Upset index
Ligue 1 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
- 66
- Upsets
- 11
- Upset rate
- 16.7%
- Upset index
- 86
Filters
Odds data: 555,994 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
-
Ligue 1
Paris Saint-Germain1
AS Monaco2
Winner's pre-match chance 12% · odds 7.50
-
Ligue 1
RC Lens0
Lorient1
Winner's pre-match chance 17% · odds 5.75
-
Ligue 1
Lorient1
Troyes2
Winner's pre-match chance 23% · odds 4.20
-
Ligue 1
RC Strasbourg2
RC Lens1
Winner's pre-match chance 24% · odds 4.00
-
Ligue 1
Olympique de Marseille2
Paris FC3
Winner's pre-match chance 25% · odds 3.75
-
Ligue 1
Lorient1
Paris FC0
Winner's pre-match chance 26% · odds 3.70
Ligue 1: by season
The most chaotic and most predictable seasons
Giant killers
Win more than expected as the underdog
| Team | Underdog wins | Expected | Index |
|---|---|---|---|
| Lorient |
3/3 | 0.7 | 142 |
| AS Monaco |
1/1 | 0.1 | 117 |
| Paris FC |
1/1 | 0.3 | 114 |
 Olympique Lyonnais |
1/2 | 0.4 | 111 |
 Stade Brestois |
1/3 | 0.7 | 107 |
 AJ Auxerre |
1/6 | 1.2 | 98 |
 Angers |
1/6 | 1.3 | 96 |
| Troyes |
1/8 | 1.6 | 92 |
| RC Strasbourg |
1/8 | 2.0 | 87 |
Upset victims
Lose more than expected as the favourite
| Team | Losses as favourite | Expected | Index |
|---|---|---|---|
| Lorient |
2/3 | 0.8 | 121 |
| RC Lens |
2/5 | 1.0 | 118 |
 Le Havre |
1/1 | 0.3 | 113 |
| AJ Auxerre |
1/2 | 0.5 | 109 |
| Paris Saint-Germain |
1/10 | 1.2 | 97 |
 Toulouse |
1/5 | 1.2 | 97 |
| Olympique de Marseille |
1/6 | 1.4 | 95 |
| Paris FC |
1/6 | 1.5 | 94 |
| AS Monaco |
1/7 | 1.8 | 89 |
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.