Builds independent probability models using historical data, news feeds, and statistical signals to estimate the true probability of an event outcome. When the market price diverges significantly from the model’s estimate, the system automatically places trades to exploit the mispricing before the market corrects — the core alpha source in prediction market trading.

Automated liquidity provision on Polymarket and Kalshi CLOB order books — simultaneously posting YES and NO bids within the spread to earn the bid-ask spread over a high volume of trades. Includes dynamic spread adjustment based on market volatility, inventory management to control directional exposure, and toxicity filters to avoid adverse selection from informed traders.

Real-time monitoring of the same event across multiple platforms — Polymarket, Kalshi, and PredictIt — to identify pricing discrepancies for the same outcome. When the same event trades at materially different prices across platforms, the system simultaneously buys on the cheaper platform and sells on the more expensive one, locking in a near risk-free profit.

Natural Language Processing models that monitor real-time news, social media, and official data releases to detect events that should materially shift the probability of a market outcome before the crowd reacts. For example — detecting an election poll release, economic data print, or breaking political news and immediately adjusting positions on Polymarket or Kalshi before prices move.

Systematic sports trading on Betfair Exchange using statistical models for pre-match and in-play markets. Covers football (expected goals models), horse racing (form and speed ratings), and tennis (serve statistics). Strategies include pre-match value betting, in-play scalping, and laying overpriced favourites using ELO-based and regression models.

Mathematically optimal position sizing using the Kelly Criterion — calculating the exact fraction of bankroll to stake on each bet or trade based on estimated edge and probability. Includes fractional Kelly variants for risk reduction, dynamic bankroll tracking, and drawdown-adjusted staking that reduces exposure during losing runs across Betfair, Polymarket, and Kalshi.

Exploits overreactions in prediction market prices following breaking news or large directional trades. When a market price moves sharply but the underlying probability has not fundamentally changed — for example, a temporary shock from a misleading headline — the system fades the move and profits from the reversion to fair value.

Machine learning models (XGBoost, LightGBM, ensemble methods) trained on historical prediction market outcomes, polling data, economic indicators, and sentiment data to produce probability forecasts. Walk-forward validation ensures out-of-sample accuracy. Forecasts feed directly into automated trading execution on Polymarket, Kalshi, and PredictIt.