Game Data

How might we analyse the big data exhausts of games to support game developers and understand people inside and outside of games?

Project areas include:

  • Imitation Learning: Using game data from human players we can build AI opponents and team-mates to enhance multi-player games.

  • Comparative Analysis of Games: By comparing data across different games, developers can understand key factors underlying game genres or mechanics, leading to more successful future game designs.

  • Social Dynamics in Games: Studying data from multiplayer games can uncover fascinating insights about social dynamics and cooperation/competition among players.

  • Game Economics: In games with virtual economies, tracking and analysing economic data can help maintain balanced economies, which is crucial for player satisfaction and the longevity of the game.

iGGi People relevant to this Theme:

Dr Nick Ballou

  • iGGi Alum
  • Player Research, Game Data
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Dr Ignacio Castro

  • Supervisor
  • Game AI, Applied Games, Player Research, Game Data
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Prof. Anders Drachen

  • Supervisor
  • Player Research, Design & Development, Game Data, Esports
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Dr Miles Hansard

  • Supervisor
  • Game AI, Immersive Technology, Design & Development, Game Data
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Prof. Paul Cairns

  • Supervisor
  • Applied Games, Player Research, Accessibility, Game Data
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Dr Tom Collins

  • Supervisor
  • Game AI, Game Audio, Game Data, Player Research, Esports
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Dr Dan Franks

Yu-Jhen Hsu

Steph Carter

  • iGGi PG Researcher
  • Available for placement
  • Applied Games, Design & Development, Player Research, Accessibility, Game Data
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Dan Cooke

  • iGGi PG Researcher
  • Available for placement
  • Esports, Game Data, Player Research
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Dr Jeremy Gow

  • Supervisor
  • Game AI, Creative Computing, Design & Development, Game Data
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Dr Patrik Huber

  • Supervisor
  • Applied Games, Game Data, Immersive Technology, Player Research, Esports
  • Read More

iGGi Publications relevant to this Theme:

Beyond the Spotlight: Co-Designing AI for Theatre Audience Communication

A Pedrassoli Chitayat, S Carter, BA Robertson, J Hook
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems

Cost-Effective Attention Mechanisms for Low Resource Settings: Necessity & Sufficiency of Linear Transformations

P Hosseini, M Hosseini, I Castro, M Purver
arXiv preprint arXiv:2403.01643, 2025

AI vs. the Algorithm: Measuring success on Twitch

AP Chitayat
2025 IEEE Conference on Games (CoG), 1-8, 2025

Foundation Models as World Models: A Foundational Study in Text-Based GridWorlds

R Sasso, M Conserva, D Jeurissen, P Rauber
arXiv preprint arXiv:2509.15915, 2025

Archaeological Gameworld Affordances: A Grounded Theory of How Players Interpret Environmental Storytelling

F Smith Nicholls, M Cook
CHI '25: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, Yokohama, Japan, Article no 465, p. 1 - 20

CG-TTRL: Context-Guided Test-Time Reinforcement Learning for On-Device Large Language Models

P Hosseini, O Bohdal, T Ceritli, I Castro, M Purver, M Ozay, U Michieli
arXiv preprint arXiv:2511.06430, 2025