On Stake’s staging RGS, /play isn’t meant to be a perfect statistical mirror of your full book.
It’s primarily there to validate integration and flow, not distribution accuracy.
In staging, the engine can apply sampling shortcuts, caching, or reduced RNG cycles to keep things fast and predictable.
That can make outcomes feel clustered around certain math paths, especially over small to medium sample sizes.
Your full 1M dataset should be reachable in theory, but you should not expect uniform coverage or true long-run variance behavior in staging.
That only really stabilizes in production-grade runs or dedicated math simulations.
If you want to test feel and balance, rely on your own simulator, not /play responses alone.
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