Evaluate card grading ROI with probabilities instead of best-case prices.

Identify the exact raw card, its current condition, the intended grading company and service level, and the realistic alternative if it is not submitted. The alternative may be selling raw now or continuing to hold the card.

ROI is useful only when both paths use the same cost basis and comparable time horizon.

For each plausible grade, use recent exact-card sales and subtract marketplace fees, payment fees, and outbound shipping. Do not mix asking prices with completed-sale evidence. Exclude outcomes that a condition review makes implausible.

Document the comp window, sample count, identity match, and valuation date. Thin evidence should reduce confidence.

Assign a probability to every modeled outcome, including a lower-than-expected result when it is plausible. Probabilities must total 100%. Multiply each outcome’s net proceeds by its probability, then add the results.

Expected grading profit equals probability-weighted proceeds minus the complete card and submission cost. Expected ROI divides that profit by the complete amount invested.

Compare expected grading profit with the raw alternative, then require a margin of safety for uncertainty, turnaround time, and capital at risk. Recalculate after reducing sale prices, increasing fees, or shifting probability toward a lower grade.

A model that qualifies only under optimistic assumptions is a watchlist candidate, not a confident submission. This methodology supports decisions; it does not predict a grade or guarantee a return.