Polymarket bots93 shown

Unified prediction market trading API, not a specific trading strategy.

unified trading API, not a standalone strategy

Multi-strategy framework: arbitrage, copy-trading, market-making, and more across Polymarket, Kalshi, Limitless, with Predict.fun roadmap.

Not a trading strategy, but a tooling project. Provides a terminal dashboard for market overview, price tracking, and order placement, enabling faster manual analysis and execution for traders who prefer CLI tools.

Framework for building, backtesting, and deploying trading strategies across multiple betting/prediction market platforms.

Uses Chainlink oracle price divergence, liquidity filters, and short-term scalping for final-epoch opportunities.

Weather-based quantitative analysis and trading on Polymarket temperature markets using intelligent models

Multi-strategy: 25+ built-in strategies including copy trading, AI scoring, and custom Python strategies.

On-chain oracle front-running — monitors Polygon block data for UMA/OVM resolution transactions, parses the outcome before the market's frontend updates, then executes trades via CLOB API with AI-based confirmation.

Autonomous multi-strategy trading with real-time market scanning and adaptive positioning

Unified market data aggregation and arbitrage across multiple prediction market venues.

Edge detection, liquidity provisioning (market making), cross-market arbitrage, all gated behind paper-trading and risk controls

Multi-strategy Rust trading engine with risk management

Market-making/arbitrage: removes juice (overround) from sportsbook lines, converts to implied probabilities, quotes two-sided markets on Polymarket, and delta-hedges positions across correlated contracts.

Hybrid ML ensemble (LightGBM+XGBoost) combined with LLM-based signals for multi-factor market analysis, with Telegram-based alert delivery

Paper trading on temperature markets using weather data for edge detection

Multi-strategy: Momentum, Maker, Arbitrage, Time Decay, Basis, ML, Trend.

Cross-platform arbitrage between Polymarket and Kalshi prediction markets using autonomous trading agents.

Cross-platform prediction market API abstraction layer — agent-based simulation, Bayesian modeling, and trading algorithm development.

AI/LLM integration layer for prediction market trading through Model Context Protocol

AI-agent-based signal generation with autonomous swarm intelligence for trade execution

Cross-exchange arbitrage exploiting price differences between Kalshi and Polymarket prediction markets

N/A - provides a framework/infrastructure for AI agents to interact with Polymarket without real funds. Support for agent-driven markets or simulated strategies.

Agentic AI framework using Claude and GPT models for trading automation and strategy enhancement

MCP server providing AI agents with Polymarket data access, real-time monitoring, and market analysis capabilities.

Cross-asset arbitrage between BTC and SOL 15-minute prediction markets on Polymarket, using Rust for low-latency execution and block engine for MEV-style order placement.

Copy trading via on-chain wallet analysis with limit order execution

Provides the foundational layer for algorithmic trading strategies. While it is not a strategy itself, it enables any Go-based bot to efficiently place orders, stream market data, and interact with the orderbook. Its value lies in performance and reliability.

Market scanning with evidence gathering, paper trade recommendation, result tracking — designed as research assistant not auto-trader.

Quantitative weather prediction market arbitrage (NO side on overpriced temperature markets)

Portfolio construction via tokenized baskets (ETF-for-prediction-markets) enabling multi-outcome position bundling

order book analysis and quant research

Scans NegRisk multi-outcome markets for arbitrage opportunities, with paper-trading mode.

Cross-exchange arbitrage between Kalshi and Polymarket with LLM-based market semantic matching

Numerical weather prediction + Kelly-criterion position sizing across Kalshi and Polymarket temperature markets, with full transparency of forecasts and market conditions at trade time

Impulse-based momentum detection with automated trailing stop management and delta-neutral hedging

Convex optimization arbitrage — models the multi-outcome arbitrage problem as a convex optimization, applies the Frank-Wolfe algorithm to find the optimal trade allocation that minimizes slippage while maximizing risk-adjusted return.

Jury-based consensus strategy for BTC 5-minute Up/Down markets. It likely aggregates signals from multiple models (the 'jury') to make a decision, and includes serious backtesting with orderbook data.

statistical arbitrage on weather markets (NO side)

Combines AI/LLM decision-making with traditional arbitrage and market making strategies

Whale watching and smart money flow tracking - informational strategy not trading execution

Cross-platform odds comparison between Polymarket and traditional sportsbooks for arbitrage opportunities

Ensemble ML model (LGBM, XGBoost, LSTM) for short-term BTC price direction prediction

NegRisk multi-outcome arbitrage detection

Uses an XGBoost + LightGBM ensemble to trade BTC 15-min binary markets, with a focus on model retraining and monitoring for performance.

Coherence arbitrage research: Scans Polymarket's multi-outcome markets for situations where the sum of probabilities for mutually exclusive outcomes deviates significantly from 100% (coherence violation). The bot demonstrates whether these violations are exploitable or obscured by transaction costs (bid-ask spread).

Combinatorial arbitrage detection across Polymarket, Kalshi and others

Bets on underdogs in high-volume, unanchored Polymarket markets based on a documented favorite-longshot bias, using a measurement-focused framework rather than a black-box model.

AI-driven edge detection with Kelly risk management across prediction markets

Cross-venue arbitrage detection by matching equivalent markets across Kalshi and Polymarket

SDK/library for building Polymarket trading bots and analytics tools

Bets on temperature outcomes using an ensemble of forecast models (METAR, Open-Meteo) fused into calibrated bin probabilities, with settlement-aware adjustments and risk-sized fail-closed execution.

Research paper replication: Dubach strategy for prediction market inefficiencies

Market making with phase-based implementation covering spread capture, inventory management, and risk limits

Analytics/Fee Research: analyzes on-chain execution data to reverse-engineer the hidden fee structures of various Polymarket interfaces and bots.

Likely statistical models on in-game events (pitch counts, scores) to identify mispriced live markets.

Signal generation from market data for live trading on Polymarket

Real-time cross-exchange arbitrage scan across four trading platforms

Same-venue binary complement arb (buy YES and NO of complementary events summing to < 1), multi-outcome NegRisk field arb with false-positive filter, and cross-venue mirror market matching with Polymarket vs Kalshi prices. Read-only, no execution.

AI-assisted weather arbitrage (predicting weather event outcomes vs. market prices)

Detects and trades price discrepancies between equivalent markets on Polymarket and Kalshi using Kelly sizing.

Cross-platform arbitrage between Predict.fun and Polymarket with market-making on identified price discrepancies

Arbitrage on 15-min Up/Down markets with hedge thresholds and risk management.

Cross-venue spread analysis and arbitrage detection

Cross-venue arbitrage research: Kalshi ↔ Polymarket market matching on equivalent event contracts, spread detection, read-only execution

General quantitative strategy framework with backtesting and live execution

Cross-exchange and inter-market arbitrage detection between Kalshi and Polymarket, with a real-time order book comparison in Rust for high performance.

No automated strategy; manual terminal-based trading interface for Polymarket CLOB with live market data.

Hedged market-making — quotes both sides of a binary market simultaneously using delta-neutral positioning; earns spread on filled orders plus potential Polymarket liquidity incentive rewards.

Infrastructure/library for building custom Polymarket bots (strategy-agnostic framework)

Market-making simulator that measures theoretical LP reward share, fill rates against real order book, and adverse selection costs using historical CLOB data without executing trades

Lead-lag arbitrage exploiting delayed price discovery in prediction markets relative to a crypto-sourced vig-free line, with Kelly criterion position sizing.

Timezone-arbitrage and multi-strategy: Python framework with 9 pluggable strategies including momentum, mean reversion, and timezone lag exploitation (trading US events during Asian hours when liquidity is thin).

Tracks smart-money wallets on Polymarket, mirrors trades paper-only, measures real-world copy-trading friction (delay, slippage, execution quality).

Research framework with 11 candidate strategies: range from simple moving average crossovers to ML-based classifiers, all evaluated on historical Polymarket data with transparent performance reporting.

Real-time monitoring of 5-minute BTC binary options with configurable thresholds, Telegram notifications for price swings and spread anomalies

Copy-trading with quantitative trader selection: ranks traders by net edge (PnL/volume - 2.3% x spread crossings), copies only those above threshold, enforces position limits and stop-losses, key remains locally

NLP-based credibility scoring of event descriptions and resolution sources to identify mispriced contracts

Data analysis and wallet reconstruction. It doesn't execute trades but provides a powerful analytical tool to reconstruct and analyze any trader's behavior based on public on-chain proxy wallet data.

Custom market-making / retail-facing execution via TUI, likely manual or semi-automated trading with real-time data display

Ensemble machine learning models with Monte Carlo simulation to price match outcomes and detect market inefficiencies

The bot likely implements a finite state machine (FSM) to track the lifecycle of arbitrage opportunities. It may define states like 'scan', 'evaluate', 'trade', and 'exit' to manage orders across related markets. The strategy likely involves finding and executing on pricing inefficiencies between multi-outcome markets, potentially on the same or different competitions.

Paper trading simulation comparing multiple bot strategies

Market mispricing detection combined with smart money flow analysis, delivered via browser extension

Kelly criterion position sizing based on NWS forecast data for weather derivatives

Cross-platform value scanning between Kalshi and Polymarket using independent probability models, decimal-exact pricing, and walk-forward backtesting for conservative expected value estimation.

Event-driven arbitrage/momentum based on real-time social media post counting.

Whale wallet identification and activity analysis with automated copy-trade signal generation

Cross-venue arbitrage detection between Kalshi and Polymarket with fee-aware pricing calculations and risk engine for locked positions

Multiple strategies including Flash Crash detection, 15-min market momentum, and gasless arbitrage using proxy wallets

Copy trading by monitoring leader wallet activity and mirroring trades with configurable sizing and delay

AI-agent-driven copy trading via MCP protocol: tracks whale wallets, generates copy signals, executes paper trades via $10k mock wallets

Simple paper copy-trading: fetches target wallet's portfolio and simulates mirror trades via scheduled GitHub Actions runs