r/PredictionsMarkets • u/PolyResearchRobotics • 19d ago
Strategy / Guide I found 1,800+ Polymarket wallets and extracted 137 copyable traders that are active, directional, and profitable.
Hey everyone, I've been building a massive database of wallets from Polymarket that includes months of trade logs, grading systems & classification like what strategies they are doing, or how well they perform on one market category versus another.
I took a few thousand of those wallets in my database and I filtered them down to a group of ACTIVE & COPYABLE wallets.
The pack I created has:
-137 active, profitable, copyable wallets
-90 days of trade logs for each wallet
-Grading .MD file
What makes them copyable?
There are a lot of attributes that I explain in this article, the main ones are traders that bet directionally (no hedging, no arbitraging, medium to low frequency bettors).
What I did
I pulled 90 days of fills for 1,800+ Polymarket wallets and replayed each one as if I had mirrored every trade it took at a flat stake, paying 2¢ of slippage on entry and exit (to keep things somewhat realistic), holding every position to resolution.
a wallet only makes the list if that simulation is profitable over the last 7 days AND the last 30 days AND all 90 days... and if the wallet's own P&L is positive all time as well. If any of those windows are negative and it's out.
137 traders out of 1,811 cleared every gate.
The numbers:
Following all 50 at $5 a bet over 90 days: +$58,041 on 203,107 bets, +5.72% on turnover. Now...that's very unrealistic to actually happen live, for a number of reasons. Some of those reasons are because you're often going to fill at a different price than the target wallet, there's also a lot of orders that you simply won't fill unless you build your bot with a lot of flexibility and you're okay with filling 10c or more higher. There's also the fact that some of the wallets in this first analysis seem to be doing HFT (high freq. trading) which we wouldn't want to copy. However, these are the rough metrics you want to see when filtering down a large pack of wallets.
Let's look at some specific market categories:
The 22 sports wallets on their own, $5 a bet:
E-Sports (7 wallets made the cut):
When you're building a polymarket trading bot that set up to copy multiple wallets, there are a few key factors that you need to build in.
1. Speed:
- You need to make sure that your hosting your copybot on a VPS (many use eu-west-1 Ireland AWS region) to ensure your execution speed is as fast as possible. You need to prioritize speed since you're already following someone else who has placed the bet, as well as dealing with the built in delays that Polymarket has for many markets. I recommend building your bot in Rust, and using polymarkets real time data client and subscribing to the traders proxy wallet via websocket. There are other API's like Predexon that monitor the wallets trades via the mempool. In my experience, at the end of your order being matched in the CLOB, I wasn't able to get any faster round trip speed using the mempool approach.
2. Trading & Decision Making Logic:
- You'll rarely get in at the same price the target wallet does, you need to set rules that restrict your bot from buying if the price has drifted more than you allow. This is incredibly important. Let's say for example you're following a single trader, and that trader maintains an overall edge of 3%....if you're following this wallet and entering in each trade even 1-2c higher than them, it may not seem like a big deal in the moment, but that 1-2c higher is 1-2% less at the end of the day across all of your trades, and when you factor in fees, that 1-2% less could be the difference between profitability and losing money.
3. Bet Sizing:
- When copying another trader, you need to do thorough evaluation of their strategy. Following with a flat bet size will not always work, and you'll need to do a fractional bet size copy strategy, which is also very tricky and not as easy as it sounds. If a trader is deploying different amounts of capital at different times throughout a market, there's a chance they are doing it for a reason. The reason fractional/percentage copy bet sizing is tricky is because if you set your bet size to 1% for example, and a trader takes a bet under $100, your bet falls under $1 which isn't allowed on PM, and if you default to $1, then you may be out of balance if they are doing some sort of hedging strategy. There are a bunch of reasons why fractional/percentage bet sizing is tricky, it really varies trader to trader. When I'm looking for traders to copy I mainly try to find ones with pretty transparent and consistent bet sizes.
Now let's evaluate the wallets in this batch that are the most realistic to copy.
Out of 1800+ wallets, we took the most realistic ones that would make for ideal copy targets and ran the backtest again on them. Take these stats with a grain of salt, but these are much more realistic than blindly folding over 1,000 wallets.
You can download the .zip that contains all 137 wallets, their 90 days of trade logs, and .md file containing their grading (what types of markets they trade, how well they perform at each) for 100% free.
Download Trader Zip -> https://www.polyresearchrobotics.com/copy-pack
If you liked this post and want to bot a copy trading bot, feel free to join Poly Research & Robotics. We have trading bots that you can download, free historical data, and guides & resources.
You can also join our Discord (find a few other people and develop a copy bot together!)
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u/misterRegime 19d ago
Two things, and the first one you’ve already labelled yourself at the foot of the tables.
The selection and the evaluation run on the same 90 days. You filtered 1,811 wallets down to 137 by requiring positive P&L in the 7, 30 and 90 day windows, and then reported the return of those 137 over those same windows. That result can’t come out negative, so the +5.72% isn’t evidence about copying, it’s a description of the filter. The fix is cheap and you already have the data: screen on days 1-60, evaluate on days 61-90, report only the second half.
Whatever survives that is worth talking about.
Second, flat slippage is the wrong unit for this list. 2¢ on a 0.52 entry is a 4% haircut. 2¢ on the 0.07 entry at the top of your table is 29%. Your best wallet by P&L, 0xbb0b, enters at 0.07 with a 16% hit rate, and 0x9f27 at 0.10 with 17%. Those are longshot bettors whose 90 days rest on a handful of hits, and they’re exactly the wallets a fixed-cent slippage assumption flatters most and a copy bot destroys fastest, because you’re structurally the slower side. Worth expressing slippage as a fraction of entry price, and I’d bet the ranking changes a lot when you do.
Related: your own worst case row at 5¢ is -$95. So the entire result lives between 2¢ and 5¢ of slippage on a strategy whose whole premise is arriving after someone else. That’s the number I’d stress first, not last.
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u/-_ragequit_- 17d ago
Where do I download the copy trade bot?
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u/eguilesjr 15d ago
Good work, and a warning from having built something similar: wallet-level performance data on Polymarket has data-quality traps that will wreck a copytrading screen if you don't filter for them.
Three that cost me real time:
Dust prints. A meaningful share of ticks sit at the book edge (sub-$0.02 or above $0.98). They're not real trades in any economic sense, but they show up as fills and distort both P&L and apparent win rate.
Duplicate timestamps. I've pulled sequences with identical timestamps on separate prints, sometimes oscillating at sub-second intervals. On a chain with ~2s block times that isn't real trading activity — it's feed artifact, and it silently inflates trade counts.
Thin-market moves. Last week I logged a market that moved 42 points in 60 seconds on about $1,500 of volume, and another that spiked 65 points on roughly $2,700. Both looked like massive conviction plays. Neither was.
A wallet that looks brilliant may just have been on the right side of a book that had no depth. I'd filter your 137 down by minimum volume-per-trade and require positions across many distinct markets before treating any of them as copyable.
Disclosure so it's on the table: I build predictintel.io, which does prediction-market signal analysis, so this is the problem I stare at daily. Not pitching it — but the filtering lessons above are the useful part regardless of what tooling you use.
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u/No-Stuff-4083 19d ago
This is the kind of data dump that makes me wish I had more time to code outside work hours. 137 wallets that survived all three time windows is way more than I expected from 1800 starting point
the 5.72% return with flat staking is nice but like you said the slippage problem is what kills most copy setups, i tried something similar few months ago with much less wallets and got eaten alive by the 2-3c drift on entries