Polymarket’s reported trading activity can be overstated when analysts add together every OrderFilled event, according to a Paradigm analysis. The problem is not that individual events contain false information: the contracts record both sides of the same economic activity, and summing those records counts it twice.
For anyone using trading volume to compare prediction markets or assess platform fundamentals, the distinction matters. Before drawing conclusions from activity, the measurement must distinguish contracts traded from dollars exchanged—and count each trade only once.
Original publication: December 9, 2025, at 02:34 UTC+08:00. This article summarizes the findings and dashboard status reported at that time.
How one trade produces duplicate records
Paradigm examined Polymarket’s market structure, Polygon event data and the code of its CTF and NegRisk CTF exchange contracts. It concluded that most Polymarket analyses and dashboards were unintentionally double-counting volume.
In the transaction structure described by the research, each Polygon transaction contains at most one group of matched orders, with exactly one taker and at least one maker. The events appear in three stages:
- Maker-focused
OrderFilledevents: One for each maker involved, describing that maker’s portion of the transaction. - One taker-focused
OrderFilledevent: Describing the entire set of fills. Itsmakerfield identifies the overall taker, while itstakerfield identifies the exchange contract. - One
OrdersMatchedevent: Carrying the same filled amounts as the taker-focused event.
The second stage is another representation of the trades already recorded in the first—not an additional transaction with the exchange.
The contracts route tokens, carry out any required split or merge operations, and distribute funds and fees. They do not supply capital, take positions or assume the counterparty’s risk. Consequently, counting their routing role as another trade adds activity that did not occur.
A simple sale of YES tokens for $4.13, for example, becomes $8.26 of reported volume if both sides’ OrderFilled records are added together.
Why cash flows can differ between counterparties
Removing redundant records is only part of the accounting problem. Polymarket can match orders across YES and NO orderbooks, so not every match is a conventional token-for-USDC swap.
Its paired outcome tokens support two operations:
- Split: Exchange $1 for one YES token and one NO token.
- Merge: Exchange one YES token and one NO token for $1.
A conventional swap transfers an existing position between participants and leaves open interest unchanged. A split creates opposing positions and increases open interest; a merge closes opposing positions and decreases it.
In a split, both participants contribute USDC. In a merge, both receive USDC. Their dollar amounts can differ even when the numbers of outcome contracts are equal.
A transaction that illustrates the difference
Paradigm examined a two-leg transaction in which a taker sold YES shares for a total of $90:
| Leg | Taker’s exchange | Maker’s exchange |
|---|---|---|
| Swap | 3,157.02 YES tokens for $28.41 | $28.41 for 3,157.02 YES tokens |
| Merge | 6,842.98 YES tokens for $61.59 | 6,842.98 NO tokens for $6,781.39 |
In the swap leg, both participants experienced identical cash-flow volume. In the merge leg, the contract counts matched, but their cash flows differed substantially.
Adding all OrderFilled records produces 20,000 contracts and $6,899.80 of USDC volume. That combines maker and taker measurements rather than selecting a consistent, one-sided measure. The example also shows why a correction cannot assume every individual transaction’s dollar volume should simply be halved.
Two volume measures, different meanings
Paradigm distinguishes two commonly used metrics:
- Notional volume: The number of contracts traded, counted once. For splits and merges, this is the number of contracts split or merged.
- Cash-flow volume: The dollar amount exchanged at execution. For a conventional swap, this is contracts traded multiplied by the share price.
For split and merge trades, cash-flow volume requires an explicit convention. Maker-side cash flow, taker-side cash flow, their average, or another approximation such as share-priced volume can give different answers for an individual trade.
Paradigm does not insist on one universal cash-flow convention. Its historical comparisons show that maker-side, taker-side and share-priced measures tend to converge over days or months, each producing approximately half the aggregate OrderFilled sum. That is an aggregate observation, not a guarantee for every transaction.
The accompanying simulator uses the YES price and number of contracts as inputs. It assumes zero fees and a NO price equal to $1 minus the YES price. The research also supplies 32 historical examples—four for each of eight trade types—from both exchange contracts.
How the research separates maker and taker activity
For taker-side volume, Paradigm filters OrderFilled events whose taker field equals either exchange address:
- CTF:
0x4bfb41d5b3570defd03c39a9a4d8de6bd8b8982e - NegRisk:
0xc5d563a36ae78145c45a50134d48a1215220f80a
Maker-side volume uses events whose taker field is neither address. Analysts can then calculate the relevant contract or USDC amounts within the selected set, rather than combining both representations.
What the finding does—and does not—establish
The analysis concerns raw trading-volume measurement, not wash trading or another classification of trading quality. Correcting duplicate records does not, by itself, establish how much activity is organic.
Its immediate relevance is comparability: a volume-based assessment needs a consistent definition across platforms before the activity figures can support further conclusions.
At publication, Paradigm reported that DefiLlama, Allium, Blockworks and others were updating their dashboards to remove double-counting. That statement reflects the source’s reporting at the time, not an independent check of their current implementations.
Disclosure: Paradigm is an investor in Kalshi, a competitor to Polymarket.
Original source: Paradigm — “Polymarket Volume Is Being Double-Counted”.