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OPEN METHODOLOGY

Every recommendation is traceable to the math.

The tool is a pre-screening and financial-modeling aid. It does not authenticate a card, issue a grade, appraise market value or provide investment advice.

Money strategy

All money is stored as integer cents. Percentages and grade probabilities are integer basis points, where 10,000 equals 100%. Percentage fees round once to the nearest cent.

Sale proceeds

fee base = sale price + applicable buyer shipping + applicable handling + applicable sales tax

marketplace fee = percentage fee + per-order fee + promoted fee + other marketplace costs

net proceeds = sale price + buyer shipping + handling − marketplace fee − seller shipping

Raw and graded profit

raw profit = raw net proceeds − acquisition cost

outcome profit = graded net proceeds − acquisition cost − allocated grading costs

expected graded profit = Σ(outcome profit × outcome probability)

incremental expected value = expected graded profit − raw profit

The break-even sale price is found with an integer-cents binary search against the complete marketplace fee function. The break-even grade is the lowest-price modeled outcome with nonnegative profit; labels never control the calculation.

Total profit versus from today forward

Total-profit view includes acquisition cost. When a card is already owned, from-today-forward view treats that purchase as sunk for displayed profit. The acquisition cost remains visible, and the raw-versus-grade incremental comparison remains mathematically consistent.

Recommendation thresholds

A strong candidate currently requires at least $50 of incremental expected value, at least 80% input completeness, non-low probability confidence and a loss probability inside the selected risk tolerance. A potential candidate requires at least $20 and a modestly wider loss band. Negative incremental value favors the raw-sale scenario or more research. These thresholds are site-defined, configurable and not industry standards.

Probability and uncertainty

Outcome probabilities must total exactly 100.00%. Preset controls are clearly labeled editable examples. Sensitivity rows lower top-grade probability, sale values, fee assumptions and grading costs so the recommendation is not driven by the best case.

Limits