Making a Profit of $100,000 from 'Mosquito Meat' with 170 High-Frequency Trades per Day?

比推Published on 2026-02-11Last updated on 2026-02-11

Abstract

A quantitative trading bot, planktonXD, generated over $106,000 in profit on Polymarket within a year by executing more than 61,000 predictions—averaging 170 trades per day. Instead of betting on high-risk "black swan" events, it employed a high-frequency market-making and arbitrage strategy, focusing on small, consistent gains with minimal drawdowns. The bot capitalized on mispriced odds in low-liquidity markets—such as regional esports matches and crypto price predictions—by placing tiny bets on highly improbable outcomes that were statistically undervalued. For example, it achieved returns as high as 23,750% on a VALORANT match and 9,285% on a SOL price prediction by buying nearly worthless shares that surged during market panics or emotional mispricings. Key takeaways include the power of compounding small gains, the necessity of automated tools and API access, and the importance of probability management over high-risk bets. The strategy highlights that success in prediction markets lies not in forecasting outcomes, but in exploiting liquidity gaps and probabilistic edges.

Author: Ma He, Foresight News

Original Title:Making a Profit of $100,000 from 'Mosquito Meat'

Another miracle has occurred on Polymarket.

Through extensive monitoring and疯狂下注 (frenzied betting), an address has managed to turn微利 (small profits) into a net gain of $100,000 in just one year through compound interest.

The address we are reviewing, planktonXD (0x4ffe49ba2a4cae123536a8af4fda48faeb609f71), is an extremely typical high-frequency quantitative trader. Since joining in February 2025, it has generated a net profit of $106,000 through over 61,000 predictions in just one year.


In prediction markets, most people are gambling on "black swan" events or chasing big news, but planktonXD has taken a completely different path: extreme certainty and terrifying execution frequency.

Looking at planktonXD's historical transaction data, the most震撼的 (astounding) aspect is its 61,000 predictions. From February 2025 to February 2026, it conducted approximately 170 transactions per day on average.

This frequency far exceeds the limits of manual human operation, so it can be concluded that this player is using an automated trading script (Bot). It is not "predicting" outcomes but "harvesting" price differences.

A very interesting phenomenon is that planktonXD's "Biggest Win" is only $2,527.4. Compared to its total profit of $100,000, this single largest win appears very "small" (only about 2% of the total profit).

Some retail players always hope to make a big score, betting all their chips on a confidently held judgment.

Winning is good, of course, but losing makes it difficult to get back to the table.

Even if you could win every time you go ALL IN, just one loss would mean a big loss.

Looking at its trading history, it never goes all-in on a single extreme event, nor does it bet on high odds. Its profit curve shows a perfect 45-degree smooth upward trend with almost no major drawdowns. This indicates it uses a market maker strategy: placing orders on both sides of the order book to earn the bid-ask spread, or conducting微型套利 (micro-arbitrage) using price fluctuations between different markets.


It does not always hold positions long-term (Buy and Hold) but frequently enters and exits the market. This "light position, fast turnover" approach极大地降低了 (greatly reduces) single-point risk. Even if an unexpected event occurs in a particular prediction market (like a sudden change in election results), its impact on the total capital pool is minimal.

This quantitative robot does not specialize in trading vertical sectors like weather, as some do, but places bets across multiple sectors: sports, weather, coin prices, politics, etc. It monitors thousands of prediction markets on the platform 24/7, looking for moments of pricing inefficiency.

VALORANT Challengers is a classic实战案例 (practical case study) for this trader.

You can think of it as the "secondary league" or "regional league" in the esports world. Fuego and LYON are professional teams in the Latin American region. Because such matches have a small audience and extremely high information asymmetry, they正好成了 (become perfect) "arbitrage paradises" for quantitative robots.

It bought 3,664.9 shares of Fuego winning at a unit price of 0.1¢.最终这笔交易 (Ultimately, this trade) yielded a return of $874.09, with a return rate reaching a恐怖的 (terrifying) 23,750%!

This is a typical "small position博取大赔率" (betting for big odds with a small position). In markets with extremely poor liquidity or where the public is extremely bearish on a certain option—long-tail markets like the round results of esports matches—it uses a Bot to monitor options that are mispriced to near "zero." It doesn't need to predict who will win; it only needs to know that Fuego's probability of winning is absolutely not just 0.1%. This本质上是在收割 (is essentially harvesting) the market's "extreme emotions" and "lack of liquidity."

When it comes to emotions, coin prices are the most vivid embodiment.

Will the SOL price drop to $130 between January 12-18?

It invested about $16 at a price of 0.7¢ (the market believed the probability of success was less than 1%) and ultimately took away $1,574, with an astonishing return rate of 9,285%.

Why did this "almost impossible" prediction allow it to make big money at that time?

During periods of剧烈波动 (violent fluctuations) in the cryptocurrency market, mainstream predictions tend to be bullish or sideways. planktonXD would capture those "extremely bearish" options priced at 0.1¢ – 1¢ around the clock. These options are like worthless paper in the eyes of ordinary people, but they are extremely cheap insurance in the eyes of quant traders. As long as the market experiences one deep price spike or sudden bad news, these "worthless papers" can instantly surge thousands of times. Additionally, in specific price ranges (e.g., SOL < $40), because the current price is极远 (extremely far) from the predicted price, the order book is often very thin. planktonXD uses automated scripts to place orders in these "no-man's lands," scooping up cheap shares抛出的 (thrown out) due to panic or misoperation. This is essentially acting as a probability搬运工 (porter).

planktonXD's SOL strategy shows that on Polymarket, buying "impossible" outcomes does not mean it believes they will happen, but because the "probability of occurrence" is underestimated by the market. It uses a cost of a few dollars to buy out the market's one-in-ten-thousand possibility of panic. This is typical "antifragile" trading.

planktonXD's success offers three core启示 (revelations) for ordinary retail investors:

The power of compound interest should not be underestimated. Earning 0.5% daily through high-frequency trading yields much more stable returns after a year than betting on a 10x coin. Technology is the killer app. In the Crypto era, quantitative tools and API capabilities are standard for top players. Finally, certainty is greater than odds. In prediction markets,寻找那些概率极高 (finding those opportunities with extremely high probability) (e.g., 90%+ certainty) for small profits is easier to survive on than gambling on 50/50 major events.

After all, the most advanced玩法 (play) in prediction markets is not predicting the future, but managing probability and liquidity.

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Related Questions

QWhat is the main strategy used by the address planktonXD to generate profits on Polymarket?

AThe main strategy used by planktonXD is high-frequency automated trading (using a bot) to capture small, certain profits through market making and micro-arbitrage, rather than predicting outcomes. It focuses on exploiting pricing inefficiencies and liquidity gaps across thousands of prediction markets.

QHow many trades did planktonXD execute over the one-year period, and what was the average daily trading frequency?

APlanktonXD executed over 61,000 trades in one year, with an average of about 170 trades per day.

QWhat was the total profit earned by planktonXD, and how does its biggest single win compare to the total profit?

APlanktonXD earned a total profit of $106,000. Its biggest single win was $2,527.4, which is only about 2% of the total profit.

QCan you provide an example of a specific market where planktonXD achieved an extremely high return on investment?

AOne example is in a VALORANT Challengers esports match between Fuego and LYON. PlanktonXD bought 3,664.9 shares of Fuego winning at a price of $0.001 each, and the trade returned $874.09, achieving a return rate of 23,750%.

QWhat are the three key insights for ordinary retail investors from planktonXD's success?

AThe three key insights are: 1) The power of compounding—small daily gains through high-frequency trading can be more stable than betting on high-risk events. 2) Technology is essential—quantitative tools and API capabilities are standard for top players. 3) Certainty is more important than odds—seeking high-probability, small-profit opportunities is easier than gambling on 50/50 events.

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