TCGplayer capped commission and Pro fees at $75 per item on February 10, 2026. Nobody has published real seller data on what that changed. This is the methodology we're committing to, and why we don't have a number yet.
We don't have the number yet. We're saying that up front instead of publishing a percentage that sounds precise but isn't, because a savings figure you can't trust is worse than no figure at all.
What we can tell you is what we're measuring, why Hoard is positioned to measure it, and the methodology we're committing to before a single result comes in. Writing the counting rules down first is what keeps a study like this from quietly bending toward whichever number looks best once someone's staring at it.
On February 10, 2026, TCGplayer capped commission and Pro fees at $75 per product, on top of the full TCGplayer fee stack this analysis is measuring. Under the 13.25% all-in Pro rate, that cap starts mattering once a card's price passes roughly $566 — the point where 8.95% commission plus 2.5% Pro fee would otherwise add up to more than $75. Above that price, the cap is what determines the fee, not the percentage.
TCGplayer has said publicly that it expects more than 95% of Direct sellers to see lower fees under its current structure. That's TCGplayer's own claim about its own program, and it covers Direct's separate fee restructure, not marketplace-wide commission specifically. Nobody outside TCGplayer has published a seller-data check on what the commission cap itself did to take-home pay on high-ticket cards. That's the gap this page is meant to close, once the underlying sample supports it.
Hoard tracks effective take-rate — fees as a percentage of sale price — across every TCGplayer store it monitors, for every order line, at the actual sale price. A single seller can look at their own high-ticket sales and eyeball whether fees feel lower since February. They can't tell whether that's the cap working as intended or ordinary month-to-month variance in what they happened to sell. Seeing the same measurement across many stores, before and after the same date, is what turns an anecdote into a study, and it's the part no single-store view can do on its own.
The study is not complete. This is the methodology as planned, not a set of findings:
All of it pulled from Hoard's own monitored seller base, once there's enough of it in the qualifying price band to publish responsibly.
We're publishing the counting rules before we look at the numbers. And we're committing to publish the result even if it shows the cap mattered less than expected, to Hoard's own assumptions or to TCGplayer's.
A study like this is only honest if it reflects the market, not a handful of large accounts that happen to sell expensive cards. We checked. Across Hoard's entire monitored seller base, only 6 distinct sellers have ever recorded a single order-item sale at or above the $566 commission-cap-relevant price point, totaling 141 line items, all-time, not yet split by date. A before-and-after comparison needs a meaningfully larger and date-segmented sample than 6 sellers to mean anything. Publishing a savings percentage from 6 stores would look authoritative while actually describing a handful of large accounts, not the market. That's not a stall tactic. It's the same trap a thin sample sets for any benchmark, and it's why this page states a sample size instead of a savings figure.
We'll update this page directly once the pool of qualifying sales is large enough to compute a real before-and-after comparison, rather than publish a separate announcement and leave this one stale. If you're citing the commission cap's effect for anything public, this is the page to watch, not the one to cite yet.
In the meantime, if you want to know whether your own sales cross the cap threshold today, the fee calculator gives you that answer on your own numbers, without waiting on the aggregate study. And the volatility this cap is patching over is structural: a percentage-based fee moves with every sale price, which is the exact problem Hoard's flat-fee model is built to avoid.
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