The astronomical rise of prediction markets like Kalshi and Polymarket has led to the exchange of billions of dollars. In case you're unfamiliar, these platforms give traders a decentralized place to buy and sell contracts across a wide variety of events including sports, politics, and finance.
While there are many different prediction market strategies, Reddit user marvmarv2693 really wanted to see if they could beat the system. More specifically, Polymarket's system. A couple of months ago, they posted their findings in r/predictionmarkets, which were based on 10 months of Polymarket data spanning 600 liquid markets.
This allowed them to test 10 unique strategies based on available statistics as opposed to engaging in the laborious, expensive task of actually buying and selling such a large volume of contracts. Here is what they found, and how other Redditors reacted.
Which 10 Polymarket trading strategies were tested?
The basis of this Redditor's Polymarket test was to adapt popular market strategies used in sports betting and traditional financial trading, with the goal being to test whether or not any would prove profitable. Here's a brief breakdown of each Polymarket strategy from Reddit:
8-agent AI LLM Forecasting Swarm: Created a group of AI agents with different personas to debate contract probabilities, with the goal of generating more accurate predictions than a group of people.
Copy-Trading Top Wallets: As it sounds, they copied the transactions of traders who had been historically profitable, seeing whether or not each trader had developed repeatable skills in this area (as opposed to just "getting lucky").
Favorite-Longshot Bias: Ignored popular low-probability contracts valued at under 20 cents, aiming to find out if there was any truth to the wide belief that most traders overvalue longshots.
Momentum Trading: Analyzed differences between early and late price trends to try and opportunistically identify any time-based advantages.
Booking Multi-Leg Events: Searched for mispriced markets with multiple outcomes, to see if profits could be generated when the total of implied probabilities didn't equal exactly 100%.
Calendar Arbitrage: Found identical binary contracts with different resolution dates in an attempt to exploit price differences between them.
Settlement-Lag Discounts: Bought contracts close to the resolution date, with the goal of collecting a small discount prior to settlement and payouts.
Crypto Round-Number Bias: Ignored cryptocurrency market trends based on how people psychologically perceive milestones (such as the value of a single Bitcoin eclipsing $100,000), hoping to exploit human bias.
Illiquid Market Exploitation: Tracked limit orders of low volume markets with wide margins, attempting to find mispriced value.
Data Re-Slicing and Alternative Filtering: Conducted various Polymarket tests by using different filters to find system inefficiencies relating to time, volume, and other parameters.
What did this Redditor's Polymarket test reveal?
Overall, all 10 strategies in this Redditor's Polymarket test failed to be sustainably profitable. Like many of the best prediction markets, Polymarket contracts are very efficiently priced, and the standard 2% fees surrounding each transaction significantly cut into any chance of turning a consistent profit.
Look to the table below for a brief breakdown of how the top-3 Polymarket tests turned out.
| 🧪 Polymarket Strategy | 📊 Expected Edge | ✅ End Result |
|---|---|---|
| 🪲 1. 8-Agent AI Swarm | AI out-predicts human crowds | Failed. There AI Brier score was 0.38, compared to the market price scored at 0.30 (lower is better). |
| 💳 2. Copying Top Wallets | Following top wallet histories | Failed. Top traders lost ~13.6% after factoring in post-trade price movement. |
| 🤞 3. Favorite-Longshot Bias | Longshots are overpriced | Non-existent. Longshots under 0.20 actually won at a 1.15% clip compared to the 0.73% implied probability. |
1. AI Models were crushed by crowd wisdom
Surprisingly, the group of 8 differing AI models that were made to collaborate as market forecasters did not end up making more accurate predictions than the general consensus of traders. In fact, the raw pricing of most markets was consistently more accurate than the AI swarm.
2. "Smart Money" wallet tracking backfired
Simply copying top wallets from the chain seemed like a strong contender, taking historical data from Polymarket's top 15 traders and applying the same concepts to new, similar markets. As it turns out, those traders lost 13.6% out-of-sample, proving that past success is often just survivorship bias in disguise.
3. The 17% "YES" base rate
Across liquid markets with over $10,000 in volume, only 16.8% resolved to "YES". Simply put, prediction markets often ask if an influential event will happen by a certain date (ex. "Will Donald Trump Resign As President by X Date?"). Since large-scale events of this nature predominantly don't end up happening, Polymarket is almost always favored to win "NO" contracts.
What did Reddit think of these Polymarket strategies?
With nearly 40 total comments on this thread, Redditors were naturally split on some opinions. Here are the top-3 sentiments expressed by Reddit users debating these Polymarket tests.
1. Skeptics doubted general quality of selected markets
Several Redditors pushed back with advice that somewhat oversimplifies the meticulous nature of these strategies, telling the original poster to simply "make better picks" or to perhaps re-visit how the bankroll itself would be managed.
The author did directly addressed these criticisms by reminding readers that bankroll management only improves an existing edge, meaning it cannot make a trade profitable if it has negative expectations.
2. Quant traders pointed out wallet calibration
Other Reddit users debated the technical side of these Polymarket tests. For example, one commenter highlighted recent academic research showing ~3% of accounts drive almost all of Polymarket's price discovery.
Further to this, they argued that tracking a wallet's calibration (accuracy) rather than its ROI (return on investment) would be a more accurate way to forecast successful outcomes. The original poster refuted this claim as well, stating that by the time a trade on the block is visible to copycat traders, the market price has already adjusted.
3. Bot developers debated cross-venue arbitrage
Redditors claiming to have extensive knowledge of how automated bot are created were skeptical of being able to identify mispriced contracts across different prediction markets. Another noted that running 233 screens a day with zero execution only fills due to strict safety thresholds.
The original posted acknowledged that while cross-platform wedges might exist, factors such as differing settlement rules and transactions fees are almost always enough to wipe out any theoretical profits.
