Opening the Polymarket leaderboard, the first reaction might be: This address made $200,000, is it safe to buy from them? Not necessarily. Behind huge profits could be 50 consecutive correct bets in the market, or it could be a single big bet that just happened to be right. The former is a systemic profit worth replicating, while the latter is unsustainable survivor bias. This article will help you solve two core problems: How to penetrate data noise and identify real "smart money"? And after finding the address, how to put it into practice using different strategies? I. Finding Smart Money: The Essence of Prediction Markets is Information Game Prediction markets are fundamentally different from secondary market cryptocurrency trading: they are extremely segmented information games. Behind each market target is a concrete professional question: Will a movie break $100 million in its opening week? (Theatrical release schedule, pre-sale data), Will the highest temperature in a certain city exceed 35 degrees Celsius tomorrow? (Weather models, historical averages), Will Iran launch an attack on Israel this month? (Geopolitics, intelligence monitoring). These areas have extremely high information barriers. Following smart money essentially involves finding people with a higher level of knowledge than you in a specific vertical field. So where do you find these people? A previous article on Biteye, "Mastering Polymarket: These 7 Tools Are Enough," introduced seven Polymarket tools. Taking Polymarket Analytics as an example, we must be wary of the following three pitfalls when selecting tools: 1. False Profit/Loss (PNL) Data: Polymarket's data structure is extremely complex, involving various on-chain operations such as buying, splitting, merging, and redemption. Many tools (even the official website) can have significantly inaccurate PNL figures if the wrong calculation dimension is selected. True smart money should calculate based on event dimensions, comprehensively considering inflows, outflows, and current holding market value. 2. Interference from Arbitrage Bots: For example, automatedAltradingbot, which often appears on lists. These addresses profit through cross-market arbitrage or providing liquidity. Although their win rate is impressive, every trade has a hedging position. If you only follow one of them, the risk will be completely asymmetrical. 3. High win rate does not equal high expectations: Some addresses specifically target markets with a win rate of over 98% that are about to settle, aiming to profit from the final $0.02 spread. While this strategy boasts a near 100% win rate, it offers no profit margin for copy traders and may even result in losses due to transaction fees. II. Four Dimensions for Screening Smart Money After finding the ranking list, the next step is screening. Smart money has two bottom-line conditions: profitability must conform to the Kelly Criterion, and there shouldn't be excessively large single losses. The core idea of the Kelly Criterion is: bet size must match the win rate and odds; one shouldn't go all in just because they feel confident in a particular trade.Traders who truly understand risk management calculate every position, preventing a single loss from wiping out all previous profits. Therefore, before looking at specific data, exclude two types of addresses: those with abnormally large total losses and those with a history of massive single losses. Even if the total PNL of such addresses is positive, their risk management logic is flawed. For the remaining addresses, use four dimensions to assess: Win Rate: Win rate is a core indicator of an address's consistent profitability, but it must be considered in conjunction with PNL. High win rate but low PNL: This often indicates end-of-day trading, where even wins are minimal; low win rate but high PNL: This might mean a few heavily leveraged trades happened to hit the market correctly. Quantity: A small sample size renders the win rate meaningless. Winning five consecutive coin tosses isn't a low probability, but nobody considers it significant. A 80% win rate on 10 markets is far more valuable than a 70% win rate on 300 markets. The more markets traded, the harder it is to explain profits as luck. However, if an address participates in too many markets, it might belong to a strategy bot, making copy trading unnecessary. Holding period: Addresses with short holding periods enter and exit within hours. By the time you discover their buy, the news may already be reflected in the price, and following them is just chasing the high, or even becoming a liquidity drain. Addresses with long holding periods are more like those who pre-plan a move; when you discover them, there's often enough time to follow, making this the most friendly type for ordinary copy traders. Profit structure: Is the profit diversified or reliant on a single trade? A good total PNL doesn't mean you're profitable in every market. Some addresses are propped up by one or two large, correct bets, while the rest are mostly losing money. This structure is difficult to replicate—you don't know where they'll bet next, or whether it's a prediction or luck. Stable smart money profits should be diversified across multiple markets, not concentrated in a few exceptionally large trades. What does a healthy address look like? Take BeefSlayer on the weather leaderboard as an example. At a glance, the data shows participation in 1,360 independent markets, totaling 2,500 trades, with a net profit of $41,367, a win rate of 61.2%, and an average bet of $196 per trade. The scatter plot on the right shows that profits are distributed across various win rate ranges, not concentrated in a few exceptionally large trades. Large positions are concentrated in the 60%-90% win rate range, consistent with the Kelly Criterion: the more confident the market, the larger the bet; in uncertain markets, position size is controlled. Money management: with an average bet of only $196 per trade, there were no instances of heavily leveraged bets that wiped out the account in the 2,500 trades, demonstrating stable risk control.III. Copy Trading Practice: Automated Tools vs. Subjective Judgment After finding a worthwhile address to copy, how do you actually operate it? There are roughly two paths: one is to directly use a robot to automatically copy trades, which is convenient but has limitations; the other is to use smart money's positions as a reference signal and then make your own judgment before deciding whether to copy. Strategy 1: Copy Trading Robots. There are already ready-made copy trading robot tools on the market. Simply set the target address and it will automatically copy trades. Common ones include: Polygun @Polygun_ (Telegram copy trading robot, which recently acquired Polymarket Analytics), Kreo @kreoapp (Telegram robot, which monitors on-chain smart money activities in real time and automatically copies trades), and PolyHub (Hubble) @MeetPolyHub (a tool under Hubble). However, copy trading robots are not as simple as they seem, and there are issues such as unequal capital size, market liquidity limitations, and order execution mechanisms. Strategy 2: Subjective Copy Trading. Use smart money's positions as a signal and then make your own judgment before deciding whether to copy. Step 1: Monitor the target address. After finding a worthwhile address to follow, don't rely on manual refreshing to discover its new activities; instead, use tools to monitor its on-chain transactions. The second step is to determine why the wallet is buying. Look at the timing of its entry: is it right after a major news event? If it entered the market in advance, before the news broke, it indicates it's trading based on its own judgment, making this signal more valuable. The third step is to determine if it's worth following. After analyzing the wallet's strategy, you need to check the price difference and position sizing before copying. Fourth, avoid pitfalls: Why do I still lose money when copying? Misconception 1: The robot's position sizing mode is incorrect. Copying robots generally have four position sizing modes: fixed amount, exact replication, proportional, and portfolio weight. If its returns mainly come from low-probability markets, the robot will find it difficult to replicate its strategy. Misconception 2: Following too late. Humans can't constantly stare at the screen. By the time you see the monitoring push and check the market, the price has often already fluctuated significantly. Following at this point means your cost is twice as high, the remaining profit margin is compressed, and the risk-reward ratio is completely unbalanced. Myth 3: You're still holding on even though the smart money has already sold off. The underlying logic of copy trading is borrowing their information and judgment. When the other person is losing money and leaving the market, you still hold onto hope—this is also the reason why copy trading results in the biggest losses. Behind these three myths lies a common problem: copy trading easily leads people to abandon independent thinking.Robots execute for you, smart money makes the judgments, and it seems like you don't need to do anything. But once a problem arises, you have no idea where you went wrong or how to adjust. V. In conclusion: Copy trading is the entry point; understanding it is the upgrade. Copy trading is a crutch; it can help you enter the deeper waters of the prediction market, but it cannot replace your walking. The real value lies not in "what" smart money "bought," but in "why it bought." When you can begin to deduce the logic behind their trades, copy trading is no longer your lifeline, but a filtering tool to improve efficiency. This is the necessary path to evolve from a "newbie" to "smart money." [Biteye]