Upset index
UEFA Champions League upset index
Including the years before odds: the biggest upsets in history, the most chaotic seasons and the giant killers by our learning Elo model's pre-match probabilities. Index 100 = as many upsets as expected.
- Matches with a clear favourite
- 4,459
- Upsets
- 1,113
- Upset rate
- 25.0%
- Upset index
- 119
Filters
Model data: 2,476,630 matches with a clear favourite between 26 Apr 1970 and 7 Nov 2026 (learning Elo, pre-match state).
Biggest upsets
By the winner's pre-match chance (Elo model) — lowest first
-
UEFA Champions League
GNK Dinamo Zagreb2
SV Werder Bremen3
Winner's pre-match chance 7.1%
-
UEFA Champions League
Benfica2
Qarabağ FK3
Winner's pre-match chance 7.4%
-
UEFA Champions League
Manchester City1
Olympique Lyonnais2
Winner's pre-match chance 8.4%
-
UEFA Champions League
Rangers0
VfB Stuttgart2
Winner's pre-match chance 8.9%
-
UEFA Champions League
PSV Eindhoven1
Girondins de Bordeaux3
Winner's pre-match chance 9.0%
-
UEFA Champions League
Inter3
Club Brugge KV4
Winner's pre-match chance 10%
-
FC Porto
0–4
Club Brugge KV
-
RSC Anderlecht
1–2
SV Werder Bremen
-
Celtic
0–1
RSC Anderlecht
-
HŠK Zrinjski Mostar
2–3
Urartu
-
RSC Anderlecht
1–4
Leeds United
-
GNK Dinamo Zagreb
1–2
Olympique de Marseille
-
Basel
2–3
AS Roma
-
Valencia
0–3
AS Roma
-
Dinamo Tbilisi
0–1
FK Aktobe
-
Hapoel Tel Aviv
1–3
Olympique Lyonnais
-
Manchester City
1–3
Olympique Lyonnais
-
Manchester City
1–2
Basel
-
Dynamo Kyiv
1–2
Borussia M'gladbach
-
GNK Dinamo Zagreb
1–3
Shakhtar Donetsk
-
Arsenal
1–2
AJ Auxerre
-
Debreceni VSC
3–4
Fiorentina
-
RB Leipzig
0–2
Olympique Lyonnais
-
RB Leipzig
1–2
Club Brugge KV
-
FC Kairat Almaty
2–1
FK Crvena zvezda
-
AS Trenčín
2–3
NK Olimpija Ljubljana
-
Basel
1–2
FC Bayern München
-
Real Madrid
3–4
FC Schalke 04
-
FC Zürich
0–1
Olympique de Marseille
-
Manchester United
0–1
Beşiktaş JK
-
FC Bayern München
0–2
Arsenal
-
Liverpool FC
0–1
Olympique de Marseille
-
Galatasaray
0–1
Royale Union Saint-Gilloise
-
Zenit St. Petersburg
1–2
Club Brugge KV
-
LASK
0–1
Club Brugge KV
-
Arsenal
2–3
Olympiacos FC
-
FC Zürich
2–5
Real Madrid
-
SV Werder Bremen
2–1
GNK Dinamo Zagreb
-
PSV Eindhoven
1–2
AS Monaco
-
Galatasaray
0–1
Borussia Dortmund
UEFA Champions League: by season
The most chaotic and most predictable seasons
Giant killers
Win more than expected as the underdog
| Team | Underdog wins | Expected | Index |
|---|---|---|---|
| Real Madrid |
48/100 | 25.5 | 196 |
| Olympique Lyonnais |
37/92 | 21.2 | 180 |
 FC Barcelona |
31/78 | 20.2 | 160 |
| Fiorentina |
8/18 | 3.9 | 156 |
 Paris Saint-Germain |
24/64 | 15.8 | 155 |
 Chelsea |
22/55 | 14.5 | 154 |
| FC Schalke 04 |
16/47 | 10.1 | 154 |
| FC Bayern München |
29/82 | 20.4 | 151 |
 Legia |
8/18 | 4.3 | 150 |
 AC Milan |
32/96 | 23.3 | 148 |
Upset victims
Lose more than expected as the favourite
| Team | Losses as favourite | Expected | Index |
|---|---|---|---|
| RSC Anderlecht |
15/28 | 6.9 | 183 |
| Dinamo Tbilisi |
7/11 | 2.3 | 172 |
 FCSB |
21/48 | 11.9 | 171 |
 The New Saints |
12/27 | 5.9 | 168 |
| Rangers |
19/48 | 10.8 | 168 |
| GNK Dinamo Zagreb |
24/65 | 15.4 | 158 |
| Debreceni VSC |
6/10 | 2.3 | 158 |
 AC Sparta Praha |
20/49 | 13.0 | 155 |
| FC Zürich |
6/11 | 2.5 | 154 |
 Brøndby IF |
5/7 | 1.8 | 153 |
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 (0.86 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.