Systematic sizingMonte CarloRisk controlsEdge discipline

For sharps who want systematic, defensible sizing — not gut instinct.

KellyIQ treats a betting slate like a portfolio optimization problem. Market odds are used as inputs, outcomes are simulated, and stake is allocated under constraints — without bundling a prediction model.

14-day free trial · No credit card required

Historical market reconstruction
Coming Q4 2026

Rebuild the odds state of any slate at any historical moment (timestamped snapshots).

  • Per-book snapshots + consensus
  • Backtest sizing policies over time
  • Auditability for experiments
Portfolio simulation

Model the joint distribution of outcomes across the whole slate, not one bet at a time.

  • 100,000-trial Monte Carlo per run
  • Drawdown and path-dependent analysis
  • Downside risk metrics in higher tiers
  • Compare up to 4 scenarios side by side
Constraint-based optimization

Move beyond naive Kelly. Apply guardrails and solve for feasible allocations.

  • Caps, total stake limits, exposure limits
  • Top-K filtering
  • CVaR-adjusted sizing (where enabled)

Decouple sizing from prediction.

Many tools bundle "model + picks + sizing." KellyIQ intentionally focuses on the optimization layer: how to allocate capital given a distribution, with explicit constraints and risk preferences.

No edge claims

KellyIQ is not claiming to forecast outcomes. It devigs the market price to a fair baseline and sizes against the probability you supply on top of it. The edge is yours; the infrastructure for sizing and risk modeling is ours.

Best fit
  • • Sharps who track results and optimize sizing over time
  • • Systematic bettors testing allocation strategies under constraints
  • • Players who want discipline and auditability over intuition

Want to evaluate sizing policies over time?

Start with market data and build upward: simulation → constraints → portfolio sizing.