Upset index
FIFA World Cup upset index
Matches won by the side the pre-match odds gave little chance, and which leagues and teams produce more upsets than expected. Index 100 = as many upsets as expected.
- Matches with a clear favourite
- 93
- Upsets
- 8
- Upset rate
- 8.6%
- Upset index
- 71
Filters
Odds data: 556,134 matches with a clear favourite between 31 Dec 2015 and 8 Nov 2026.
Biggest upsets
By the winner's pre-match chance (from odds) — lowest first
-
FIFA World Cup
South Africa1
South Korea0
Winner's pre-match chance 16% · odds 5.75
-
FIFA World Cup
Australia2
Türkiye0
Winner's pre-match chance 18% · odds 5.25
-
FIFA World Cup
Ecuador2
Germany1
Winner's pre-match chance 20% · odds 4.75
-
FIFA World Cup · Round of 16
Brazil1
Norway2
Winner's pre-match chance 21% · odds 4.50
-
FIFA World Cup
France4
England6
Winner's pre-match chance 23% · odds 4.10
-
FIFA World Cup
Türkiye0
Paraguay1
Winner's pre-match chance 25% · odds 3.80
FIFA World Cup: by season
The most chaotic and most predictable seasons
Giant killers
Win more than expected as the underdog
| Team | Underdog wins | Expected | Index |
|---|---|---|---|
| England |
1/1 | 0.2 | 115 |
| Türkiye |
1/1 | 0.3 | 114 |
| Ecuador |
1/2 | 0.4 | 111 |
| Norway |
1/3 | 0.6 | 108 |
| Paraguay |
1/4 | 0.7 | 107 |
 Côte d'Ivoire |
1/3 | 0.7 | 106 |
| South Africa |
1/4 | 0.7 | 106 |
| Australia |
1/4 | 0.9 | 103 |
Upset victims
Lose more than expected as the favourite
How is it calculated?
- Probability: From pre-match 1X2 (or two-way) odds, with the bookmaker margin removed proportionally: p = (1/odds) / Σ(1/odds). The same formula as the stats hub's “upsets by odds” block.
- Clear favourite and upset: Only matches with at least a 10-point gap between the home and away win probabilities count; if the favourite's opponent wins, it is an upset. Draws are not upsets. Winner's chance of 25% or less = big upset.
- Ranking: The lower the winner's pre-match chance, the bigger the upset (surprise score = 100 × (1 − chance)).
- Index: 100 × (actual upsets + 5) / (expected upsets + 5); expected = sum of the underdogs' win probabilities. The +5 pulls small samples towards 100. Teams have two directions: giant killing (winning as the underdog) and fragility (losing as the favourite).
- Calibration: Expected values are scaled by the source's overall hit factor (0.95 in this view), so a systematic bias of the source does not shift every league the same way.
- Historical (model): For past matches without odds, the probability comes from our learning Elo model replaying the full history chronologically and taking its state before the match (both teams need at least 15 matches; friendlies excluded). Never mixed with odds.