Polymarket Smart Money Panorama: 26 Long-Term Trackable Addresses (Categorized by Sector)

marsbitPublished on 2026-03-31Last updated on 2026-03-31

Abstract

This article profiles 26 high-performing "smart money" addresses on Polymarket, categorized by their expertise in five distinct prediction market sectors. The selection criteria focused on proven Profit and Loss (PNL), a diversified winning structure (not reliant on a single bet), and high transaction volume to distinguish informed speculation from arbitrage. The addresses are broken down as follows: * **Politics & Geopolitics (5 addresses):** Experts in long-cycle macro events like Fed rates, US elections, and Middle Eastern geopolitics. They often bet against consensus (NO) in low-probability markets, achieving high ROI. * **Weather (6 addresses):** Specialists in temperature prediction markets for specific cities. Strategies range from high-frequency, small bets across thousands of markets to focused, high-conviction wagers. * **Tech (5 addresses):** Focused on Big Tech and AI product timelines (e.g., Google, OpenAI). They typically target high-probability outcomes or use a high-volume, low-cost approach on undervalued options. * **Culture (5 addresses):** Experts in movie box office results and Twitter-related markets. Strategies include betting on high-probability outcomes or taking contrarian, high-odds positions in low-probability markets. * **Sports (5 addresses):** Specialists in specific leagues like UFC, Soccer, and Tennis. They excel at identifying mispriced odds, often in medium-probability markets, and hold positions until settlement. A key warning i...

Original Author: Changan I Biteye Content Team

Biteye's previous article, "Polymarket Smart Money Copy Trading Guide: From Screening Addresses to Practical Tips, Everything Explained," discussed how to find smart money, how to screen it, how to copy trades, and where the pitfalls lie - judging whether an address is worth following mainly depends on three dimensions:

  • PNL: Verify they have actually made money
  • Profit Structure: Whether profits are diversified or reliant on a single bet
  • Number of Trades: Distinguish between discretionary trading and arbitrage

The most common question received was: "But can you just give a few smart money addresses?"

Honestly, truly "smart money" addresses are extremely scarce.

These 26 addresses were meticulously selected by the editor through countless late-night reviews, based on their keen sense in five sectors: politics, weather, technology, culture, and sports.

They are no longer just addresses; they are more like a group of "hunters" with special intuition in different fields.

🏛 Politics & Geopolitics

1️⃣ Trader: wokerjoesleeper

🔗 Address: 0x63d43bbb87f85af03b8f2f9e2fad7b54334fa2f

📖 Intro: Ranked 73rd overall in Politics, 7th overall in Economy, 9th overall in Fed Rates, total profit $900K. 93% of positions bet NO, specializing in low-probability markets; 81% win rate in this range, ROI as high as +227%. Focuses on long-cycle macro events like Fed rate decisions and Iranian politics.

2️⃣ Trader: Frank0951

🔗 Address: 0x40471b34671887546013ceb58740625c2efe7293

📖 Intro: Ranked 7th overall in Hormuz, 62.8% win rate, total profit $290K. Spans both esports and geopolitics sectors, main positions bet on oil prices and Middle East局势, also deeply involved in CS2, LOL等 esports markets. Actively takes profits, doesn't hold positions indefinitely. Stable profits in both sectors, one of the few addresses on the list capable of cross-sector operations.

3️⃣ Trader: cowcat

🔗 Address: 0x38e59b36aae31b164200d0cad7c3fe5e0ee795e7

📖 Intro: Ranked 184th overall in Geopolitics, win rates over 88% in Iran and Middle East sub-sectors, total profit nearly $200K. Focuses on Middle East geopolitics, heavily bets on low-probability events the market thinks are almost impossible; achieved a 39% actual win rate in markets with an implied probability of only 8%, Longshot ROI as high as +117%. A rare focused, heavy-position player in the politics sector.

4️⃣ Trader: ScottyNooo

🔗 Address: 0xbacd00c9080a82ded56f504ee8810af732b0ab35

📖 Intro: Ranked 43rd overall in Politics, 6th overall in Middle East sub-sector, total profit over $1.3M, $970K profit from Trump-related markets alone. Average bet nearly $13K, 58.8% win rate, heavily bets on large political and geopolitical markets. Entered in May 2025, achieved seven-figure returns in less than a year.

5️⃣ Trader:How.Dare.You

🔗 Address: 0x4bbe10ba5b7f6df147c0dae17b46c44a6e562cf3

📖 Intro: Ranked 4th overall in Foreign Policy (Politics), 6th overall in Ukraine, ranked 1st in Trump-Zelenskyy sub-sector with 100% win rate, total profit $277K. Focuses on high-certainty markets in the Ukraine and foreign policy direction, heavily bets on high-probability outcomes. Average bet over $12K, 70.5% win rate. One of the players with the strongest sense of direction in the politics sector.

💰 Weather

1️⃣ Trader: HondaCivic

🔗 Address: 0x15ceffed7bf820cd2d90f90ea24ae9909f5cd5fa

📖 Intro: Ranked 12th overall in Weather, 3rd overall in Daily Temperature, 85.7% win rate, total profit $48K. Focuses on temperature-related markets, over 3000 positions, average bet $1,478. Accumulates advantage by frequently covering temperature markets in multiple cities; maintains a 100% win rate in the Hong Kong sub-sector to date.

2️⃣ Trader: ikik111

🔗 Address: 0x57ee70867b4e387de9de34fd62bc685aa02a8112

📖 Intro: Total profit of $50K in Weather, covers over 3300 different markets, average bet only $37. Doesn't rely on high win rate; 38% win rate paired with a 3.54 profit/loss ratio. Uses extremely low cost to buy分散头寸 in many temperature markets, wins through volume. A typical high-frequency, volume-based strategy in the weather sector.

3️⃣ Trader: Maskache2

🔗 Address: 0x1f66796b45581868376365aef54b51eb84184c8d

📖 Intro: Total profit $27K in Weather, win rate only 30%, but profit/loss ratio reaches 3.74. Covers many small losses with a few big wins. Has insights into Seoul temperature markets; single highest profit $8,221. Found pricing discrepancies in cities other traders pay less attention to. Entered in January 2026, quickly achieved positive returns within three months.

4️⃣ Trader: JoeTheMeteorologist

🔗 Address: 0x1838cca016850ac7185a9b149fe7d0bd2d6629b4

📖 Intro: Formerly a weather forecaster, now trades weather markets on Polymarket. $29K profit in Weather, single highest profit $7,056 in Seoul temperature market, average bet $42. Accumulates profits by frequently covering 2100+ different markets, total profit $77K. Also participates in sports and esports besides weather. A rare balanced player crossing sectors within the weather category.

5️⃣ Trader: BeefSlayer

🔗 Address: 0x331bf91c132af9d921e1908ca0979363fc47193f

📖 Intro: Total profit $49K in Weather, accounting for 99% of overall收益, 67% win rate. Covers temperature markets in multiple US cities like NYC, Seattle, Chicago, Dallas. Average bet $198, entered less than half a year ago, curve持续向上. One of the most focused players in the weather sector.

6️⃣ Trader: Varyage

🔗 Address: 0xd75d96a23515172778d3281f53c9180b985100c8

📖 Intro: Ranked 47th overall in Weather, 68th overall in NYC sub-sector, 78% win rate, total profit $20K, account age over two years. Only trades 2 bets per day, average bet $238. Focuses on temperature markets in NYC and other cities. Slow pace, wide coverage. A rare low-frequency, steady player in the weather sector.

📱 Technology

1️⃣ Trader: George.Smiley

🔗 Address: 0x2110ba2a1e18840109482ff4ddc547baeff45850

📖 Intro: Ranked 14th overall in AI, 14th overall in Google markets, 76.1% win rate, total profit $28K. Deeply involved in AI product release timelines, heavily bets on specific product timelines like Gemini, OpenAI. Focuses on high-certainty markets, avoids low-probability markets entirely.

2️⃣ Trader: Optimus.

🔗 Address: 0xd5b97d08ec6098407bfbf66c2786ccc9967fe44e

📖 Intro: Ranked 114th overall in Technology, 62nd overall in Elon Musk markets, bet on 1471 markets, 2500 trades, total profit $73K. Small,分散仓位, average bet $780, YES and NO bets roughly equal, bets on judgment not direction. Spans politics, tech, geopolitics multiple sectors, win rate over 60% in each. A rare all-around balanced player.

3️⃣ Trader: BobInvestments

🔗 Address: 0x41816fc1ebdfeb33f6356f2655ab499253b3de86

📖 Intro: Ranked 35th overall in Big Tech, 75% win rate, total profit $24K. Specializes in buying cheap shares in low-probability markets, average entry price only $0.16. Bets on options the market thinks are almost impossible, achieving a 52% win rate far exceeding the implied probability. Extremely small positions, very high frequency, accumulates positive expected value through大量低价买入.

4️⃣ Trader: DerDon

🔗 Address: 0xf797d4d1c038d1eb0593edae0e66bf8e4b2e0bf

📖 Intro: Ranked 68th overall in Big Tech, 179th overall in Technology, bet on 2864 markets, 62.5% win rate, total profit $38K. 75% win rate in Tech is his most stable home ground. Small,分散仓位, average bet $372, trades consistently year-round. Major geopolitical events are the main source of losses. When copying, focus on his tech positions.

5️⃣ Trader: Mujurry

🔗 Address: 0x5ecde7348ea5100af4360dd7a6e0a3fb1d420787

📖 Intro: Ranked 20th overall in Technology, 28th overall in AI, 10th overall in Google, 75.8% win rate, win rate in tech-related sectors稳定在80%以上, total profit $170K. Over 200 trades per day, extremely high frequency, also actively takes profits, doesn't hold positions indefinitely.

🎭 Culture

1️⃣ Trader: Big.Chungus

🔗 Address: 0x06dcaa14f57d8a0573f5dc5940565e6de667af59

📖 Intro: Ranked 18th overall in Culture, 3rd overall in Movie Box Office, bet on 1500 markets, 2500 trades, 73.7% win rate. Mainly bets on high-probability markets, average entry price $0.82. Amplifies the win rate advantage through大量分散布局复利. Buying frequency is nearly twice selling frequency, typical style of持续加仓、让利润奔跑.

2️⃣ Trader: TheRedChip

🔗 Address: 0xdf6da574f8b0c0ce5e01ddb1c5a49b87993e9c5c

📖 Intro: Ranked 23rd overall in Tweet Markets, 22nd overall in Elon Musk related markets, bet on 1600 markets, win rate only 45%, but used a risk/reward ratio of 2.91 to achieve total profit of $100K. Specializes in heavily betting YES in low-probability markets (win rate below 15%), covering many small losses with a few big high-odds wins. A typical逆向博赔率 style.

3️⃣ Trader: GUHHH

🔗 Address: 0x033dc6e3e3e0a3ae55402576990392ae910aaf05

📖 Intro: Ranked 20th overall in Movie Box Office, bet on 1200 markets, 77.9% win rate, total profit $68K. Strategy is opposite to most: 69% of positions bet NO, specifically shorting overpriced options in the market. Focuses on high-certainty markets with win rates above 70%, accumulates slowly through stable positive expected value, avoids low-probability冷门.

4️⃣ Trader: BeN

🔗 Address: 0x668d85d791049bf0100e557a72c7ed4dc97297d2

📖 Intro: Ranked 13th overall in Music, 141st overall in Culture, 67.3% win rate, total profit $40K. Focuses on high-probability markets, large positions concentrated in markets with win rates above 90% to harvest the final段收益. Maximum drawdown only $4,446, one of the addresses with the most stable risk control.

5️⃣ Trader: pol76

🔗 Address: 0x36e7e560c4d4cf32926906d939a18cf91f8a0b6b

📖 Intro: Ranked 43rd overall in Tweet Markets, 72.9% win rate, total profit $44K. 83% of positions bet NO, focuses on high-probability markets, achieving a 96% win rate in this range, the stable main source of profit. Spans politics, culture, technology multiple sectors, win rate above 65% in each.

⚽ Sports

1️⃣ Trader: CKW

🔗 Address: 0x92672c80d36dcd08172aa1e51dface0f20b70f9a

📖 Intro: Ranked 66th overall in Sports, 19th overall in UFC, 26th overall in MLB, total trading volume over $74M. Good at identifying overpriced options in the market, bets NO反向 in low-probability markets. Average bet nearly $16K, long holding periods, rarely sells mid-way.

2️⃣ Trader: ewelmealt

🔗 Address: 0x07921379f7b31ef93da634b688b2fe36897db778

📖 Intro: Ranked 20th overall in Soccer, 12th overall in La Liga, entered only in February 2026, profit of $860K from 67 markets in 19 days. Average bet nearly $44K, never sells mid-way, holds all positions until settlement. Specializes in medium-probability markets (30-70% range) with接近100% win rate. A typical重仓慢打、极度自信型选手.

3️⃣ Trader: EFFICIENCYEXPERT

🔗 Address: 0x8c0b024c17831a0dde038547b7e791ae6a0d7aa5

📖 Intro: Ranked 15th overall in Esports, 14th overall in LOL, bet on 2700 markets, trading volume $30M. Accumulated $580K net profit by covering many markets and turning small advantages into gains. Recent win rate has declined;建议先观察近期表现 before copying.

4️⃣ Trader: synnet

🔗 Address: 0x8e0b7ae246205b1ddf79172148a58a3204139e5c

📖 Intro: Ranked 17th overall in Tennis, 1st overall in ATP, average entry price only $0.30, 31.7% win rate but net profit $290K. Focuses on tennis longshot bets, one win covers multiple losses. Performance drops significantly outside tennis.

5️⃣ Trader: middleoftheocean

🔗 Address: 0x6c743aafd813475986dcd930f380a1f50901bd4e

📖 Intro: Ranked 99th overall in Sports, 83.1% win rate in football (soccer), bet on 1700 markets, total profit $470K. Main profits concentrated in medium-probability markets, avoids low-probability冷门. Generally not worth following outside sports.

Final Notes

If a master in the sports sector switches to political markets, their win rate might not transfer. When copy trading, identify the sector they are good at; don't blindly follow across types.

Every address on this list participates in more than one sector. Smart money in culture might bet on geopolitics; experts in sports might touch crypto markets, but their performance outside their home ground is often much worse.

If you use a tool to copy all trades directly, profits from their strong sector could be offset by losses in other sectors. Before copying, check where their home ground is and only follow positions in that direction.

Addresses are for reference, not answers. Smart money gives you direction, but you still need to make your own judgments.

All addresses in this article are for reference only and do not constitute any investment advice. Prediction markets carry the risk of loss of principal; please participate within your承受范围.

Related Questions

QWhat are the three main dimensions to evaluate whether an address is worth following on Polymarket according to the article?

AThe three main dimensions are PNL (to verify actual profits), profit structure (whether profits are diversified or rely on a single big win), and number of trades (to distinguish between subjective trading and arbitrage).

QWhich address is described as a specialist in Middle East geopolitics, with a strategy of heavily betting on low-probability events the market deems almost impossible?

AThe address 0x38e59b36aae31b164200d0cad7c3fe5e0ee795e7 (cowcat) is described as such, with over 88% win rates in Iran and Middle East sub-markets and a Longshot ROI of +117%.

QIn the Weather category, which trader uses a high-frequency, high-volume strategy with a low average bet size of $37 to profit from many small, dispersed positions?

AThe trader with the address 0x57ee70867b4e387de9de34fd62bc685aa02a8112 (ikik111) uses this strategy, achieving a 38% win rate with a high profit-to-loss ratio of 3.54.

QWhat is a key piece of advice the article gives about following these 'smart money' addresses across different prediction markets?

AThe key advice is to follow an address only in its area of expertise (its 'home field') and not to blindly follow its trades across different market types, as performance often drops significantly outside their specialty.

QWhich trader in the Tech category is noted for having an extremely high frequency of over 200 trades per day and actively taking profits instead of holding positions to expiration?

AThe trader with the address 0x5ecde7348ea5100af4360dd7a6e0a3fb1d420787 (Mujurry) fits this description, with a 75.8% win rate and $170k in total profit from tech-related markets.

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While the concept of Agent S is fundamentally innovative, specific information about its creator remains elusive. The creator is currently unknown, which highlights either the nascent stage of the project or the strategic choice to keep founding members under wraps. Regardless of anonymity, the focus remains on the framework's capabilities and potential. Who are the Investors of Agent S? As Agent S is relatively new in the cryptographic ecosystem, detailed information regarding its investors and financial backers is not explicitly documented. The lack of publicly available insights into the investment foundations or organisations supporting the project raises questions about its funding structure and development roadmap. Understanding the backing is crucial for gauging the project's sustainability and potential market impact. How Does Agent S Work? At the core of Agent S lies cutting-edge technology that enables it to function effectively in diverse settings. Its operational model is built around several key features: Human-like Computer Interaction: The framework offers advanced AI planning, striving to make interactions with computers more intuitive. By mimicking human behaviour in tasks execution, it promises to elevate user experiences. Narrative Memory: Employed to leverage high-level experiences, Agent S utilises narrative memory to keep track of task histories, thereby enhancing its decision-making processes. Episodic Memory: This feature provides users with step-by-step guidance, allowing the framework to offer contextual support as tasks unfold. Support for OpenACI: With the ability to run locally, Agent S allows users to maintain control over their interactions and workflows, aligning with the decentralised ethos of Web3. Easy Integration with External APIs: Its versatility and compatibility with various AI platforms ensure that Agent S can fit seamlessly into existing technological ecosystems, making it an appealing choice for developers and organisations. These functionalities collectively contribute to Agent S's unique position within the crypto space, as it automates complex, multi-step tasks with minimal human intervention. As the project evolves, its potential applications in Web3 could redefine how digital interactions unfold. Timeline of Agent S The development and milestones of Agent S can be encapsulated in a timeline that highlights its significant events: September 27, 2024: The concept of Agent S was launched in a comprehensive research paper titled “An Open Agentic Framework that Uses Computers Like a Human,” showcasing the groundwork for the project. October 10, 2024: The research paper was made publicly available on arXiv, offering an in-depth exploration of the framework and its performance evaluation based on the OSWorld benchmark. October 12, 2024: A video presentation was released, providing a visual insight into the capabilities and features of Agent S, further engaging potential users and investors. These markers in the timeline not only illustrate the progress of Agent S but also indicate its commitment to transparency and community engagement. Key Points About Agent S As the Agent S framework continues to evolve, several key attributes stand out, underscoring its innovative nature and potential: Innovative Framework: Designed to provide an intuitive use of computers akin to human interaction, Agent S brings a novel approach to task automation. Autonomous Interaction: The ability to interact autonomously with computers through GUI signifies a leap towards more intelligent and efficient computing solutions. Complex Task Automation: With its robust methodology, it can automate complex, multi-step tasks, making processes faster and less error-prone. Continuous Improvement: The learning mechanisms enable Agent S to improve from past experiences, continually enhancing its performance and efficacy. Versatility: Its adaptability across different operating environments like OSWorld and WindowsAgentArena ensures that it can serve a broad range of applications. As Agent S positions itself in the Web3 and crypto landscape, its potential to enhance interaction capabilities and automate processes signifies a significant advancement in AI technologies. Through its innovative framework, Agent S exemplifies the future of digital interactions, promising a more seamless and efficient experience for users across various industries. Conclusion Agent S represents a bold leap forward in the marriage of AI and Web3, with the capacity to redefine how we interact with technology. While still in its early stages, the possibilities for its application are vast and compelling. Through its comprehensive framework addressing critical challenges, Agent S aims to bring autonomous interactions to the forefront of the digital experience. As we move deeper into the realms of cryptocurrency and decentralisation, projects like Agent S will undoubtedly play a crucial role in shaping the future of technology and human-computer collaboration.

566 Total ViewsPublished 2025.01.14Updated 2025.01.14

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