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Ligue 2
Pau FC
T S T S T
1–2
Full-time

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

Pau FC Quevilly Rouen
Last 6 — all competitions · 6/6 matches
Win Ø 34%
50%
17%
Points per game
1,5
0,8
Over 2.5 Ø 50%
33%
67%
Both score Ø 42%
33%
50%
Average goals
2,2
2,3
Scored
1,0
0,7
Conceded
1,2
1,7
Goal diff per game
-0,2
-1,0
This season — Ligue 2 · 17/17 matches
Win Ø 35%
41%
29%
Points per game
1,4
1,2
Over 2.5 Ø 44%
35%
53%
Both score Ø 47%
41%
53%
Average goals
2,1
2,2
Scored
1,1
0,9
Conceded
1,1
1,3
Goal diff per game
+0,0
-0,4
🔒 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: 0–0

20 Shots 9
5 Shots on target 6
6 Corners 0
17 Free kicks against 10
1 Yellow cards 1
0 Red cards 0
The table before the match Pau FC 8. · Quevilly Rouen 13.
# Team K V U T +/− P
1 Ajaccio 18 10 5 3 +11 35
2 Toulouse 17 9 6 2 +21 33
3 Sochaux 17 9 4 4 +4 31
4 Auxerre 17 8 6 3 +8 30
5 Paris FC 17 9 3 5 +5 30
6 Le Havre 18 7 8 3 +6 29
7 Rodez 17 7 4 6 +3 25
8 Pau FC 17 7 3 7 +0 24
9 Niort 17 7 3 7 -1 24
10 Guingamp 17 5 6 6 -3 21
11 Grenoble 17 6 3 8 -5 21
12 Nimes 17 5 5 7 -2 20
13 Quevilly Rouen 17 5 5 7 -6 20
14 Valenciennes 17 5 5 7 -9 20
15 Dijon 17 6 1 10 -6 19
16 Amiens 17 3 9 5 +1 18
17 Caen 17 4 6 7 -1 18
18 Bastia 17 4 6 7 -3 18
19 Dunkerque 17 4 4 9 -8 16
20 Nancy 17 2 6 9 -15 12

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.

Odds comparison

Green columns are the outcomes that came in.

1X2
H
1,93
U
3,23
B ✓
4,20
Over/under goals
O1,5 ✓
O2,5 ✓
2,34
U2,5
1,57
U3,5 ✓
Both teams to score
BLS ja ✓
BLS nei

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