170 high-frequency trades per day on average, how to turn "pocket change" into a $100,000 profit?

Author: Mahe, Foresight News

Original Title: Mosquito Meat, Roll Out $100,000 Profit

Once again, a miracle has appeared on Polymarket.

Through widespread monitoring, frantic betting, and just one year, a single address earned a net profit of $100,000 through small margins and compound interest.

The address we’re analyzing, planktonXD (0x4ffe49ba2a4cae123536a8af4fda48faeb609f71), is a highly typical high-frequency quantitative trader. Since joining in February 2025, in just one year, it has made over 61,000 predictions, rolling up a net profit of $106,000.

In prediction markets, most people are betting on “black swan” events or chasing big news, but planktonXD takes a completely different approach: extreme certainty and terrifying execution frequency.

Looking at planktonXD’s historical trading data, the most shocking aspect is its 61,000 predictions. From February 2025 to February 2026, it averaged about 170 trades per day.

This frequency far exceeds human manual operation limits, confirming that the trader uses automated trading scripts (bots). It’s not about “predicting” outcomes but “harvesting” price differences.

An interesting phenomenon is that planktonXD’s “biggest single profit” is only $2,527.40. Compared to its total profit of $100,000, this single largest gain appears very “small” (only about 2% of total profit).

Some retail traders always hope to make a big win, confidently betting all their chips on their judgment.

Winning is great, but losing makes it hard to get back to the table.

Even if every all-in bet wins, just one loss can wipe out everything.

Reviewing its trading history, it never all-ins on a single extreme event, nor does it bet high leverage. Its profit curve shows a perfect 45-degree smooth upward slope, with almost no major drawdowns. This indicates it employs a market-making strategy: placing orders on both sides of the order book to earn the bid-ask spread, or exploiting price fluctuations across different markets for micro-arbitrage.

It doesn’t always hold long-term positions (buy and hold), but frequently enters and exits the market. This “light position, quick turnover” approach greatly reduces single-point risk. Even if an unexpected event occurs in a prediction market (such as a sudden change in election results), its overall capital pool is minimally affected.

This quantitative bot doesn’t specialize in vertical sectors like weather, but bets across multiple sectors—sports, weather, crypto prices, politics. It monitors thousands of prediction markets across platforms 24/7, seeking moments when pricing fails.

VALORANT Challengers is a classic case for this trader.

Think of it as the “secondary league” or “regional league” in esports. Fuego and LYON are professional teams from Latin America. Due to small audiences and high information asymmetry, these markets become a “arbitrage paradise” for quantitative bots.

It bought 3,664.9 shares of Fuego’s victory at a price of 0.1¢, ultimately earning $874.09 from this trade, with a staggering return of 23,750%!

This is a typical “small position, high odds” strategy. In illiquid or highly pessimistic long-tail markets (like match outcome bets in esports), it uses bots to monitor those mispriced options near zero. It doesn’t need to predict who will win; it only needs to know that Fuego’s win probability is definitely higher than 0.1%. Essentially, it’s harvesting market “extreme emotions” and “liquidity shortages.”

Speaking of emotions, crypto prices reflect this most vividly.

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

It invested about $16 at a price of 0.7¢ (market perceives less than 1% chance of success), ultimately earning $1,574, with a return of 9,285%.

Why could such an “almost impossible” prediction make it so much money?

During sharp crypto market volatility, mainstream predictions tend to be bullish or sideways. planktonXD constantly captures those “extremely bearish” options priced at 0.1¢–1¢. These options seem worthless to ordinary people, but to quant traders, they are extremely cheap insurance. If the market experiences a deep spike or sudden negative news, these “worthless” options can skyrocket a thousandfold. Moreover, in certain price ranges (like SOL < $40), since the current price is far from the predicted price, order books are often very thin. planktonXD uses automation scripts to place orders in these “no-man’s land,” eating up cheap shares thrown out due to panic or misoperation—essentially, it’s a probability transporter.

planktonXD’s SOL strategy shows that on Polymarket, buying “impossible” events doesn’t mean it believes they will happen, but that the market underestimates their probability. It spends a few dollars to buy out a one-in-ten-thousand panic possibility, exemplifying “antifragile” trading.

The success of planktonXD offers three core lessons for ordinary retail traders:

The power of compound interest should not be underestimated. Earning 0.5% daily through high-frequency trading yields far more stable returns over a year than betting on a 10x coin. Technology is essential—quant tools and API access are standard for top players in the crypto era. Lastly, certainty outweighs odds. In prediction markets, finding small profit opportunities with very high probabilities (like over 90%) is easier to survive than betting on big events with 50/50 odds.

After all, the highest-level gameplay in prediction markets isn’t about predicting the future but managing probabilities and liquidity.