Earning $80,000 in One Day: How Top Players Turn Polymarket into Their Personal ATM?

比推Pubblicato 2026-02-13Pubblicato ultima volta 2026-02-13

Introduzione

In just under a day, a top trader on Polymarket, using the handle Bidou28old, netted $80,000 by exploiting the platform’s newly launched ultra-short-term prediction markets (5-minute and 15-minute intervals). The user is believed to be a quantitative trader or arbitrageur leveraging low-latency data feeds to capitalize on pricing delays. With only 48 total predictions, the trader maintained a remarkably high risk-reward ratio, often buying outcomes with only a 3-8% probability (e.g., betting on a Bitcoin rebound within minutes during a sharp decline). Even with 7 losses exceeding $10,000, the strategy remained profitable due to high payoff multiples—sometimes as high as 33x. The trader employed strict position management, placing large bets ($7,000–$19,000) on high-probability opportunities and securing returns between $4,800–$6,400 per successful trade. In one notable 30-minute span, the user executed three consecutive winning trades, earning over $18,000, demonstrating a high-frequency, data-driven approach. Activity was concentrated during U.S. evening hours (7:30–11:00 PM ET), suggesting either a North American night trader or a professional Asian quant operating during daytime hours. The trader focused predominantly on Bitcoin and Ethereum due to their high liquidity and volatility. This case highlights how sophisticated players use quantitative strategies and real-time market data to systematically profit from short-term market movements on prediction platfo...

Author: Ma He, Foresight News

Original Title: Earning $80,000 in One Day, This Top Player Treats Polymarket as an ATM


The crypto market is unpredictable, even top traders sometimes step back due to its hellish difficulty.

Predicting weekly or monthly trends might not be too hard, but what if the timeframe shrinks to minutes? The difficulty skyrockets.

However, smart people always find their own ways to make money.

A player nicknamed Bidou28old (0x4460bf2c0aa59db412a6493c2c08970797b62970) on Polymarket, who just joined in February this year, netted $80,000 in less than a day.

This player is no ordinary speculator; they were among the first top players on Polymarket's newly launched "5-minute / 15-minute ultra-short-term prediction markets" in February 2026.

They made only 48 predictions in all, but the win rate and profit-loss ratio are astonishing. They aren't "predicting" the future; they are "hunting" volatility. They are most likely a quantitative trader or an arbitrageur with extremely low-latency market data, specifically targeting Polymarket's pricing delays for a dimensional strike.

If you scroll down on this trader's Polymarket address homepage, you will be stunned by their "losses" – just these 7 losses amount to over $10,000.

Ordinary people see failure, but this player sees mathematical logic. Observe some of their entry prices: 3¢, 5¢, 8¢, 0.8¢. On Polymarket, they specifically buy events the market believes have only a 3%-8% chance of happening (e.g., buying "rebound within 5 minutes" when BTC plummets). If they buy at 3¢ and guess correctly, the return is 33x. This means even if they fail 30 times, succeeding just once covers the cost; succeeding twice is pure profit.

If these failed cases are about betting small to win big, losing more but winning occasionally, then the big wins shown below truly reveal the other side of their top-tier trading skills.

Looking at this screenshot of massive wins, you'll notice a startling pattern: extremely high single-trade investments. Their winning bets generally range from $7,000 to $19,000. Furthermore, their profit amounts are very stable, almost every single one falling between $4,800 and $6,400.

This indicates they have a strict position management model. They aren't gambling for a "double-up"; they are betting on "certainty." Whenever the market shows a signal they recognize, the moment the trend becomes clear, they push in tens of thousands of dollars, capturing 30%-50% of the move before retreating.

If you think those so-called techniques are child's play, then look at these three bets placed within 15-minute timeframes.

9:00 PM – 9:05 PM: Made $6,028;

9:10 PM – 9:15 PM: Made $6,350;

9:15 PM – 9:30 PM: Made $5,717;

This can be called a textbook example of high-frequency position switching.

Within 30 minutes, they executed three consecutive operations on price predictions for different short timeframes, accumulating over $18,000 in profit. This frequency means they are definitely not making decisions based on news; they are watching second-level candlestick charts or order flow.

Looking carefully at their historical transaction records, most of their trading time is concentrated between 7:30 PM and 11:00 PM EST, which is 8:30 AM to 12:00 PM Beijing Time the next day.

Based on their trading frequency and time, this trader is either a night hunter in North America, perhaps using their evening rest time after the US stock market closes and dinner to specifically harvest volatility in cryptocurrencies during the US post-market session. Or, they could be a "daytime professional trader" in the Asia-Pacific region, as the extremely calm, high-frequency style with single bets in the tens of thousands of dollars matches a professional quantitative trader based in Asia treating this as a full-time job.

In terms of asset selection, they heavily favor BTC, followed by ETH and other major cryptocurrencies, because their high volatility makes them less susceptible to manipulation by single forces, suitable for such large short-term bets.

They allow themselves small losses but dare to place heavy bets on high-probability opportunities (60¢+).

Perhaps, this is the self-cultivation of a Polymarket top player.


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Original link:https://www.bitpush.news/articles/7611832

Domande pertinenti

QWho is the top player mentioned in the article that earned $80,000 in less than a day on Polymarket?

AThe top player is known by the nickname Bidou28old, with the address 0x4460bf2c0aa59db412a6493c2c08970797b62970.

QWhat is the key strategy that the player Bidou28old uses to profit on Polymarket?

AThe player is not predicting the future but 'hunting' volatility, likely as a quantitative trader or an arbitrageur exploiting Polymarket's pricing delays by buying low-probability events for high returns.

QHow does the player manage risk despite having significant losses in some trades?

AThe player uses a strict position management model, allowing small losses on low-probability bets but placing large bets (e.g., $7,000 to $19,000) on high-probability opportunities (60¢+), ensuring that even with many small losses, a few wins cover costs and generate profit.

QWhat trading pattern did Bidou28old demonstrate in one 30-minute period, as highlighted in the article?

AIn a 30-minute period, the player executed three consecutive trades in different short-term prediction markets (5-minute and 15-minute intervals), earning over $18,000, showcasing high-frequency position switching based on real-time data like second-level K-line charts or order flow.

QDuring which time periods does Bidou28old primarily trade, and what does this suggest about their location or strategy?

AThe player trades mostly between 7:30 PM and 11:00 PM EST, which is 8:30 AM to 12:00 PM Beijing time, suggesting they could be a night trader in North America or a professional daytime quant in Asia, capitalizing on cryptocurrency volatility during post-US market hours or Asian trading sessions.

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An individual manipulated a weather sensor at Paris Charles de Gaulle Airport with a portable heat source, causing a Polymarket weather market to settle at 22°C and earning $34,000. This incident highlights a fundamental issue in prediction markets: when a market aims to reflect reality, it also incentivizes participants to influence that reality. Prediction markets operate on two layers: platform rules (what outcome counts as a win) and data sources (what actually happened). While most focus on rules, the real vulnerability lies in the data source. If reality is recorded through a specific source, influencing that source directly affects market settlement. The article categorizes markets by their vulnerability: 1. **Single-point physical data sources** (e.g., weather stations): Easily manipulated through physical interference. 2. **Insider information markets** (e.g., MrBeast video details): Insiders like team members use non-public information to trade. Kalshi fined a剪辑师 $20,000 for insider trading. 3. **Actor-manipulated markets** (e.g., Andrew Tate’s tweet counts): The subject of the market can control the outcome. Evidence suggests Tate’sociated accounts coordinated to profit. 4. **Individual-action markets** (e.g., WNBA disruptions): A single person can execute an event to profit from their pre-placed bets. Kalshi and Polymarket handle these issues differently. Kalshi enforces strict KYC, publicly penalizes insider trading, and reports to regulators. Polymarket, with its anonymous wallet-based system, has historically been more permissive, arguing that insider information improves market accuracy. However, it cooperated with authorities in the "Van Dyke case," where a user traded on classified government information. The core paradox is reflexivity: prediction markets are designed to discover truth, but their financial incentives can distort reality. The more valuable a prediction becomes, the more likely participants are to influence the event itself. The market ceases to be a mirror of reality and instead shapes it.

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