How to Systematically Track High-Probability Wallets on Polymarket

How to Find 100X Insider Polymarket Wallets to Copy, by Aleiah (@AleiahLock)

Compiled by Odaily Planet Daily (@OdailyChina); Translator: Asher (@Asher_0210)

An address on Polymarket rolled $35,000 into $442,000, achieving a 12.6x return. Notably, the position was established several hours before major market movements occurred, with the trades largely liquidated before the news spread through mainstream channels. This is not an isolated incident: prior to the public release of news regarding the "Venezuela raid" political event, three addresses positioned themselves in advance and collectively profited $630,000 from the same event.

If this trade occurred in traditional financial markets, people would easily think of information asymmetry. However, in prediction markets, all fund flows and position changes are recorded on a public blockchain, with no hidden accounts or off-chain trades.

Transparency does not mean there are no disparities. The key is not whether transactions can be seen, but whether truly informative signals can be extracted from vast amounts of data.

Many participants in prediction markets still view Polymarket as a traditional betting platform: watching odds, choosing a direction, and placing bets on outcomes. But Polymarket’s underlying structure is fundamentally different from DraftKings or conventional sports betting. All trades occur on-chain, with fund flows, position sizes, and entry/exit times fully transparent and publicly verifiable. The trading patterns of the most accurate and timely addresses are not retroactively inferred—they are real-time, on-chain records.

Polymarket's API is also open. Trading records, market data, and historical trades can be accessed directly by anyone, with no access restrictions.

Therefore, the gap isn’t about who can see the data, but who can extract meaning from it. On-chain information is public, but the real value lies in identifying wallets worth tracking consistently and recognizing behavioral changes before prices fully reflect them.

It’s important to emphasize that not all profitable wallets imply insider information. Some traders possess strong research skills, while others rely on quantitative models and algorithmic advantages. However, when profits consistently align with specific behavioral patterns, certain structural characteristics distinguishable from “luck” can be observed.

Category 1: Combination of new addresses and unusually large bets

It is uncommon for a wallet created only a few days ago with very few transactions to suddenly deploy large amounts of capital in a low-liquidity niche market. Especially in the absence of public catalysts, large concentrated positions often carry stronger informational significance.

Category Two: Highly Specialized Trading Domains

Some addresses do not operate across multiple markets but instead focus long-term on a specific niche, maintaining a consistent and notable win rate within that domain. Rather than spreading their attention across cryptocurrency prices, elections, sports, and other areas, they concentrate their efforts on a single theme and make position decisions with greater decisiveness.

Category Three: Abnormal Changes in Position Size

When an address that has consistently placed moderate bets suddenly significantly increases its position in a particular market, this behavior often signals a shift in conviction. The position itself is a statement—sudden changes in scale typically reflect an upgrade in information or belief.

Category 4: Overly Precise Time Selection

Occasional early positioning can be attributed to coincidence, but if a particular address repeatedly builds positions several hours before major announcements, with consistent directional alignment, this temporal advantage is difficult to explain simply as luck. Once may be random; repeated occurrences suggest a likely informational advantage.

Step 1: Analyze Polymarket's ranking performance

Start by exploring the leaderboard on Polymarket Analytics (link: https://polymarketanalytics.com/traders), sorted by 30-day profit and loss, using consistent recent profitability as your first filter. Focus on wallet addresses that have shown positive overall returns over 30 consecutive days, a win rate above 55%, and total profits significantly exceeding total losses. Also, verify that their trades are concentrated in markets with genuine liquidity, not low-volume prediction events with little to no participation.

The goal of this stage is not to directly determine whether the entity possesses information advantage, but to establish a watchlist of consistently profitable entities. A stable profit record serves as the foundation for subsequent behavioral analysis.

Step 2: Analyze the position structure in the specific event

After completing the initial screening, you can drill down to specific trading events. Visit a trading-active prediction market and review the Top Holders list for that event. Polymarket publicly displays the addresses with the largest current positions, which often indicate stronger conviction.

The key is not whether an address made a single large bet that hit, but whether its behavior is consistent. If a wallet repeatedly appears at the top of holding lists for multiple significant events, and these positions were established before the market fully priced them in, then this repeated appearance itself constitutes a signal.

Hitting a single trade may be coincidental, but repeatedly building large positions early with consistent direction and verified outcomes often indicates a stable edge in their decision-making system.

Step 3: Analyze trading behavior and entry timing

After filtering candidate addresses, further trace their on-chain transaction history, focusing on analysis of entry points, position structure, and holding patterns.

First, observe the entry time. If purchases occur several hours before the official news release and are repeated multiple times, the time advantage itself becomes a significant factor; whereas entering after media coverage is more likely merely following the information.

Second, analyze the position-building approach. Experienced traders typically build positions in batches and add to them gradually, while wallets with strong informational insights often complete concentrated positioning rapidly within a short time frame, due to their limited window of opportunity.

Additionally, pay attention to holding periods. Some high-quality addresses choose to exit during the middle phase of market momentum rather than waiting for the extreme volatility at the end, indicating their goal is to lock in the main trend rather than chase marginal profits.

Finally, observe its trading range. Addresses that are highly focused and long-term dedicated to a single niche are more likely to develop stable informational advantages; addresses that frequently switch between sectors are more likely to rely on market sentiment rather than specific domain expertise.

After mastering basic screening methods, what truly sets apart top performers is a deeper breakdown of capital behavior details.

First, focus on exit behavior, not just entry timing. Addresses with information advantages often not only position themselves in advance but also proactively reduce holdings before potential negative catalysts emerge. When a large address with a long-term, stable position suddenly makes a significant reduction without clear catalysts, the informational value of this action often exceeds that of its original purchase. Especially when the reduction reaches a substantial proportion, this shift itself serves as a signal.

Second, wallet clustering can be performed using on-chain data. Relationships between addresses are not entirely untraceable. Common funding sources, similar gas usage patterns, and transactions occurring in rapid succession may reveal connections between addresses. Many seemingly "new" accounts can often be traced back to a long-active legacy address through two to three fund transfers. Tracking the flow of funds can help identify new, potentially high-quality accounts before the market takes notice.

Additionally, pay attention to unusual volume changes in less popular markets. If a market with typically low daily trading volume suddenly experiences a significant influx of capital without any public news, this structural volume surge often indicates that some participants have already acted ahead of the curve. Analyzing the specific addresses driving the volume change can help build new watchlists.

Finally, on-chain behavior can be cross-verified with external public information. The so-called "pizza index" once inferred potential military operations through anomalous changes in pizza orders near the Pentagon. Similarly, flight tracking data, social media activity of key individuals, and public schedule adjustments may provide corroborating or counter-evidentiary support for on-chain position behavior. The correlation between on-chain fund flows and real-world signals often enhances the reliability of conclusions.