In-Depth Analysis of Polymarket: 27,000 Trades by the Top 10 Profitable Whales in December Reveal the Truth Behind “Smart Money”: Extremely High Win Rates Are Masked by Large Numbers of Unsettled “Zombie Orders,” with Actual Win Rates Slightly Above Random; Hedging Arbitrage Is Far More Complex Than Imagined, and Blind Imitation Can Lead to Losses.
(Background: Heaven, Earth, Humanity — Why Did Prediction Markets Take Nearly 40 Years to Explode?)
(Additional Context: 26 Predictions About the Development of Prediction Markets in 2026)

Table of Contents

• SeriouslySirius: 73% Win Rate Masked by “Zombie Orders” and a Complex Quantitative Hedging Network
• DrPufferfish: Turning Small Probabilities into Large Probabilities — The Art of “Risk-Reward” Management
• 3. gmanas: High-Frequency Automated Assembly Line
• 4. Hunter simonbanza: Treating Prediction Probabilities Like “K-Line” Swing Trading
• 5. Whale gmpm: Asymmetric Hedging Strategy Using “Large Positions” to Capture Certainty
• 6. Workaholic swisstony: “Ant Moving House” High-Frequency Arbitrage
• 7. Outlier 0xafEe: The “Pop Culture Prophet” with a Unique Approach
• 8. Manual Hedging Player 0x006cc: Upgrading from Simple to Complex Hedging Strategies
• 9. Cautionary Tale RN1: When “Hedging” Turns into a “Loss Formula”
• 10. Gambler Cavs2: Unilateral Heavy Positions in Hockey, Luck Over Strategy
• 5 Harsh Truths After Disenchanting “Smart Money”

Recently, the popularity of prediction markets continues to rise, especially as the arbitrage strategies of “smart money” are hailed as the gold standard. Many have begun to imitate and experiment, as if a new wave of wealth creation is underway.

But behind the hype, how effective are these seemingly clever and reasonable strategies? How are they actually executed? PANews conducted an in-depth analysis of 27,000 trades by the top ten whales in December on Polymarket, seeking the true nature of their profitability.

The analysis revealed that although many of these “smart money” traders employ hedging arbitrage strategies, these are far more complex than the simple hedges often described on social media. The actual strategies involve sophisticated combinations, such as exploiting “over/under” and “win/lose” rules in sports betting for hedging.

Another key finding is that the extremely high win rates behind these whales’ long-standing positions are largely due to a large number of “zombie orders” that remain unsettled, artificially inflating their apparent success. The real win rates are much lower than the historical averages.

Next, PANews will use actual cases to reveal the real operations of these “smart money” players.

SeriouslySirius: 73% Win Rate Masked by “Zombie Orders” and a Complex Quantitative Hedging Network

SeriouslySirius is the address ranked first in December, with a profit of about $3.29 million in that month and a total historical profit of $2.94 million. If only considering completed orders, his win rate reaches 73.7%. However, the reality is that he still holds 2,369 open orders, with 4,690 orders settled so far.

Among these, 1,791 open orders are actually complete failures, but the user has not closed them individually. On one hand, this saves effort and transaction fees. On the other hand, since most of his closed orders are profitable, the historical settled data shows an extremely high win rate. When considering these unsettled “zombie orders,” his true win rate drops to 53.3%, only slightly above random chance.

In his actual trading, about 40% of orders are hedges on the same event in multiple directions. But these hedges are not simple “yes” + “no” bets. For example, in an NBA game between the 76ers and Mavericks, he bought 11 different bets, including Under (small score), Over (large score), 76ers (home), Mavericks (away), ultimately earning $1,611. During this process, he also employed probabilistic arbitrage strategies, such as buying the 76ers’ victory at a 56.8% probability and Mavericks’ victory at 39.37%, with a combined cost of about 0.962, ensuring a guaranteed profit regardless of the outcome. He ultimately profited $17,000 from this game.

However, this strategy is not always profitable. For example, in a Celtics vs Kings game, he participated in 9 different bets but ended up losing $2,900.

Additionally, there are many cases where the capital allocation is heavily skewed, such as placing bets on both sides but with over tenfold difference in invested funds. This likely results from low market liquidity, indicating that while arbitrage opportunities appear attractive, liquidity can be a major obstacle. Opportunities may exist, but achieving balanced hedges on both sides is not guaranteed.

Furthermore, since these are automated trades, buy and sell actions can often lead to significant losses.

Nevertheless, the reason why SeriouslySirius can achieve large profits through this strategy is primarily due to disciplined position management, with a risk-reward ratio of about 2.52. This allows him to profit despite a relatively low true win rate.

It’s also worth noting that this strategy is not always profitable. Before December, this address’s profit and loss situation was not optimistic, with long periods near break-even and a maximum loss of around $1.8 million. Now, with a more mature strategy, it remains uncertain whether such profitability can be sustained.

DrPufferfish: Turning Small Probabilities into Large Probabilities — The Art of “Risk-Reward” Management

DrPufferfish ranks second in profitability for December, with a profit of about $2.06 million, and boasts an even more impressive historical win rate of 83.5%. However, considering his large number of “zombie orders,” his effective win rate is around 50.9%. His strategy differs significantly from SeriouslySirius. While he also has about 25% of orders as hedges, these are not opposite bets but diversified bets.

For example, in a Major League Baseball championship prediction, he bought 27 low-probability teams, with combined probabilities exceeding 54%. This approach effectively turns small-probability events into large-probability outcomes.

The main reason for his huge gains is his ability to control the risk-reward ratio. Take Liverpool, for instance, a team he favors; he predicted their results 123 times, earning about $1.6 million. On average, profitable predictions yielded about $37,200, while losing predictions averaged about $11,000. Most losing bets are sold early to limit position losses.

This operational approach results in an overall risk-reward ratio of 8.62, indicating high profitability potential. But overall, his strategy is not simple arbitrage; it involves professional prediction analysis and strict position management. Notably, most of his hedging trades are in a loss state, totaling a net loss of $2.09 million, suggesting that hedging is mainly used as insurance.

( 3. gmanas: High-Frequency Automated Assembly Line

Ranked third, gmanas shares similarities with DrPufferfish, achieving a total profit of about $1.97 million in December. His true win rate is close to 51.8%, similar to DrPufferfish. His trading frequency is higher, with over 2,400 predictions completed, indicating an automated execution strategy. His betting style is similar to the previous address, so details are omitted here.

) 4. Hunter simonbanza: Treating Prediction Probabilities Like “K-Line” Swing Trading

Ranked fourth, simonbanza is a professional prediction hunter. Unlike the previous addresses, he does not use hedging orders at all. His realized profit is about $1.04 million, with only $130,000 in unsettled zombie orders. Although his capital and trading volume are modest, his true win rate is the highest at approximately 57.6%. Among settled orders, his average profit is about $32,000, with an average loss of about $36,500. The profit-loss ratio is not high, but his high win rate yields good overall returns.

He also has very few zombie orders—only 6—because he usually does not wait for event completion but exploits probability fluctuations for profit. Simply put, he takes profits when they appear and does not hold out for final results.

This represents a unique prediction market investment approach, where probability changes resemble stock market fluctuations. The specific logic behind his high win rate remains unknown, as it is his exclusive secret.

5. Whale gmpm: Asymmetric Hedging Strategy Using “Large Positions” to Capture Certainty

Ranked fifth, gmpm’s December profit ranking is fifth, but his total historical profit exceeds others at around $2.93 million. His true win rate is about 56.16%, relatively high. His approach is similar to the fourth-ranked address but with a unique core strategy.

For example, he often places bets on both sides of the same event, but his strategy is not to arbitrage between the two. Instead, he invests more capital on the side with higher probability and less on the lower probability side. This creates a hedge where, when the high-probability side wins, the position is large, but losses from low-probability events are limited.

In practice, this is a more advanced hedging strategy that combines probabilistic judgment with loss reduction, rather than relying solely on “yes” + “no” < 1 arbitrage.

6. Workaholic swisstony: “Ant Moving House” High-Frequency Arbitrage

The sixth address, swisstony, is a super high-frequency arbitrage trader, with the highest trading volume among these addresses—5,527 trades. Despite earning over $860,000, the average profit per trade is only $156. His style resembles “ant moving house,” frequently buying all odds of a match.

For example, in a Jazz vs Clippers game, he bought 23 different odds. Due to small investment amounts, his capital distribution is relatively balanced, enabling some hedging effect.

However, this strategy heavily depends on precise buy-in details. For instance, the combined “yes” + “no” bets often exceed 1, which is problematic. His hedging orders often result in total bets exceeding 1, leading to inevitable losses. Nonetheless, with a reasonable risk-reward ratio and win rate, his overall profit remains positive.

7. Outlier 0xafEe: The “Pop Culture Prophet” with a Unique Approach

The seventh address, 0xafEe, is a low-frequency, high-win-rate trader. His trading frequency is about 0.4 trades per day, with a real win rate of 69.5%.

His completed orders have yielded about $929,000, with minimal zombie orders—only about $8,800 unrealized losses. He does not hedge but focuses solely on predictions, mainly about Google search trends and pop culture topics, such as “Will Pope Leo XIV become the most searched person on Google this year?” or “Will Gemini 3.0 be released before October 31?” His unique analytical approach results in a very high success rate, making him an outlier among top whales outside sports.

8. Manual Hedging Player 0x006cc: Upgrading from Simple to Complex Hedging Strategies

Ranked eighth, 0x006cc’s net profit is about $1.27 million, with a true win rate of approximately 54%. Compared to earlier manual traders, his trading frequency is low—about 0.7 trades per day. Early on, he likely employed simple manual hedging strategies.

Since December, he has upgraded to more complex hedging methods. His trading history suggests that as more traders understand hedging, strategies are evolving.

9. Cautionary Tale RN1: When “Hedging” Becomes a “Loss Formula”

Ninth, RN1 is the only address among the top ten in December with an overall loss. His realized profit is about $1.76 million, but unrealized losses reach $2.68 million, totaling a net loss of $920,000. As a cautionary example, there are many lessons here.

First, his true win rate is only 42%, the lowest among these addresses, with a risk-reward ratio of 1.62. These figures suggest his strategy is unprofitable overall.
A closer look reveals that he is a clear arbitrage trader, but many of his hedging trades, while satisfying “yes” + “no” < 1, tend to involve larger bets on the lower-probability side and smaller bets on the higher-probability side, leading to unbalanced positions. When high-probability events occur, this results in real losses.

10. Gambler Cavs2: Unilateral Heavy Positions in Hockey, Luck Over Strategy

Tenth, Cavs2 is a gambler who prefers unilateral heavy positions, mainly in NHL hockey. His total profit is about $630,000, with a win rate of 50.43% and a relatively low hedge ratio of 6.6%. The data is average, and luck plays a significant role, as he hit some high-yield single-game results. His strategy offers limited practical insight.

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( “Disenchanting” Smart Money: 5 Harsh Truths

After deep analysis of these “smart money” traders, PANews summarizes the reality behind the “wealth stories” of prediction markets.

1. “Hedging arbitrage strategies” are far more complex than simply meeting probability conditions. Under fierce market competition and liquidity constraints, they can turn into counterproductive loss formulas. Blind imitation is not advisable.

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2. “Copy trading” in prediction markets also seems ineffective, mainly because the ranking or win rate often relies on “distorted” historical profit data. Behind such data, many “smart money” traders are not truly “smart.” True win rates above 70% are rare; most are close to coin flips.

Moreover, current market depth is limited, and arbitrage opportunities may only accommodate small capital entries. Copy traders can easily be squeezed out.

3. Managing risk-reward ratios and position sizes is more important than chasing high win rates. Successful addresses tend to excel at managing risk-reward, with some like gmpm and DrPufferfish adjusting their exits based on probability trends to reduce losses and improve ratios.

4. The real secret lies beyond “mathematical formulas.” Many social media interpretations of “arbitrage formulas” seem reasonable but are often superficial. In practice, these traders rely on superior judgment of certain events or unique cultural analysis models. Their decision algorithms are the key to their success. For users lacking such algorithms, prediction markets remain a “dark forest.”

5. The profit scale of prediction markets remains small. The top earners in December only made around $3 million. Compared to the overall crypto derivatives market, the profit potential appears capped. For those dreaming of overnight riches, the market size is still limited. This niche, highly specialized and small-scale, may not attract institutional players, possibly explaining why prediction markets have not grown larger.

In the seemingly golden prediction market of Polymarket, the so-called “god-tier whales” are mostly just surviving gamblers or diligent “brick movers.” True wealth secrets are not hidden in inflated win rate rankings but in the algorithms used by a few top players who bet with real money after filtering noise.

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