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To check a stablecoin’s token concentration, identify the exact token deployment, retrieve its address balances for a dated snapshot, and compare the largest balances with a clearly defined on-chain supply denominator. Report the chain and contract or mint address alongside the ticker: the same stablecoin can have very different holder counts and concentration on different chains.
The result describes how tokens are distributed among addresses—not necessarily among individual owners. Exchanges, issuers, bridges, and protocol contracts may pool assets for many users, while a single entity may control multiple addresses. Treat holder counts and top-wallet shares as address-level measures, then examine what the largest wallets are and how the data provider labels them.
What token concentration measures—and what it cannot tell you
Token concentration is the share of a token deployment’s supply held by its largest addresses or by specified wallet categories. A common measure is the top-10 share: add the balances of the ten largest addresses, then divide by the selected supply denominator. You can calculate the same measure for the top address, top five, or top 100.
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Wallet distribution adds context to that percentage. It can include the number of addresses with balances, the share held in wallet-size bands, and the apparent roles of major addresses—for example, an exchange, issuer treasury, bridge, or lending protocol. Together, these measures are more informative than a holder count alone: a deployment can have millions of addresses while a small number of addresses still hold a substantial share of supply.
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These are address-level observations, not a census of people or beneficial owners. An exchange or custodian may hold tokens for many customers, and one person or organization may control multiple addresses. A high top-wallet share therefore does not by itself establish that a few individuals own that share, nor does a large holder count prove that ownership is broadly distributed.
Start with the exact token deployment
Before collecting balances, record four identifiers: the ticker, the chain, the official token contract or mint address, and the snapshot date and time. A ticker alone is not unique. A native deployment and a bridged representation can use similar names while having different contracts, supplies, and holder profiles.
Check the address against the issuer’s information or the relevant chain explorer. If you are comparing deployments, keep each chain-specific contract separate at first. Do not combine balances across chains or compare a chain-specific balance total with a supply figure that includes other deployments.
- Asset: ticker and token name.
- Deployment: chain and contract or mint address.
- Snapshot: date and time, including the time zone if available.
- Source: explorer, API, or dataset used to obtain the balances.
Retrieve balances for a dated snapshot
You can obtain holder balances from a chain explorer, a holder API, or an on-chain analytics dataset. The choice affects what you can reproduce: a holder endpoint may offer a ranked list and a total holder count, while an analytics dataset may provide historical snapshots, normalized fields, and optional wallet labels.
Use a holder list or API
Open the token’s holder view on the relevant chain explorer, or use an API that returns token holders. For example, HolderScan’s holders API documentation describes a ranked, paginated token-holder endpoint and a total holder count. Record the requested token address, chain, retrieval time, pagination settings, and any filters. Check whether the endpoint’s holder count includes every nonzero balance or applies a minimum balance threshold; do not assume counts from different providers use the same rule.
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A ranked list is useful for calculating top-wallet shares, but a partial page is not enough to calculate the full holder distribution. Retrieve enough pages for the top-N measure you intend to report, and confirm whether balances and total supply refer to the same snapshot. If the provider does not expose historical balances, the result is a snapshot of the data returned at retrieval time—not a historical series.
Use a balance dataset
Dune’s stablecoin dataset documentation describes raw daily balance snapshots across supported networks and separate enriched balance data. Its documentation identifies free normalized balance snapshots and premium enriched balance tables and activity tables. Check the current chain and token coverage, table availability, snapshot cadence, and access level before relying on a deployment or comparing providers.
Raw balances and enriched balances serve different purposes. Raw balances support calculations based on addresses and token amounts. Enriched data adds categories intended to describe economic function, but categories and entity labels are not a complete identity map. Dune says entity labels and manual attribution are updated periodically, and attribution for exchanges and large institutional holders is still being developed. Preserve the provider’s label date or retrieval date with your analysis.
Choose a denominator before calculating shares
For a chain-specific analysis, a straightforward denominator is the deployment’s total on-chain supply at the same snapshot time as the address balances. State the exact supply definition and whether you include issuer or treasury wallets, burn addresses, locked protocol contracts, and bridged tokens. Those choices can materially change the reported share.
Let Bi be the balance of address i, and let S be your stated supply denominator. The share of supply held by a selected group is:
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Group share (%) = (sum of balances in the group ÷ S) × 100
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For the top-10 share, select the ten largest eligible addresses, add their balances, divide by S, then multiply by 100. Use consistent inclusion rules for the numerator and denominator. For example, if you exclude burn addresses from the top-holder list, decide whether the denominator also excludes their balances and explain that choice. Do not mix a numerator drawn from one chain with a cross-chain supply denominator.
One useful presentation is to show a primary, inclusive figure and then disclose meaningful exclusions separately—for instance, the top-10 share including known protocol and exchange addresses, followed by the share after excluding a clearly defined burn address. Avoid silently removing large addresses because their presence makes a result look less representative; the exclusions are part of the metric, not a cosmetic adjustment.
Calculate concentration and describe the distribution
Top-wallet shares
Report one or more ranked shares, such as top 1, top 10, or top 100. State the number of addresses in each group, the denominator, and whether known contracts or other categories are included. Top-N shares are easy to explain and reproduce, but they say little about how balances are distributed below the selected cutoff.
Wallet-size bands
For a fuller picture, group addresses into balance bands and report both the address count and the share of supply in each band. Define boundaries in token units or as a percentage of supply, and make the bands mutually exclusive. If the data provider offers wallet categories, show them separately from balance bands: “exchange” is a role classification, whereas “holds at least a specified amount” is a size classification.
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Herfindahl–Hirschman Index
You can also calculate the Herfindahl–Hirschman Index (HHI) from the shares of all eligible addresses. If each address’s share is expressed as a percentage, square each percentage and add the results. Under that convention, the index ranges toward 10,000 when one address holds all of the included supply; a decimal-share convention instead yields values up to 1. State which scale you use. An HHI calculated from addresses is still an address-concentration measure, not a measure of beneficial ownership.
For HHI, explain whether you treated addresses as separate units, combined addresses you could reliably attribute to one entity, and excluded burns, protocol contracts, or other balances. If entity attribution is incomplete, an address-based HHI may count one entity several times, while grouping addresses on uncertain labels may introduce a different error. Include the methodology rather than presenting the index as self-explanatory.
Classify the largest addresses without overclaiming
Inspect the largest addresses and classify them only where labels or other evidence support a category. Dune’s enriched categories include DEX, lending, bridge, yield, issuer, treasury, CEX, burn, unidentified smart contract, whale, and unidentified. These labels can help explain why an address is large, but they do not establish who ultimately benefits from the balance.
Keep at least these distinctions visible when they matter:
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- Exchange or custodian: an address that may pool assets for many customers.
- Protocol, bridge, or contract: balances held or managed by an on-chain service rather than necessarily by one user.
- Burn address: tokens sent to an address treated as inaccessible under the provider’s methodology.
- Unidentified: an address whose role or owner is not established by the available labels.
Do not convert a label such as “whale” into a claim about a named owner. Nor should you assume that an exchange address’s entire balance belongs to the exchange as beneficial owner. When labels are absent, stale, or ambiguous, mark the address as unidentified rather than guessing.
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Compare chains and dates on an apples-to-apples basis
For a time series, hold the token deployment, denominator rule, eligible-address rules, and labeling logic constant across snapshots. If a provider’s coverage or classifications change, note the change rather than presenting a discontinuity as a real movement of tokens. For cross-chain analysis, present each deployment separately before any roll-up, with its own chain, contract, snapshot, and denominator.
A practical comparison table should include the following fields:
- Stablecoin ticker, chain, and token contract or mint address.
- Snapshot date and time, plus the data provider and retrieval date.
- Supply denominator and rules for burns, treasuries, contracts, and bridged assets.
- Top-1 or top-10 share, holder count, and optional size-band or HHI results.
- Categories of the largest wallets and the provider’s label-coverage caveat.
Provider differences matter. One dataset may include labels and another may not; one holder count may include dust balances while another applies a threshold. Check supported chains, token coverage, snapshot frequency, label methodology, and whether relevant tables require premium access. If two values use different rules, label them as different measurements rather than treating them as directly comparable.
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Dune’s article “A Behavioral Map of Stablecoins,” published July 10, 2026, reports balances dated June 29–30, 2026. These are historical, provider-specific figures, not live balances. Its comparisons illustrate why ticker-only comparisons are misleading:
| Deployment or example | Reported finding | Interpretation |
|---|---|---|
| USDT on Tron | About 74.7 million holders; the ten largest addresses held roughly 5% of supply. | A very large holder count coexisted with a relatively small top-10 share in that snapshot. |
| USDT on BNB Chain | About 70 million holders; the ten largest addresses held roughly 18% of supply. | The same ticker had a substantially different reported top-10 share on another chain. |
| USDC on its main chains | About a quarter of supply was in the top ten on each of the main chains discussed. | The approximate similarity in this metric does not mean the largest addresses had the same roles or ownership. |
| USDe and USDS | Each had about 94% of supply in the top ten. | Large top-10 shares should prompt inspection of the largest-address categories and deployment context. |
| USDC on HyperEVM | The most concentrated analyzed pair: about 99% in the top ten. | This is specific to the analyzed deployment and snapshot, not a claim about all USDC. |
Dune’s calculation counts exchange and contract wallets. The figures therefore measure distribution among addresses or custody locations, not the number of people holding the asset. Its reported category breakdowns make the distinction concrete: USDC on Base had about 56% with one exchange; on Ethereum, around 57% was in ordinary wallets and 28% on exchanges; on HyperEVM, about 88% sat in a reserve wallet supplying Hyperliquid trading. These examples describe the categories and deployments in that analysis, not a timeless or universal distribution.
Do not infer payment use from transfer counts
Wallet distribution is not the same thing as payment activity. A transfer event does not necessarily represent a standalone payment between two people: programmable transactions can combine trading, lending, arbitrage, liquidity provision, and settlement.
In its 2026 working paper on Ethereum transaction and event data, the Bank for International Settlements reports that nearly 60 percent of stablecoin transfer events in its study occurred within complex transactions. The authors caution against treating each transfer as an independent payment. That figure is specific to their Ethereum study; it should not be generalized to every chain or to all stablecoin activity. For the paper’s scope and findings, see the BIS publication, “The anatomy of stablecoin transactions,” Working Paper 1359.
Quick Recap
A reproducible check, step by step
- Verify the deployment. Write down the ticker, chain, and official contract or mint address. Confirm the token is the intended issuer deployment rather than a similarly named or bridged asset.
- Fix the snapshot. Choose a date and time, and use balances and supply from the same point or clearly state any timing difference.
- Choose a source. Use a chain explorer, a holder API, or an analytics dataset. Record the provider, retrieval date, coverage, and any balance threshold or pagination setting.
- Define eligibility. Decide how to handle burns, issuer and treasury balances, smart contracts, locked balances, and bridges. State both the numerator rule and denominator rule.
- Collect and rank balances. Obtain enough records to identify the top wallets and the holder count under the provider’s rules. Preserve raw addresses and balances so the result can be checked.
- Calculate the metrics. Compute top-N shares using the stated denominator. Add balance bands or HHI only if you can explain their boundaries, units, and inclusion rules.
- Review the leading addresses. Apply reliable labels where available; distinguish exchanges, protocols, issuer wallets, burns, contracts, and unidentified addresses. Do not infer an owner from a category label alone.
- Publish the comparison with context. Include deployment, date, denominator, provider, holder-count method, and label limitations beside the figures. For multiple chains, show deployments individually before discussing any aggregate.
Common mistakes and how to avoid them
- Using only the ticker: identify the chain and contract or mint address because bridged and native versions are distinct deployments.
- Calling addresses people: describe address-level concentration and explain that pooled and multi-address ownership can distort a people-level interpretation.
- Mixing supply definitions: use a deployment-specific denominator and disclose treatment of burns, treasuries, contracts, and bridged tokens.
- Treating holder count as a concentration score: report top-wallet shares or another defined concentration metric alongside address count.
- Assuming labels are complete: use unidentified categories where appropriate and date the provider’s labels or retrieval.
- Comparing unlike snapshots: align deployment, snapshot timing, source coverage, and inclusion rules before interpreting a change.
- Reading transfers as payments: transfer-event totals alone do not establish how many people paid one another or how tokens are distributed.
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