MOBA characters can be played in different ways to align with team roles. However, most current esports analytics systems do not separate the data, such that each role is analysed separately. This is a problem because it is difficult to evaluate the performance of different roles with the same metrics. For example in football goals scored is a great metric for striker performance, but a poor one for goalkeeper performance. Using Dota 2 as a case study, we propose a method using ensemble clustering to classify and label individual roles for each hero in Dota 2. Rather than focusing on pre-existing roles defined by expert knowledge, we allow unsupervised learning to identify roles which each hero can play in an unbiased way. This work enables the separation of historical data for each hero, enabling a more accurate analysis to be performed by analytical tools