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Primeira Liga
Referee: Rui Oliveira
Feirense
S T U S U
2–1
Full-time
Rio Ave
T U T T S

Retrospective analysis — the model is trained only on matches played before this one.

🔒 Who wins? Pro

The model's probabilities for a home win, draw and away win — with reasoning and recommended markets.

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Team trends

Feirense Rio Ave
Last 6 — all competitions · 6/6 matches
Win Ø 33%
33%
33%
Points per game
1,3
1,2
Over 2.5 Ø 34%
17%
50%
Both score Ø 42%
33%
50%
Average goals
1,7
2,8
Scored
0,8
1,2
Conceded
0,8
1,7
Goal diff per game
+0,0
-0,5
This season — Primeira Liga · 19/19 matches
Win Ø 34%
26%
42%
Points per game
1,0
1,4
Over 2.5 Ø 48%
42%
53%
Both score Ø 48%
37%
58%
Average goals
2,5
2,6
Scored
0,8
1,3
Conceded
1,7
1,4
Goal diff per game
-0,9
-0,1
🔒 Goal markets Pro

Expected goals, over/under and both teams to score — priced by the model before kick-off.

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🔒 Most likely result Pro

The model's top final scores with the best bookmaker odds.

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Match stats

Half-time score: 1–0

28% Possession 72%
7 Shots 11
3 Shots on target 3
1 Blocked shots 2
2 Goalkeeper saves 1
2 Corners 11
5 Offside 2
20 Free kicks against 18
3 Yellow cards 1
0 Red cards 0
The table before the match Feirense 14. · Rio Ave 9.
# Team K V U T +/− P
1 Benfica 20 15 3 2 +32 48
2 Porto 20 14 5 1 +28 47
3 Sp Lisbon 20 11 5 4 +14 38
4 Sp Braga 19 11 3 5 +14 36
5 Guimaraes 20 10 5 5 +7 35
6 Maritimo 20 9 4 7 +2 31
7 Chaves 20 6 10 4 +2 28
8 Vitoria Setubal 20 8 4 8 +1 28
9 Rio Ave 19 8 3 8 -2 27
10 Arouca 20 8 3 9 -4 27
11 Boavista 20 6 7 7 -1 25
12 Belenenses 20 6 6 8 -5 24
13 Pacos Ferreira 20 5 5 10 -11 20
14 Feirense 19 5 4 10 -18 19
15 Moreirense 20 5 3 12 -13 18
16 Estoril 19 4 3 12 -11 15
17 Tondela 20 3 5 12 -18 14
18 Nacional 20 3 4 13 -17 13

Calculated from our results data. “xG +/−” is expected goal difference — a positive number with a low league position suggests an undervalued team. Ties on points are sorted by goal difference; some leagues use other rules.

Recent head-to-head meetings

28. Aug -16 Rio Ave – Feirense 1–0

The analysis is a statistical estimate based on the teams' results and underlying performances (xG) — not a guarantee. See the model's results.