Foreline/Products/Parlay Protection

Product 4 · Parlay Protection

Joint prices that agree with your marginals

A bet-builder multiplies legs that are not independent. We price the joint outcome from a coherent score matrix built out of de-vigged marginals — 1X2 and totals agree with each other by construction, and the handicap, which the matrix is not fitted to, comes back out with a median error of 0.83 pp.

Coherent score matrix Outcome × total Calibration published Known limitation disclosed
Request trial See pricing → Including the family where our model is weakest — that number is on this page, not in a footnote.
The mechanism

One matrix, so the legs cannot contradict each other

De-vigged marginals from the surface are assembled into a score matrix. Every market you quote is then a sum over the same cells — which is what makes a joint price consistent with the singles sitting next to it on your own site.

  • 1X2 and totals agree by construction. They are read off the same matrix, so there is no combination of the two you can hold that is priced from two different worlds.
  • The handicap is the held-out check. The matrix is not fitted to the handicap ladder, yet reproduces it with a median error of about 1 pp. That is the honest test of coherence: reconstruct a market the matrix was never shown.
  • Joint probabilities for combinations — outcome × total and handicap × total: the exact families where a naive multiply-the-legs builder leaks the most, because result and goal volume are correlated in every league. Four families are calibrated inside the headline band; the rest are returned with their own, wider numbers rather than folded into an average.
  • Every price carries its measured error. Each joint price is returned with the calibration band we measured for that family against realised outcomes, and with the worst family called out rather than the average one. The band describes how far the model has been seen to miss — it does not vary with whether a leg sat on a quoted rung or an interpolated one, and we do not claim that it does.
0.83 pp
median error when the matrix reproduces the handicap ladder it was not fitted to
2.1–2.9 pp
maxGap in the calibration of the joint families — the worst bucket, not the average one

maxGap is the largest deviation between predicted and realised frequency across calibration buckets. We publish the maximum rather than the mean because the maximum is what a sharp customer will find and use.

Full disclosure

Where the model is weakest

A pricing vendor that reports only its good buckets is selling you its residual risk. Here is ours, stated plainly.

  • Why it matters to you: “home and over” is one of the most-built families in any bet-builder. If you take our number at face value on that family without the band, you inherit our error.
  • What we do about it: the band is widened where the miss lives, the miss is reported per bucket, and the calibration is re-measured on every release rather than quoted from the launch report.
  • What we do not do: quietly patch the family with a fudge factor and keep reporting an aggregate that hides it.
How to engage

Audit first, feed second

The audit is the cheap way to find out whether this is worth an integration — it runs on prices you already have.

Audit — your builder prices, through our joint model You send a period of builder prices; we return which combination families cost you and by how much, with the calibration of our own numbers alongside so you can weigh the finding.
Feed — joint prices for your marginal combinations Delivered live for the combinations you actually offer, scoped by contract, with the same bands and the same ledger commitments as the surface.
Audit trail — permanently on Every joint call is committed to the hash-chained log as it is made: who asked, when, for how many legs, at which as-of moment, and the correlation gap we returned. Batch audit reports keep the full per-coupon numbers for 30 days and are yours to export. Turning that record into a quarterly calibration against settled outcomes is on the roadmap, not in the product today.

The marginals behind the matrix are the ordinary GET /v1/surface response — if you already take the surface, the audit needs nothing new from your side except the builder prices. Player props (goals or shots for a named footballer) are on the roadmap, phase 3, and are not part of this product today.

Get started

Request a parlay audit

Send us the combination families you offer and the period you want checked. We reply with the export format and what the audit will tell you.

Email us

We usually reply within one business day. Pricing is quoted per scope — ask and we will send terms.

Request trial