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Ligue 1
Referee: Frank Schneider
Bastia
S T U S T
1–0
Full-time
Montpellier
T U S T T

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

Bastia Montpellier
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
1,3
Conceded
0,8
1,5
Goal diff per game
+0,0
-0,2
This season — Ligue 1 · 20/20 matches
Win Ø 30%
30%
30%
Points per game
1,1
1,1
Over 2.5 Ø 43%
40%
45%
Both score Ø 48%
45%
50%
Average goals
2,3
2,4
Scored
1,0
1,1
Conceded
1,3
1,3
Goal diff per game
-0,3
-0,2
🔒 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

44% Possession 56%
2 Shots 8
1 Shots on target 1
0 Blocked shots 2
1 Goalkeeper saves 0
1 Corners 5
3 Offside 2
0 Free kicks against 0
3 Yellow cards 1
1 Red cards 1
The table before the match Bastia 16. · Montpellier 15.
# Team K V U T +/− P
1 Paris SG 21 18 3 0 +42 57
2 Angers 21 9 7 5 +7 34
3 Nice 21 9 6 6 +10 33
4 Monaco 20 8 9 3 +2 33
5 Caen 20 9 3 8 -3 30
6 Lyon 20 8 5 7 +3 29
7 St Etienne 20 9 2 9 -1 29
8 Rennes 20 6 10 4 +4 28
9 Lorient 20 6 9 5 +1 27
10 Nantes 20 7 6 7 -2 27
11 Marseille 20 6 8 6 +7 26
12 Bordeaux 20 6 8 6 -4 26
13 Lille 20 5 10 5 +2 25
14 Gazelec FC Ajaccio 20 6 7 7 -2 25
15 Montpellier 20 6 4 10 -4 22
16 Bastia 20 6 4 10 -6 22
17 Reims 20 5 6 9 -7 21
18 Guingamp 20 5 5 10 -10 20
19 Toulouse 21 4 8 9 -11 20
20 Troyes 20 0 8 12 -28 8

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

24. Oct -15 Montpellier – Bastia 2–0

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