KellyIQ
Devigged market baselineYour view of the edgePortfolio sizingRisk controlsNo picks

How KellyIQ works

KellyIQ helps you answer one question: “How much should I bet?” across a slate. The market price sets the baseline, your confidence shifts it, and KellyIQ sizes the position under your constraints.

Start freeView pricingKellyIQ does not provide picks, predictions, or promised profitability.
Clarity

Optimization software — not a betting advice product.

We don’t tell you what to bet. We help you size a set of wagers you choose to place, under constraints and risk preferences you define.

What KellyIQ does
  • • Removes the vig to get a fair market baseline
  • • Applies your confidence to that baseline
  • • Simulates portfolio outcomes (Monte Carlo)
  • • Sizes bets using Kelly-style logic with guardrails
  • • Outputs a ticket: stake per wager + risk metrics
What KellyIQ does not do
  • • Not picks
  • • Not predictions
  • • Not “AI says bet X”
  • • Not edge claims or guaranteed profit
Workflow

The workflow in 5 steps

You bring the markets and your read on them. KellyIQ returns sizing and risk context, so you can be consistent over time.

1) Ingest market odds (per book + consensus)

KellyIQ pulls current odds and maintains timestamped snapshots allowing you to reconstruct any slate at any point in time.

Multi-book snapshotsHistorical reconstructionConsensus views
2) Remove the vig → fair market baseline

Odds carry the market's view plus the bookmaker's margin. KellyIQ strips the margin to get the fair probability the price implies, which is the baseline it starts from rather than the number printed on the board.

Implied vs fairMulti-book consensusNo model forecast
3) Apply your view → estimated probability

Your confidence moves that baseline up or down. This is where an edge can exist at all: KellyIQ does not predict games and does not tell you what to bet, so the probability it sizes from is yours, not the book's.

Worth being plain about why this step is not optional. A fair baseline matches the price by definition, so a market-only probability leaves zero edge and Kelly sizes every bet at nothing. The view you supply is what makes a stake possible, and it is also what you are accountable for.
4) Model portfolio outcomes (Monte Carlo)

Instead of evaluating each bet in isolation, KellyIQ simulates the combined outcome distribution across the whole slate.

Full-slate simulationDrawdown-awareDownside metrics
5) Optimize stake sizing under constraints

KellyIQ allocates stake using a Kelly-based framework to manage exposure under your chosen guardrails, including caps, total stake limits, exposure controls, max-position filtering, and downside sensitivity (e.g., CVaR).

Fractional KellyFixed stakeCVaR-adjustedTop-KExposure caps
The chain, end to end
  1. Market price
  2. Devigged fair probability
  3. Your adjustment
  4. Estimated probability
  5. Edge vs. the offered price
  6. Position size

Two of those steps are yours: which markets to consider, and how far your view sits from the market’s. Everything else is arithmetic you can check.

Output

What you get back

A sizing ticket (stake per wager) plus context on concentration and downside — so risk is visible before you place anything.

Stake per wager

A concrete stake size for each position in the slate.

Risk metrics

Portfolio-level volatility, drawdowns, and downside-sensitive risk views.

Constraint visibility

Clear guardrails: caps, total stake limits, exposure controls, and top-K filtering.

A note on “Kelly” (plain English)

The Kelly criterion is a sizing framework that’s about how much to stake when you have probabilities. KellyIQ uses Kelly-style sizing as a base, then adds practical controls (caps, fixed stake, downside sensitivity) so the results are usable for real bankroll management.

Want sizing you can justify — and repeat?

Start with a slate you already bet. KellyIQ will translate market data into a risk-aware ticket, without pretending to “know” outcomes.

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