Cheetahs v Ospreys
Set a scoreline and see where it sits among the 5,000 simulated runs behind this fixture. Ratings as at 2026-08-24.
CheetahsOspreysThe 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.
15.6% of runs finished in this bin — Ospreys by 3 to 7.
51 points is around the 55th percentile of the total — the middle run scored 49.
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 agrees with the model on the winner. Nothing here scores that. 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 Cheetahs are not favoured
Starting from an even match and adding what the model reads, in percentage points of win probability. Positive favours Cheetahs, negative favours Ospreys.
Cheetahs 1260, Ospreys 1470 — 210 points, favouring Ospreys
Cheetahs are at home
Recent results, head-to-head record and rest days, as the XGBoost heads weigh them. Deliberately capped, so it can nudge the rating but never overrule it.
Cheetahs and Ospreys 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.
4 meetings — Cheetahs 1, Ospreys 3. Last 2019: Cheetahs 14–31 Ospreys.
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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