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Emil Nielsen
Emil Nielsen

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Building a Faster Polymarket Trading Bot: Why 5–10 WebSocket Connections Matter

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:

  1. Receive identical events from multiple connections.
  2. Deduplicate incoming messages.
  3. Keep only the earliest event.
  4. 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

GitHub logo DextersSlab / Polymarket-Arbitrage-Trading-Bot

Polymarket Arbitrage Bot | Polymarket Trading Bot | Polymarket Arbitrage Bot | Polymarket Trading Bot | Polymarket Arbitrage Bot | Polymarket Trading Bot | Polymarket Arbitrage Bot | Polymarket Trading Bot | Polymarket Arbitrage Bot | Polymarket Trading Bot | Polymarket Arbitrage Bot | Polymarket Trading Bot | Polymarket Arbitrage Bot | Polymarket

Polymarket Arbitrage Trading Bot (BTC, ETH Momentum Arbitrage trading bot)

TypeScript bot for Polymarket CLOB V2 5-minute BTC and ETH Up/Down markets. It monitors Chainlink strike/spot vs order books, enters momentum-aligned positions late in each epoch, optionally completes the opposite leg for a boxed pair, and manages exits with configurable risk rules.

You can check this bot pnl with this account.

https://polymarket.com/@9g9g99

My_account_Pnl
BTC-ETH-Momentum-Arbitrage-Bot-9g9g99.mp4

Built with @polymarket/clob-client-v2 and Node.js 20+. See V2_MIGRATION.md for Polymarket exchange upgrade notes.

Features

  • Dual-market confirmation — BTC and ETH must align before entries (reduces false signals)
  • Chainlink Data Streams — strike at epoch open + live spot for spot_minus_strike
  • High-frequency monitor — REST CLOB /book polling (~150ms), merged btc/eth wave logs
  • Six strategy phases — buy1, buy2, buy3, buy4, risk1, risk2, risk3
  • Paper trading — simulated fills without live CLOB orders
  • Optional redeem — gasless redeem via Polymarket builder relayer after epoch end
  • Deposit wallet

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
Enter fullscreen mode Exit fullscreen mode

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.

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