Edinburgh v Saracens
Set a scoreline and see where it sits among the 5,000 simulated runs behind this fixture. Ratings as at 2026-10-19.
EdinburghSaracensThe steppers skip 1, 2 and 4. Points come in fives, threes and twos with a conversion needing a try in front of it, so no match has ever finished on any of them.
19.3% of runs finished in this bin — within 2 points either way.
54 points is around the 54th percentile of the total — the middle run scored 52.
Those two figures are separate readings and are not multiplied together. The simulation draws the gap and the amount of scoring independently, so one bar of the histogram covers many scorelines and the payload holds nothing about which of them came up with which gap.
Your pick names a different winner from the model, which makes Saracens more likely. The model’s two answers point different ways here: it makes Saracens the more likely winner while its average scoreline has Edinburgh. That is not a contradiction — the average gap is taken over both winners, so a side that wins narrowly more often can still be behind on it. Nothing here scores any of it. The model’s gap is an average over both winners and yours is one afternoon, so the two are different kinds of number rather than one being right. How the model works.
Why Edinburgh are not favoured
How the model arrives at the chance of Edinburgh winning. It starts at an even 50%, and each line below adds to that or takes from it, in percentage points (pp): a bar to the right helps Edinburgh, a bar to the left helps Saracens.
Edinburgh 1528, Saracens 1861 — 333 points, favouring Saracens
Edinburgh are at home
Recent results, past meetings between the two sides, and days of rest. It has a limit, so it can nudge the rating but never overrule it.
Edinburgh and Saracens have no fixture on the published schedule, so there is no ground, no kick-off forecast and no team sheet to put beside this. The prediction itself does not need any of them.
3 meetings — Edinburgh 2, Saracens 1. Last 2023: Edinburgh 20–14 Saracens.
None of this reaches the model. Weather is not a feature, team selection is not a feature and the record is already inside both ratings, so the probability above does not move because any of it changed.
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