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Surprises against the model

The results the model gave a small chance before kick-off, and how often they happened. It shows what happened, not what will happen. How good is the model? →

By league

For each league: how many results came even though the model gave them under 20%, and how many should have come on average if the estimates are right. When the two numbers are close, the surprises are exactly as many as “expected”.

LeagueSeasonmatches with an estimateresults under 20%: actual / expectedbiggest upset
Premier League2025-26 ↺36419 / 20.3if the model is right: between 13 and 28 (95%)Arsenal FC 1–2 AFC Bournemouth (10.7%)
La Liga2025-26 ↺35923 / 24.7if the model is right: between 16 and 33 (95%)Real Madrid CF 0–1 Getafe CF (7.2%)
Serie A2025-26 ↺36427 / 25.9if the model is right: between 17 and 35 (95%)FC Internazionale Milano 1–2 Udinese Calcio (5.8%)
Bundesliga2025-26 ↺29821 / 20.9if the model is right: between 13 and 29 (95%)FC Bayern München 1–2 FC Augsburg (3.6%)
Ligue 12025-26 ↺29834 / 24.8if the model is right: between 16 and 33 (95%)above the interval: the model underestimated low-chance results this seasonOlympique de Marseille 0–2 FC Nantes (7.8%)
Liga 12024-25 ↺30011 / 14.3if the model is right: between 8 and 21 (95%)Sepsi OSK Sfantu Gheorghe 1–2 SCM Gloria Buzău (9.5%)

With 6 leagues compared, the chance that at least one falls outside the 95% interval by chance alone is 26%. A single league outside the interval is a signal to watch, not proof.

How to read it

How to read the figures on this page and what they do not say.

Updated: 25 Oct 2026, 07:20 UTC