Polymarket trading has become increasingly competitive. In fast-moving prediction markets—especially short-duration markets such as Bitcoin Up/Down contracts—milliseconds can determine whether a trade captures value or misses an opportunity entirely.
A recent experiment analyzing nearly 9 million Polymarket events across 18 WebSocket connections revealed something many bot developers have suspected: running a single WebSocket connection is not enough for optimal market data quality.
This article breaks down the findings and explores how developers can improve the performance of their Polymarket trading bots.
The Experiment
The test focused on Polymarket's 5-minute Bitcoin Up/Down markets and measured:
- Event coverage (missed messages)
- Latency (data freshness)
- Connection reliability
- Data gaps
- First-seen event performance
The experiment collected:
- Nearly 9 million events
- Across 18 unique WebSocket connections
- Over 51 market rotations
- Approximately 4 hours of runtime
Reference video:
YouTube: https://www.youtube.com/watch?v=pT7fu4n8o9Q
Why WebSocket Redundancy Matters
Most trading bots rely on a single WebSocket connection to receive market updates.
The problem?
WebSocket connections occasionally:
- Stall
- Drop packets
- Experience routing delays
- Deliver messages at different speeds
Even when multiple connections receive the same event, they often do not arrive simultaneously.
By maintaining multiple concurrent connections and selecting the earliest arriving event, a trading system can significantly improve execution speed and data quality.
Event Coverage Results
The study measured how many market events were missed.
| Connections | Miss Rate (PPM) | Coverage |
|---|---|---|
| 1 | ~2206 | 99.77% |
| 2 | Similar to 1 | Slight improvement |
| 5 | ~565 | Significant improvement |
| 10 | Even lower | Best result |
Key Takeaway
Moving from 1 connection to 5 connections reduced missed events by roughly 74%.
For algorithmic traders, missing fewer events means:
- More accurate market state
- Better order timing
- Reduced execution risk
Latency Improvements
Latency was measured as the difference between the event timestamp provided by Polymarket and the local receipt time.
Median Latency
| Connections | Median Latency |
|---|---|
| 1 | 67.2 ms |
| 2 | 63 ms |
| 5 | 58 ms |
| 10 | 55.9 ms |
While a 10 ms improvement may not sound dramatic, in highly competitive prediction markets it can create a meaningful edge.
95th Percentile Latency
The most interesting improvement occurred in the latency tail.
| Connections | P95 Latency |
|---|---|
| 1 | 522 ms |
| 2 | 305 ms |
| 5 | 175 ms |
| 10 | 154 ms |
This shows that redundant connections don't just improve average performance—they dramatically reduce worst-case delays.
Eliminating Data Gaps
One of the biggest risks in automated trading is silent connection degradation.
The test measured the largest observed gap between events.
Largest Data Gap
| Connections | Largest Gap |
|---|---|
| 1 | ~12 seconds |
| 2 | 4.86 seconds |
| 5 | Milliseconds |
| 10 | 2.8 milliseconds |
A single 12-second blind spot can be catastrophic in a fast-moving market.
By running multiple parallel streams, the system effectively eliminated these gaps.
First-Seen Advantage
Another interesting metric was the "first-seen win rate."
This measures which connection receives an event first.
Results showed:
| Connections | First-Seen Rate |
|---|---|
| 1 | 0.49% |
| 2 | 3.81% |
| 5 | 28.13% |
| 10 | 76.57% |
The implication is clear:
More connections create more opportunities to receive an event before competitors relying on fewer data streams.
The Engineering Trade-Off
Of course, increasing WebSocket connections is not free.
Developers must consider:
Higher Resource Usage
More connections mean:
- More CPU consumption
- Higher memory usage
- Increased network traffic
Rate Limits
Polymarket infrastructure may impose limits on excessive connection counts.
Running 10 connections per strategy can quickly become problematic if multiple bots are operating simultaneously.
Event Deduplication
A robust architecture must:
- Receive identical events from multiple connections.
- Deduplicate incoming messages.
- Keep only the earliest event.
- Forward the winning event to the trading engine.
This requires careful engineering but delivers measurable performance gains.
Open-Source Polymarket Bot Examples
Developers looking to experiment with Polymarket automation can explore several open-source projects.
Polymarket 5-Minute Bot Collection
https://github.com/topics/polymarket-5min-bot
A collection of repositories focused on automated trading strategies for short-duration Polymarket markets.
Polymarket Trading BTC ETH M Bot
https://github.com/nahuelvivas/Polymarket-Trading-BTC-ETH-M-Bot
An example trading bot targeting cryptocurrency prediction markets on Polymarket.
Polymarket Copy Trading
https://github.com/ducksybils/polymarket-copytrading
A copy-trading implementation that mirrors selected trader activity.
Architecture Recommendation
Based on the test results, a practical architecture would be:
Polymarket
│
┌────┼────┐
WS1 WS2 WS3
WS4 WS5 WS6
WS7 WS8 WS9
WS10
│
Deduplication Layer
│
Earliest Event Selector
│
Market State Engine
│
Execution Engine
This design allows the system to:
- Reduce latency
- Improve coverage
- Eliminate connection gaps
- Increase first-seen probability
Final Thoughts
The data suggests a clear conclusion:
One WebSocket connection is adequate for casual monitoring, but not for serious automated trading.
The largest gains appear when moving from:
- 1 → 5 connections
- 5 → 10 connections
The sweet spot for many traders is likely between 5 and 10 concurrent WebSocket connections, balancing performance improvements against infrastructure costs and potential rate limits.
As Polymarket grows and competition intensifies, market participants who invest in low-latency data infrastructure may gain a measurable advantage over traders relying on a single connection.
In prediction markets, information arrives only once. The trader who sees it first often wins.