Football · Brazil Serie A · 12/10, 00:30

Prediction: EC Bahia vs Mirassol

Team pages: EC Bahia · Mirassol

Prediction summary
Expected goals
2.93Total
EC Bahia1.9
Mirassol1.03
1X2
56% 25% 19%
EC Bahia Draw Mirassol
Markets
Over 2.5 goals 56% Both teams to score 54%
Most likely score
1-1 12%
Recent form · 10 last
EC Bahia 4-4-2 (W-D-L)
DDDDWWWWLL
Mirassol 3-4-3 (W-D-L)
WLLDDLWDWD
Head-to-head
EC Bahia 1–1–1 Mirassol (3 last)
  • Mirassol1-2EC Bahia
  • Mirassol5-1EC Bahia
  • EC Bahia1-1Mirassol
Our model (Elo) vs Market Rating Elo · EC Bahia 1537 · Mirassol 1491
EC BahiaDrawMirassol
Our model57%24%19%
Market56%25%19%
Estimated total (ours) 2.93 goals · Bet365 line 2.75 · +0.2

The bar above blends our model with the market: where our probability diverges most from the odds is where the model sees the widest gap.

Model analysis
1st-half goalsOver 1.5 · 62%model estimate

Match keys

  • Our model (Elo, opponent-adjusted) favours EC Bahia (rating 1537 vs 1491).
  • Cards-heavy: 7.7 🟨 combined avg.

Statistics · 10/10 matches analysed

F = for · A = against · HT = half-time · FT = full-time

EC BahiaMirassol
Goals for / against (FT)1.5 / 1.21.3 / 1.7
Goals for / against (HT)1 / 0.70.5 / 0.7
Half-time result (W/D/L)30/60/10%20/50/30%
Corners (HT / FT)2.1 / 4.82.3 / 4.8
Cards (🟨 / 🟥)4.1 / 03.6 / 0.3

Head-to-head (H2H) · EC Bahia 1–1–1 Mirassol

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DateHomeScoreAway
11/04/26
Brazil Serie A
Mirassol1-2
HT 1-0
EC Bahia
31/08/25
Brazil Serie A
Mirassol5-1
HT 3-0
EC Bahia
13/04/25
Brazil Serie A
EC Bahia1-1
HT 1-1
Mirassol

Standings · Brazil Serie A

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#Team PWDL GFGAPts
1 Flamengo 291874 572561
2 Palmeiras 291793 482160
3 Fluminense 291496 483651
4 Athletico Paranaense 291487 453450
5 Cruzeiro 291469 444048
6 EC Bahia 2912107 433646
7 Atletico Mineiro 291289 393444
8 Santos 291199 454342
9 Sao Paulo 3011613 353539
10 Coritiba 2910811 374738
11 Bragantino 2910712 343337
12 Vitoria 3010614 334436
13 Botafogo 299812 424735
14 Vasco da Gama 299812 364235
15 Mirassol 298912 344333
16 Corinthians 298813 303432
17 Internacional 2971012 323731
18 Gremio 297913 313930
19 Remo 3051015 334825
20 Chapecoense 283916 295718

Common opponents 4 opponents

How each team fared against the same recent opponents

OpponentEC BahiaMirassol
Palmeiras 0-1 L 1-1 D
Remo 2-1 W 2-1 W
Bragantino 3-2 W 1-1 D
Vitoria 2-0 W 2-2 D
Record vs common 3 W 0 D 1 L 1 W 3 D 0 L

Better against common opponents: EC Bahia (2 of 4 head-to-heads won)

Last 10 matches played

The averages above come from these matches. W = win, D = draw, L = loss. Common opponents to both are in blue.

EC Bahia

DDDDWWWWLL

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Date Opponent HT FT Cor.Cards Res.
09/10 Palmeiras
Brazil Serie A
0-1 0-1 33 L
21/09 Athletico Paranaense
Brazil Serie A
1-1 1-2 35 L
15/09 Remo
Brazil Serie A
1-0 2-1 73 W
05/09 Bragantino
Brazil Serie A
2-2 3-2 83 W
31/08 Internacional
Brazil Serie A
3-1 3-2 36 W
23/08 Vitoria
Brazil Serie A
0-0 2-0 76 W
16/08 Chapecoense
Brazil Serie A
2-1 3-3 53 D
09/08 Vasco da Gama
Brazil Serie A
0-0 0-0 43 D
30/07 Fluminense
Brazil Serie A
0-0 0-0 12 D
26/07 Corinthians
Brazil Serie A
1-1 1-1 77 D

Mirassol

WLLDDLWDWD

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Date Opponent HT FT Cor.Cards Res.
08/10 Bragantino
Brazil Serie A
0-0 1-1 31 D
19/09 Botafogo
Brazil Serie A
2-0 2-0 31 W
13/09 Vitoria
Brazil Serie A
0-2 2-2 1210 D
06/09 Coritiba
Brazil Serie A
0-0 2-1 75 W
03/09 Flamengo
Brazil Serie A
0-2 0-2 72 L
30/08 Palmeiras
Brazil Serie A
0-0 1-1 33 D
23/08 Santos
Brazil Serie A
1-0 1-1 26 D
16/08 Flamengo
Brazil Serie A
0-1 1-5 43 L
09/08 Cruzeiro
Brazil Serie A
1-1 1-3 14 L
30/07 Remo
Brazil Serie A
1-1 2-1 64 W

Frequently asked questions

Who is the favourite in EC Bahia vs Mirassol?

According to our model, the most likely result is a EC Bahia win (56%). Probabilities: EC Bahia 56%, draw 25%, Mirassol 19%.

How many goals are expected in EC Bahia vs Mirassol?

The model expects 2.93 goals (EC Bahia 1.9 · Mirassol 1.03), with a 51% chance of over 2.75 goals.

Will both teams score in EC Bahia vs Mirassol?

The model gives a 54% chance that both teams score.

What is the most likely score?

The most likely score according to our model is 1-1.