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.
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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
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
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.
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.
- • 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.