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Gameplay Analysis through State Projection

This study explores the intricacies of player behavior in gaming using data-driven approaches. By utilizing state projection techniques, the researchers investigate player confusion, strategies, and design flaws within games. The authors apply statistical methods, including surveys and in-game statistics, to mine extensive gameplay data from popular titles like Halo 3. The findings aim to unveil patterns in player interactions and dynamics, enhancing our understanding of player experience and guiding future game design improvements.

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Gameplay Analysis through State Projection

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  1. Gameplay Analysis through State Projection 1 Center for Game Science Department of Computer Science University of Washington Erik Andersen1, Yun-En Liu1, Ethan Apter1, François Boucher-Genesse2, Zoran Popović1 2Department of Education • Université du Québec à Montréal FDG 2010 June 21st, 2010

  2. We want to know how people play

  3. We want to know how people play

  4. We want to know how people play ?

  5. We want to find…

  6. We want to find… • Player confusion

  7. We want to find… • Player confusion • Player strategies

  8. We want to find… • Player confusion • Player strategies • Design flaws

  9. Patterns in data SELECT * FROM replays WHERE location=x AND time>y AND attempt>3 AND death=“grenade”…

  10. Patterns in data SELECT * FROM replays WHERE location=x AND time>y AND attempt>3 AND death=“grenade”… Confusion? Strategies?

  11. Traditional Playtesting

  12. Statistical Methods • Surveys • In-game statistics

  13. Statistical Methods • Surveys • In-game statistics

  14. Visual Data Mining Lets people see patterns in data Bungie (Halo 3)

  15. Visual Data Mining Lets people see patterns in data • Dynamic information? Bungie (Halo 3)

  16. Visual Data Mining Lets people see patterns in data • Dynamic information? • Games with no map? Bungie (Halo 3)

  17. But what about?

  18. But what about?

  19. But what about?

  20. But what about?

  21. “Playtraces” Start Goal

  22. “Playtraces” Start Goal

  23. “Playtraces” Start Goal

  24. “Playtraces” Start Goal Confusion? Distance to goal

  25. Refraction

  26. Refraction • Massive educational data mining

  27. Classic Multidimensional Scaling • 2-D projection of points in high-dimensional space • Clusters game states based on some distance function

  28. State Distance

  29. State Distance

  30. State Distance

  31. State Distance

  32. Action Distance • da (s1, s2)

  33. State Distance Start Goal Confusion? Distance to goal

  34. Distance to Goal • dg (s1, s2) = abs(dg (s1, sg) - dg (s2, sg))

  35. Distance Functions Action distance Distance to goal Combined

  36. Refraction Distance Function • d (s1, s2) = (da (s1, s2) + dg (s1, s2)) / 2

  37. Playtracer Framework

  38. Easy level

  39. Difficult level

  40. Failure

  41. Chance To Win

  42. Chance To Win

  43. Evaluation

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