South Africa v Spain
Set a scoreline and see where it sits among the 5,000 simulated runs behind this fixture. Ratings as at 2026-10-18.
South AfricaSpainThe 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.
7.0% of runs finished in this bin — South Africa by 28 to 32.
64 points is around the 52nd percentile of the total — the middle run scored 63.
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.
That is the model’s own average scoreline. 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 South Africa are favoured
How the model arrives at the chance of South Africa 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 South Africa, a bar to the left helps Spain.
South Africa 2512, Spain 1566 — 946 points, favouring South Africa
South Africa 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.
South Africa and Spain 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.
1 meetings — South Africa 1, Spain 0. Last 1999: South Africa 47–3 Spain.
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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