A sharp drop in spot ETH typically creates two simultaneous pressures. The first is simple mark-to-market pain for large holders with higher average entry prices. The second is mechanical selling triggered by leverage, especially when loans, perps, or structured positions sit close to liquidation bands.
That combination matters because it changes behavior. Large holders can shift from accumulation to balance-sheet defense, which often looks like exchange deposits, loan repayments, or a move into staking to reduce circulating float.
The figures summarized below are taken from a Lookonchain infographic in this post.
The largest ETH exposure in the set to Tom Lee’s Bitmine, with a total purchase of about 4.243M ETH (shown as roughly $9.55B at the time of aggregation), with an average cost around $3,854 and an implied PnL near -$6.8B.
The root driver here is cost basis, not a single trade. A treasury-style accumulation program concentrates price risk into spot, which makes drawdowns look extreme when measured in dollars, even if the holder is not using high leverage.
For first-party validation of holdings labels and net flows, Arkham’s entity page for Bitmine provides a starting point to review wallets, inflows, outflows, and counterparties.
BitcoinOG (1011short) faces two distinct sources of loss.
One portion comes from rotation. It cites a swap of 35,991 BTC into 886,371 ETH at an ETH/BTC ratio of 0.0406, resulting in a $770M+ loss figure.
The second portion comes from leverage. It cites a 223,340 ETH long (shown as about $632M) that was liquidated, with an additional loss shown around $195M.
The root cause is compounding. Rotation into ETH at a less favorable relative level creates drawdown when the ratio moves against the position, and leverage adds a hard failure mode because liquidation converts drawdown into realized loss.
Entity-level tracking for this label is accessible via Arkham at this entity page, which is useful for verifying whether subsequent flows look like de-risking, re-hedging, or loan repayment.
Large ETH position of Jack Yi’s Trend Research, purchases of about 651K ETH (shown as roughly $1.46B at the time of aggregation), an average cost near $3,300, and an implied PnL near -$680M.
The core driver is again cost basis paired with position size. Even if a holder avoids liquidation risk, a large spot inventory can become a source of supply pressure if it must be tapped to repay leverage elsewhere.
Arkham’s entity page for Trend Research is a practical place to monitor whether the entity shifts into exchange deposits, staking, or stablecoin borrowing and repayment loops.
Large underwater holders create a market overhang even without “capitulation.” When spot rebounds, those entities can become natural sellers as they reduce exposure, rebalance treasury risk, or repay liabilities.
Leverage-driven losses also change the tape in the short run. Liquidations reduce open interest, compress positioning, and can produce sharp relief bounces that are mechanical rather than sentiment-led.
A third-order effect is narrative spillover. When highly visible whales or treasuries are underwater, market participants tend to overweight on-chain flow signals, making exchange deposits and loan repayment transactions more price-relevant than usual.
The safest path is to start from the original infographic post and then cross-check against first-party analytics pages.
A practical workflow that avoids fake portals:
This snapshot is less about personalities and more about positioning. Large ETH inventories with higher cost bases create visible drawdowns during selloffs, while leverage adds liquidation risk that can turn losses into forced realization. The most useful signal is not the headline PnL, but whether on-chain flows shift into exchange deposits, loan repayments, or other actions that change effective supply.
The post Top Ethereum Whales Under Pressure: Bitmine, 1011short, And Trend Research appeared first on Crypto Adventure.
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