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World desk12 min

How to Check a Stablecoin’s Token Concentration and Wallet Distribution

A reproducible guide to measuring stablecoin concentration: identify the exact chain deployment, retrieve dated balances, define supply and exclusions, and interpret address-level results carefully.
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To check a stablecoin’s concentration, first identify the exact token deployment—ticker, blockchain, and contract or mint address—then take a dated snapshot of its address balances and compare large-wallet holdings with a clearly defined supply denominator. A ticker alone is not enough: the same stablecoin can have very different holder counts and concentration on different chains. The result describes balances by address, not necessarily ownership by individual people.

What token concentration tells you—and what it does not

Token concentration measures how much of a token’s supply is held by a small number of addresses or by defined groups of addresses. A common first check is the percentage held by the ten largest addresses, often called the top-10 share. You can also examine the largest address, top five, top 100, or a concentration index such as the Herfindahl–Hirschman Index (HHI).

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These measures answer different questions. The top-10 share is easy to interpret: it tells you what fraction of the chosen supply is in the ten largest address balances. HHI uses the shares of all addresses in the calculation, so it reflects more of the distribution than a top-wallet cutoff. Neither measure, on its own, tells you whether the distribution is economically risky, whether holders can redeem, or how many people ultimately control the balances.

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Most importantly, an address is not necessarily a person or independent holder. An exchange or custodian can hold tokens for many customers in one address; one organization can also control multiple addresses. A protocol, bridge, issuer, treasury, or burn address can rank among the largest without representing an ordinary investor. Treat an address-level result as a map of on-chain balances and custody locations, not a definitive beneficial-ownership register.

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Start with the exact token deployment

Before collecting balances, record the asset identity and the snapshot you intend to analyze. A token ticker can be reused, and a native issuer token, a bridged version, and another token with a similar name may be separate assets. Results are meaningful only when they are tied to the correct contract or mint address on the correct network.

  • Ticker and token name: useful labels, but not sufficient to identify the asset.
  • Chain: for example, Ethereum, Tron, Base, or another supported network.
  • Contract or mint address: verify that it is the intended deployment, rather than relying on a search result or ticker alone.
  • Snapshot date and time: balances change, so a concentration result without a timestamp is not reproducible.
  • Supply definition: decide whether the denominator is the deployment’s total on-chain supply and state how special addresses and bridged representations are treated.

Do not combine a chain-specific holder list with a supply figure that covers multiple chains. That would compare a numerator and denominator from different scopes. For a cross-chain comparison, calculate each deployment separately first; only create a roll-up if you can define a consistent cross-chain supply and avoid double-counting representations of the same economic tokens.

Get the address balances

There are three common ways to retrieve balances: a token-holder view in a chain explorer, a holder API, or an on-chain balance dataset. Choose a source that identifies the chain and token deployment clearly, and check its coverage and snapshot timing before treating its output as complete.

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Explorer holder views

A chain explorer can be a straightforward starting point for a single token deployment. Find the verified token page for the exact contract or mint address, then open its holder or token-holder view if available. Record the date and time of retrieval, whether the page is paginated, and any stated limits. An explorer’s displayed holder count may reflect its own indexing and filtering, so note the provider rather than presenting the count as a universal census.

Holder APIs

An API is useful when you need ranked and paginated results or want to repeat the same extraction. HolderScan documents a holders endpoint that returns ranked, paginated token holders and a total holder count: HolderScan’s holders API documentation. Before calculating, confirm that the endpoint parameters specify the intended chain and token address, and capture all pages needed for the metric you report. If the API supplies only a top-N list, it may support a top-N share but not a full-distribution HHI.

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On-chain balance datasets

A balance dataset can help with repeatable snapshots and analysis across deployments. Dune documents raw daily stablecoin balance snapshots across supported networks, as well as enriched balance data that adds economic-function categories. Its documentation distinguishes free balance snapshots from premium enriched balances and activity tables; availability and supported coverage should be checked in the current Dune stablecoin dataset documentation. The published dataset overview is also available at Dune’s Stablecoin Dataset article.

Raw and enriched balances are not interchangeable. Raw balances are the basis for a balance calculation; enriched labels are an interpretation layer that attempts to classify addresses by function. Dune says entity labels and manual attribution are updated periodically, and named-entity attribution for exchanges and large institutional holders is still being developed. Therefore, an unlabeled address is not proof that it belongs to an individual, and a category assignment should not be presented as exhaustive ownership information.

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Choose a denominator and inclusion rules

The arithmetic is simple only after the scope is settled. For a deployment-level analysis, a practical denominator is the token’s total on-chain supply at the snapshot time. State this explicitly and make sure that the address balances being added come from that same deployment and time.

Decide in advance how you will handle issuer or treasury wallets, burn addresses, locked protocol contracts, bridges, and other large contract balances. There is no universally correct choice for every question. Including all on-chain balances answers how supply is distributed among addresses under the chosen supply definition. Excluding a category can answer a narrower question, such as how balances are distributed outside issuer-controlled addresses—but then the denominator and numerator must both be adjusted consistently.

Decision What to document Why it changes the result
Supply denominator Total on-chain supply for the named deployment at the snapshot time, or a clearly defined alternative Top-wallet percentages depend on the denominator; mixing a chain-specific balance list with cross-chain supply distorts the share.
Issuer and treasury Whether labeled issuer or treasury addresses are included Large operational balances can materially affect the top-wallet share without representing circulating user holdings.
Burn addresses Whether burn addresses are counted and how they are identified Including tokens that are not available to ordinary holders can change concentration statistics.
Protocol and bridge contracts Whether locked, pooled, or bridged balances remain in the address-level calculation Contracts can aggregate many users or represent tokens moving through infrastructure rather than one holder.
Related addresses Whether known addresses are analyzed separately or grouped, and the evidence for grouping One entity may use multiple addresses; grouping changes entity-level concentration and requires reliable attribution.

Keep both the raw address-level calculation and any adjusted view. If you exclude a category, explain the exclusion and show the corresponding denominator. Never silently remove a large address because its balance looks unusual.

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Calculate top-wallet shares and HHI

Top-wallet share

Rank the addresses by balance at the snapshot and add the balances for the selected group. Divide that sum by the stated supply denominator, then multiply by 100 to report a percentage:

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Top-N share (%) = (sum of balances in the N largest addresses ÷ stated supply denominator) × 100

Apply the same rule for top one, top five, top ten, or top 100. State which address types are included and whether the figures are address-level or grouped by attributed entity. If you calculate a top-10 share from a paginated source, make sure you have the actual ten largest addresses rather than the first ten rows of a differently sorted or filtered list.

HHI, if you need a fuller concentration measure

For an address-level HHI, calculate each address’s share of the same denominator and square those shares; then add the squared values across the addresses included. If shares are expressed as fractions, the result is on a 0-to-1 scale. If shares are expressed in percentage points, the result is on a 0-to-10,000 scale. State which units you use so a reader can compare like with like.

HHI is sensitive to the unit being analyzed. An address-level calculation treats each address separately, even if several addresses belong to one entity. An entity-level calculation requires a defensible method for grouping related addresses. Explain whether contracts, known related addresses, and excluded balances are included; otherwise, another analyst cannot reproduce the result. If your data source provides only a ranked list of the largest holders rather than balances for the full distribution, do not present a partial calculation as a complete HHI.

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Describe the distribution, not just the biggest number

A top-10 percentage and a holder count are useful starting points, but together they still leave much of the distribution hidden. A fuller report can show shares across wallet-size bands and identify the types of the largest addresses where labels are available. Define the bands before comparing tokens, use the same thresholds at every snapshot, and make clear whether bands count addresses or sum their token balances.

For the largest addresses, distinguish among exchanges, protocols, issuer and treasury wallets, burn addresses, unidentified smart contracts, and ordinary or unidentified wallets when the provider supports those labels. Dune’s enriched categories include DEX, lending, bridge, yield, issuer, treasury, CEX, burn, unidentified smart contract, whale, and unidentified. These categories describe inferred economic function, not verified beneficial ownership, and labels can be incomplete or change as attribution is updated.

Do not interpret a large holder count as proof that ownership is broadly distributed. Many small addresses can coexist with a significant share held by a few large wallets. Conversely, a large exchange address may pool balances for many customers. Report the count, concentration metric, distribution bands, and address categories together when available; each addresses a different part of the question.

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Compare deployments and snapshots fairly

For a time series, hold the token deployment, supply rule, calculation method, and labeling logic constant at each snapshot. If any of these changes, mark the break rather than describing the resulting line as a clean change in concentration. A provider may also revise historical balances or labels, so note the provider and retrieval date when reproducibility matters.

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For cross-chain comparisons, present each chain-specific deployment independently before any roll-up. A comparison table should include at least the chain and token address, snapshot date, holder count, top-wallet share or defined index, denominator, the largest-wallet categories, provider, and known coverage caveats. Different chain coverage, snapshot frequency, token coverage, and access tiers can make superficially similar metrics non-comparable.

Dune’s published analysis illustrates why the deployment matters. In its analysis using balances dated June 29, 2026, USDT on Tron had about 74.7 million holders and roughly 5% of supply in its ten largest addresses; USDT on BNB Chain had about 70 million holders and roughly 18% in its top ten. These are historical, provider-specific observations, not live figures. They should not be read as a current ranking or as measurements of unique people. The figures are reported in Dune’s July 10, 2026 article, “A Behavioral Map of Stablecoins”.

Deployment or finding Reported result Snapshot and interpretation
USDT on Tron About 74.7 million holders; roughly 5% of supply in the top ten addresses Dune balance snapshot dated June 29, 2026; historical, provider-specific address data.
USDT on BNB Chain About 70 million holders; roughly 18% of supply in the top ten addresses Dune balance snapshot dated June 29, 2026; not directly interchangeable with a different chain’s deployment.
USDC on its main chains About a quarter of supply in the top ten addresses on each of the main chains discussed Dune’s June 29, 2026 balance analysis; the article’s chain-specific context matters.
USDe and USDS Each had roughly 94% of supply in the top ten addresses Dune’s June 29, 2026 analysis; historical figures, not live concentration readings.
USDC on HyperEVM About 99% of supply in the top ten; roughly 88% sat in a reserve wallet supplying Hyperliquid trading Dune’s June 29, 2026 analysis; this is a deployment- and address-category-specific example.
USDC on Base About 56% of supply was held by one exchange Dune’s historical analysis; an exchange address may represent pooled customer custody, not one beneficial owner.
USDC on Ethereum Around 57% sat in ordinary wallets and 28% on exchanges Dune’s historical category breakdown; labels are classifications, not a complete identity map.

These figures should be read with Dune’s stated methodology in mind: its concentration calculation counts exchange and contract wallets. A top-ten figure therefore measures distribution among addresses and custody locations, not the number or concentration of individual people. The large reserve, exchange, and protocol examples also show why the address category can be as important as the percentage.

Use transfer activity cautiously

Transfer counts are not a substitute for wallet distribution. A transfer event can occur inside a larger atomic transaction involving trading, lending, arbitrage, liquidity provision, or settlement; it need not represent a standalone payment between two users. The Bank for International Settlements’ 2026 working paper, The anatomy of stablecoin transactions, reports that nearly 60 percent of the stablecoin transfer events in its Ethereum study occurred within complex transactions. That result is specific to the paper’s Ethereum transaction and event data; it should not be generalized to every chain or all stablecoin activity. See the BIS Working Paper 1359.

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For a concentration question, use balance snapshots and holder data as the core evidence. If you also discuss transfer activity, explain what the source counts as a transfer and whether it isolates standalone payments from events embedded in complex transactions.

A reproducible checklist for a concentration report

  1. Identify the deployment. Write down the ticker, chain, and official contract or mint address. Confirm that the address is the intended issuer deployment.
  2. Set the snapshot. Choose a date and time, then use a source whose balance timing and coverage are clear.
  3. Retrieve balances. Use an explorer, holder API, or on-chain balance dataset. Record pagination, source, retrieval date, and any known limits.
  4. Set the denominator and inclusions. Specify the supply basis and treatment of issuer, treasury, burn, locked-contract, bridge, and related-address balances.
  5. Calculate the metric. Report top-1, top-10, or another defined share; if using HHI, specify address versus entity level and units.
  6. Add distribution context. Include holder count and, where possible, consistent wallet-size bands and categories for the largest addresses.
  7. Qualify attribution. Identify which labels are provider-inferred, incomplete, periodically updated, or unavailable.
  8. Compare only matching scopes. Keep deployment, timestamp rules, denominator, and labeling method consistent across chains or dates.

A compact report can make these choices visible in a methods note: “Balances for [deployment] at [snapshot time]; denominator [definition]; top-10 share includes [address categories]; source [provider], retrieved [date]; labels [method and limitations].” Replace each bracketed field with the actual value before publishing. This makes the calculation easier to reproduce and prevents a percentage from being mistaken for a timeless property of a ticker.

Common interpretation mistakes

  • Calling addresses holders in the human sense: use “addresses” unless you have evidence about beneficial owners.
  • Comparing a ticker across chains without naming deployments: show each chain and contract or mint address separately.
  • Mixing denominator scopes: match the supply and balances to the same deployment and snapshot.
  • Removing contracts or exchanges without disclosure: exclusions can transform the result; state them and adjust the denominator consistently.
  • Treating provider labels as complete: categories and named-entity attribution can be incomplete or updated over time.
  • Using a large holder count as a decentralization verdict: count does not reveal how supply is distributed among addresses or entities.
  • Reading raw transfers as user payments: complex transactions can bundle many operations, so event counts do not establish payment use or distribution.
  • Presenting a dated snapshot as current: label the observation with its snapshot date and provider, especially when quoting an older comparison.

What a careful conclusion can say

A sound conclusion is scoped to the evidence: for a named token deployment, at a named snapshot, a defined share of the chosen supply sat in a defined set of addresses under specified inclusion rules. Add what is known about those addresses, and make clear where labels or ownership attribution are uncertain. That is enough to compare observable wallet distribution without claiming to know who ultimately owns every balance.

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