AccaIQ

Betting decisions, backed by the numbers behind them.

A stats-driven probability model — form, shots, and expected goals — priced against Betfair Exchange back odds with commission already netted out. Every suggestion shows its full reasoning, not just a number.

One Hilton Industries account, then a one-time access code — invite only.

Every pick shows its work.

No black-box confidence score — you can see exactly which sources agreed, which disagreed, and why a leg was included or dropped.

Priced on Betfair Exchange

Match result, goals, BTTS, double chance, draw no bet and more — every pick is priced at real Betfair back odds with the 5% commission already taken off, so the edge you see is the edge you'd get.

Powered by The Kendall Engine

A Poisson goal model built on real team stats — form, shots on target, expected goals — produces the fair probability for every leg. If the model's price beats the exchange, that's the pick.

Chat for an acca in plain English

“Give me a safer 3-leg acca for this Saturday, no cup games” — the request is parsed into real constraints and the AI selects from actual computed legs, never invented odds. Free daily calls on us; bring your own key for more.

Same-game combos, priced properly

“Home Win & BTTS” and similar combos are priced off a real Poisson scoreline grid, not independent-probability multiplication, which would misprice the correlation.

A track record that learns

Every suggestion is logged automatically at a flat stake, settled itself, and every loss gets an AI-generated post-mortem — a running record of what the model got wrong and why.

How it works

1

Ask or browse

Ask in plain English — "tonight's best value", "safer picks for Saturday" — or browse the week's fixtures.

2

See the reasoning

Every leg comes with its blended fair probability, edge, and a plain-English rationale citing the actual sources behind it.

3

Track what happens

Every pick is logged to the track record automatically at a flat £1 stake — settlement and loss post-mortems run themselves.