OrcaScore
Upset index

Carioca 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
45
Upsets
12
Upset rate
26.7%
Upset index
126

Filters

Odds data: 556,030 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

  1. Carioca Boavista1 Fluminense0 Winner's pre-match chance 16% · odds 5.75
  2. Carioca Nova Iguaçu0 Maricá FC1 Winner's pre-match chance 19% · odds 4.75
  3. Carioca Flamengo1 Vasco da Gama0 Winner's pre-match chance 23% · odds 4.00
  4. Carioca Maricá FC1 Bangu2 Winner's pre-match chance 23% · odds 4.00
  5. Carioca Bangu2 Flamengo1 Winner's pre-match chance 24% · odds 3.70
  6. Carioca Fluminense2 Flamengo1 Winner's pre-match chance 25% · odds 3.70
  1. Portuguesa-RJ 0–1 Maricá FC Carioca · 19 Jan 2026 25%
  2. Bangu 1–0 Volta Redonda Carioca · Semifinals · 21 Feb 2026 27%
  3. Maricá FC 0–4 Sampaio Corrêa-RJ Carioca · 12 Feb 2026 28%
  4. Nova Iguaçu 1–2 Bangu Carioca · 31 Jan 2026 28%
  5. Maricá FC 0–1 Sampaio Corrêa-RJ Carioca · 27 Jan 2026 28%
  6. Sampaio Corrêa-RJ 2–1 Botafogo Carioca · 19 Jan 2026 29%

Carioca: by season

The most chaotic and most predictable seasons

Giant killers

Win more than expected as the underdog

Giant killers
Team Underdog wins Expected Index
Bangu 4/8 1.4 142
Sampaio Corrêa-RJ 3/7 1.5 124
Maricá FC 2/5 1.0 117
Flamengo 1/1 0.2 115
Fluminense 1/2 0.5 110
Boavista 1/5 1.0 101

Upset victims

Lose more than expected as the favourite

Upset victims
Team Losses as favourite Expected Index
Maricá FC 3/3 0.8 139
Nova Iguaçu 2/4 0.9 120
Flamengo 2/8 1.3 112
Botafogo 1/5 0.8 104
Volta Redonda 1/4 0.8 104
Fluminense 1/6 0.9 102
Portuguesa-RJ 1/4 1.1 100
Vasco da Gama 1/7 1.4 95
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.