Keynote

A/B Testing Incorrectly

Nick Ross

The Meta

Summary: Experimentation is one of the most powerful tools that data scientists and analysts have to optimize games. In this talk we will cover a few different failure modes and ways to avoid them. Using real world examples and situations, we will deep dive into these traps, describe why they are problematic and provide you with the means to diagnose and correct for them. Specific focus will be on issues such as estimating the difference between experimental conditions and interference.

Bio: Nick Ross is director of data science and backend services at The Meta, an esports training platform for millions of competitive gamers. Before joining The Meta Nick was a professor of Data Science at the University of San Francisco where his research focused on how to effectively use data and data science techniques to answer business questions. Previously he spearheaded the data efforts at Sega and TinyCo (acquired by Jam City).

Tutorial

Applying Neural Networks into Game Analytics

Alan Pedrassoli Chitayat

IGGI - Computer Science Department, University of York

Summary: Neural networks have gained vast academic interest due to its ability to take any shape, thus being very flexible and powerful to assist in solving complex problems. While areas such as AI and pattern recognition have been utilising NNs extensively, not much work has been done in the field of game analytics. This tutorial explores different ways in which NN can be implemented, to both aid and enhance techniques typically utilised within game analytics. Covering the fundamentals of neural network design and implementation as well as an interactive demonstration of how to apply NN to existing game analytics workflows. This tutorial aims to equip attendees with experience of how to utilize these techniques alongside their existing studies within the field. Furthermore, this tutorial aims at ways in which to enhance existing studies to highlight the applied potential of game analytics and relevant studies.

Bio: Alan studies player decision making within esport titles such as Dota 2 and CS:GO. Alan's research focuses on explaining and predicting player intent within a live context. Through his industry experience, Alan has worked to both implement and cater to the research and development of many features within the game analytics and pattern recognition fields. Alan also has experience in applying machine learning techniques, including neural networks, to commercial products such as the ESL Weavr companion app.

Talk

Game Data Science - Introduction

Anders Drachen

IGGI - Computer Science Department, University of York

Summary: The interactive entertainment industry has grown dramatically in the past decade, and recently projected to reach 200 billion USD in global yearly revenue, making it one of the super-heavyweight sectors in entertainment. Estimates place the number of people worldwide who currently play computer games at 2.6 billion. Tracking detailed interaction behaviour from this number of people results in truly massive datasets. With the rapid growth and innovation in the sector, data has come to the forefront as a means for informing decision making. This has in turn spurred the evolution of the domain of Game Data Science - a cross-disciplinary area which merges perspectives from multiple academic domains to help the Creative Industries make sense - and use - of the rapidly growing data space. Given the constant changes in games, the people who play them and the communities that support them, data from games tend to be volatile, requiring that they be acted on rapidly. In addition to supporting the industry, the data from video games and gamified applications has permitted Game Data Science to target a broad variety of research questions, from exploring human behaviour to developing new algorithms for real-time analytics. Game Data Science has had a direct impact on the interactive entertainment industry within the past few years, as the practice of tracking and analysing the behaviour of players and processes has emerged as a key component of game development in this age of mobile platforms, increased game persistence and non-retail-based revenue models.

Bio: Anders Drachen is recognized as one of the world’s most influential people in business intelligence in the Creative Industries, and a core innovator in the domain. His work has assisted major international game publishers, as well as SMEs, make better decisions based on their data. He currently serves as Professor at the Department of Computer Science, University of York. He is the Lead Analyst of the UKRI Audience of the Future Demonstrator Weavr. which is building new data-driven audience experiences across esports and sports. He is also the manager of the Arena Research Cluster, an international research network focused on innovation in esports and sports. His award-winning research has seen world-wide media coverage, and his books have seen hundreds of thousands of downloads, forming standard works of reference in game data science and games user research. In his private life, he writes books for children about technology and economics.

Paper Presentation

Applying Rapid Crowdsourced Playtesting to a Human Computation Game

Pratheep Paranthaman

Computer Science Department at Elon University

Summary: Player engagement and task effectiveness are crucial factors in human computation games. However, collecting data and making design changes towards these goals can be time-consuming. In this work, we incorporate rapid crowdsourced playtesting via the ARAPID (As Rapid As Possible Iterative Design) system to iterate on the design of a human computation platformer game. For each level in the game, the player’s goal is to collect items relevant to a given scenario while avoiding irrelevant items. We extended the visualization modules in the existing ARAPID system to include a multi-level data visualization and item collection task effectiveness plot. A designer from the project team used the system to iterate on the game’s level design, with the goal of increasing relevant and decreasing irrelevant items collected by players. A large-scale test with the game versions created during the iterative analysis found that the designer was able to use ARAPID to improve the specified goal parameters.

Bio: Dr. Pratheep Kumar Paranthaman is an Assistant Professor of Computer Science at Elon University. Dr. Paranthaman is currently overseeing the Game Design Minor Program in the computer science department. Dr. Paranthaman earned his Ph.D. from the University of Genoa, Italy. During his Ph.D. research phase, he investigated the impact of Serious Games in the automotive sector, and he was also associated with an Industrial European Union (EU–FP7) project on safe and collaborative transportation. Dr. Paranthaman’s research interests include immersive technologies, Games User Research, human-computation games, and artificial intelligence. Prior to joining Elon, Dr. Paranthaman worked as a Postdoctoral Researcher and Lecturer at Northeastern University.

Authors: Pratheep Kumar Paranthaman (Elon University), Anurag Sarkar (Northeastern University), Seth Cooper (Northeastern University)

Demonstration

Fireballs and Lightning: Visualising Esports Experiences

Anders Drachen

IGGI - Computer Science Department, University of York

Summary: In the 25 bn esports industry, data is king. With detailed data from every single match being played across all levels of skill, covering uncounted hundreds of thousands of years of playtime, there is no bottom in the ocean of data that we can analyse and visualise. The availability of data, the digital nature of the games, the technical infrastructure and the surrounding young audiences has led esports to become a rapidly innovating sector, which is constantly striving to invent new ways of engaging audiences. More than half a billion people play esports games regularly, and the audiences are young, technologically in the forefront and keen to be involved in the experience, as opposed to traditional one-size-fits-all sports broadcasting. They are the audience of the future, and esports has become a testbed for new entertainment technologies, with companies launching new initiatives on a daily basis. Jointly, this has launched esports as the fastest growing entertainment sector worldwide. On this exciting background, the UKRI/Innovate UK Demonstrator project Weavr was launched in 2019 as a collaboration between seven companies and the University of York. Weavr has since its inception launched data-driven, interactive and personalised audience-facing experienced across mobile platforms, VR, AR, 2nd screen, and other formats, all utilising data from esports matches to tell stories with data. 27 million views and 2 million users later, Weavr is ready to present some experiences from the project and highlight the potential impact of data visualization in esports.

Bio: Anders Drachen is recognized as one of the world’s most influential people in business intelligence in the Creative Industries, and a core innovator in the domain. His work has assisted major international game publishers, as well as SMEs, make better decisions based on their data. He currently serves as Professor at the Department of Computer Science, University of York. He is the Lead Analyst of the UKRI Audience of the Future Demonstrator Weavr. which is building new data-driven audience experiences across esports and sports. He is also the manager of the Arena Research Cluster, an international research network focused on innovation in esports and sports. His award-winning research has seen world-wide media coverage, and his books have seen hundreds of thousands of downloads, forming standard works of reference in game data science and games user research. In his private life, he writes books for children about technology and economics.