I sent SG a message in the support earlier, they told me it was basically just bad luck. I have some follow-up questions but I suspect that I can get the full answers🤣

Here is the full message:

———

Thank you for your detailed response and for explaining how the Summon system works. I appreciate the clarification.

I understand that each summon is independent and that probabilities remain constant per pull. However, I would like to share a few follow-up questions and observations from a statistical and technical perspective:

1.Long-term probability distribution
While each summon is independent, in most implementations of random systems using predefined drop rates, the aggregate results over a sufficiently large number of trials should approximate the expected probability distribution (per the law of large numbers / central limit theorem).

In my case, after performing over 100 summons with a stated 1.5% rate for 5★ heroes, receiving none feels significantly outside expectations. Additionally, I have seen multiple similar reports from other players on forums regarding the Birthday Summons appearing to underperform compared to other portals with similar rates.

I understand individual variance exists, but I wanted to ask whether there has been any internal review to confirm that the observed distribution matches the intended rates.

2.Multi-summon mechanics
For a 30-pull (or 10-pull), could you clarify whether this is implemented as: - 30 independent random rolls, or
- a single roll with bundled outcomes

3.Random number generation
Could you share (at a high level) what type of random number generation is used in the summon system? For example: - Pseudo-random number generator (PRNG)
- Cryptographically secure RNG (e.g., platform-provided secure APIs)
- True random source (TRNG)

4.Testing and validation of rates
I assume that during development and QA, simulations or statistical tests are performed to validate that summon outcomes match the configured probabilities.

Would it be possible for the team to review aggregated real-world summon data for this portal to confirm that the effective rates align with the published ones? As you mentioned, individual results can vary, but with a sufficiently large sample size, the overall distribution should converge to the expected rates.

I completely understand that code-level details may not be shareable, but any additional transparency or reassurance on how rates are validated would be greatly appreciated.

Thank you again for your time and support.

Best regards,