The downfall of a 100% winning streak whale: 21-day betting spree, 14-game winning streak ended, $44.67 million evaporated. | Bee Network
Image source: Hyperbot
From Accumulation to Peak On October 14, 2025, an anonymous whale with the address 0xc2a30212a8ddac9e123944d6e29faddce994e5f2 began a fourteen-consecutive-profit trading cycle on Hyperliquid. He bought 5,255 ETH, sold them the next day for 22 million USDC, and shorted BTC with approximately 5x leverage. Just one night later, at 8 AM on October 16th, he closed his position, making a profit of $2.6 million. This was his first profitable trade in a row, and also the cleanest trade in the entire cycle. The following week, he precisely switched directions amidst the volatility. On the morning of October 17th, he turned bullish, adding to his position twice, expanding it to $222 million. Before the market crashed in the early hours of October 22nd, he closed out approximately $300 million of his long positions, netting a profit of $6.04 million. This move became a signature action in his tweets, described as “the guy’s reaction was quick,” and solidified his myth of a 100% win rate. October 24th to 28th was his peak period. He continuously added to his BTC and ETH positions in batches, keeping the leverage below 8x, expanding his position from $274 million to $447 million. On Hyperbot’s profit and loss curve, that was the only complete upward green line—at 6:12 AM on October 28th, the account had a floating profit of $25.349 million. This was the last time his profit and loss curve showed a one-sided upward trend. The following week, the rhythm began to subtly shift. From taking profits to obsession On October 29th, the whale chose to close out its profitable positions first, while continuing to hold onto its losing positions. At 4 AM, the market dropped, and it closed out its $268 million BTC long positions, making only a profit of $1.4 million. In the afternoon, it closed out its $163 million ETH long positions, making a profit of $1.63 million, leaving only its trapped SOL positions. Two days later, he increased his SOL position to a total of $105 million, bringing his average cost to $198.3. In the early hours of October 30th, Federal Reserve Chairman Powell’s speech triggered a brief market downturn. He chose to buy the dip in BTC and ETH, while simultaneously increasing his SOL position. That evening, all three positions were underwater, resulting in a paper loss of $9.73 million. At 4:00 AM on October 31st, losses peaked at over $18 million. As the market rebounded, the floating losses narrowed, and the whale attempted to hold on until it broke even. By 8:00 AM on November 3rd, the floating losses had shrunk to $1.98 million; it was just one step away from breaking even, but it didn’t reduce its positions. Just three hours later, the market turned downwards, and all four of the whale’s previously undefeated long positions were once again in a state of floating loss. He was just one step away from a clean getaway, but in waiting and hesitating, he handed the initiative back to the market. From stop-loss to self-destruction In the early hours of November 4th, his undefeated streak officially ended. He cut his losses, closing out $258 million worth of long positions in BTC, ETH, and SOL, incurring a loss of $15.65 million. This figure is equivalent to the $15.83 million profit he earned over the previous 20 days and 14 consecutive wins. At this point, he still held $148 million worth of long positions in ETH, SOL, and HYPE, with a floating loss of $18.86 million, and only 8% away from the liquidation price. The market continued its downward trend throughout the day. The whale was only 4% away from the liquidation price. His account balance had already fallen by $40.4 million from its peak, returning him to square one. With the liquidation price rapidly approaching, any rational trader should have stopped, but he instead added 2196 ETH and 78,724 SOL at $3497 and $159 respectively. The liquidation line was further pushed up, with the ETH liquidation price at $3348 and the SOL liquidation price at $151.6. ETH was only $130 away from liquidation, and SOL was only $8 away. On November 5th, it all ended. Around 5 AM, he was forced to liquidate all his positions, leaving his account with only $1.4 million in margin, practically equivalent to a margin call. Thus, this 21-day trading spree ended completely with nothing. The $15.83 million in profit from 14 consecutive wins, plus his initial $28.76 million principal, totaling $44.67 million, was wiped out in a single loss. Between leverage and human nature In Hyperliquid’s trading history, almost every legendary trader ended in a similar way: James Wynn once held $1.2 billion in BTC long positions with 20x leverage, peaking at $87 million in profit, but ultimately losing $21.77 million; qwatio used $3 million to endlessly roll over positions, once earning $26 million, only to lose it all in the end; veteran trader AguilaTrades made a peak profit of $41.7 million with $300,000, but ultimately lost $37.6 million. And this anonymous whale, known for his “14-game winning streak,” also wiped out $44.67 million in just one night. Winning streaks can be achieved through skill and luck, but survival always depends on restraint. When everyone is captivated by the upward curve, the outcome is often already predetermined by leverage. この記事はインターネットから得たものです。 The downfall of a 100% winning streak whale: 21-day betting spree, 14-game winning streak ended, $44.67 million evaporated.Recommended Articles Related: The Monad Meme Handbook: How to Discover the Next 10,000-Fold Meme Coin Original translation: AididiaoJP, Foresight News In this article, I’ll cover the following tools and strategies: Tracking wallets and sniping early releases Managing risk, positions and profit taking Monitor social media for early contract addresses and information advantages New Token Discovery Copy profitable avid traders. Let’s start by exploring how to find these tokens in the first place 1. Token Discovery Early discovery is 90% of the work, and to be able to do early discovery you must understand the various stages of token discovery. 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