Balancing gameplay of aRPG using player behavioral patterns
summary
Indie studio harvests event logs from playtests, applies process mining and an extended fuzzy gameplay miner to extract player behavioral patterns, computes metrics (frequency, routing, proximity) and filters edges to expose overpowered loops. Iterative redesigns shrink dominant transitions and produce a more even skill graph; simulation bots recreate player runs with roughly 60–75% action match and live alpha/beta tests reach about 100,000 unique players. Method runs on self-built telemetry and produces measurable balance changes across solo and 2–4 player modes.
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chapters (13)
- 0:00Start
- 3:27Game Balancing
- 6:56Game Mechanics
- 9:07Cooperative Combos
- 12:35General Thoughts
- 14:32Process Mining
- 17:53The Gameplay Event Logs
- 23:01The Binary Frequency Sequence
- 23:51Routing Significance
- 24:45Proximity Correlation
- 25:23Metrics of Activity Type
- 29:36Edge Filtering
- 38:30Combat Accuracy
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