OP Simulation Engine

Can the ecosystem sustain itself while staying profitable?

A Discrete Event Simulation of the OwnPiece pack-opening economy. Every deposit, pull, buyback and restock is an event that mutates inventory, wallet liability, buyback reserve and cash. Tune the model, run thousands of customers, and read the five answers that matter.

Set your model on the left and press Run simulation.
The dashboard answers five questions: profitability, buyback solvency, inventory adequacy, bottleneck classes, and capital required.
Illustrative defaults These are starting assumptions for exploring the modelnot OwnPiece's actual figures. The preset is deliberately conservative; adjust every input to your real numbers before reading anything into the output.

What the Advanced Model adds

A time-stepped, concurrent-population simulation over a calendar horizon. Customers arrive over time, hold persistent store-credit wallets, and can redeem at the same time — including a configurable bank-run shock. It adds the full operating cost stack, moving card prices, the three real pack tiers, inventory aging, and a sensitivity tornado. Read the full Model Notes →

Set the model on the left and press Run advanced model.
The dashboard shows real P&L with costs, liquidity over time (with the redemption shock visible), survival vs break, price attribution, inventory aging, the Monte Carlo pass rate, and the sensitivity tornado.

About these two models

This tool ships two simulators of the same OwnPiece pack-opening business — customers deposit, buy a mystery pack, reveal a card by odds, then keep it or sell it back for store credit. They answer different questions.

Base Model

Establishes the core economics: house edge, inventory depletion by rarity, which card classes bottleneck first, and gross profitability. It runs customers one at a time, which keeps the unit economics clean and easy to verify — but by construction it cannot show liquidity risk (each customer always funds their own withdrawals), it counts only the house's take (not operating costs), and it assumes card prices never move. Trust its inventory and profitability signals; treat its capital and return figures as an illustrative upper bound.

Advanced Model

Built to pressure-test the things the Base Model assumes away — the failure modes that actually decide whether a business like this survives:

1. Concurrent redemption (the bank-run test). Customers across the whole population hold store credit and can cash out at the same time, including a configurable redemption-shock event. This is the real risk: cash is tied up in inventory while many holders redeem at once. The model shows when liquidity runs short and how large a reserve actually protects you.

2. The full cost stack. Customer acquisition, operating expense, payment processing, minting/gas, vault storage, and shipping/insurance on physical redemptions — so margin and return are real numbers, not just the house edge.

3. Card prices move. Listed values drift and fluctuate over time, which turns the buyback promise into a price-risk obligation: a fixed-percentage buyback is effectively a guarantee written against a moving market. The model shows the exposure.

It also adds the three real pack tiers (Rookie / All-Star / Pro), inventory aging, and a sensitivity view that ranks which assumptions move the outcome most.

How to read it

The Base Model tells you whether the unit economics work. The Advanced Model tells you whether the business is survivable and fundable once real-world frictions and concurrent customer behaviour are in play. Every input is adjustable — the defaults are illustrative starting points, not OwnPiece's actual figures.

Out of scope — and one real-world flag

Secondary marketplace / royalties, $COLT token economics, the KYC flow, and real database integration are out of scope for this simulator. Regulatory and gambling-licensing analysis is also out of scope — but note it is a genuine business risk for a pack-opening (gacha) product, and should be assessed separately. It is flagged here deliberately; it is not a simulation parameter.

OP Simulation Engine · client-side DES · Monte Carlo runs in a Web Worker · Base Model (v1) + Advanced Model (v2)