With combined xG of 3.20, this looks primed for goals: Monaco’s solid attack brings confidence, while Freiburg’s defense is slightly below average. Both sides have strong reasons to push in this European contest, and Monaco’s defensive strength may not be enough to shut out Freiburg. Over 2.5 appears the most logical call.
Match GoalsOver 2.5
Best Pick
Home Win
56%
Correct Score
Top
1-0
11.3%
9.50
Top
1-1
11%
7.00
2-0
10.1%
12.00
2-1
9.8%
9.00
0-0
6.3%
13.00
0-1
6.2%
12.00
3-0
6%
21.00
3-1
5.9%
17.00
156%
2.15TOP
X23%
3.60
220%
3.10
1X79%
X243%
1276%
Combined Bet Builder
4 legs
Monaco’s +10% attacking edge and stronger-than-average defence make the home-or-draw leg compelling. Combined xG of 3.20 points toward an open game, while 8.16 expected corners supports Over 7.5; Monaco’s attacking profile also gives Balogun a credible route to an anytime goal. A 4.84 builder looks well aligned with the matchup.
1Double ChanceAS Monaco or Draw
2Match GoalsOver 2.5
3GoalscorersAnytime
4Corners Over/UnderOver 7.5
Confirmed XI3-5-2
1
Hradecky
72
Sané
22
Salisu
13
Mawissa
4
Teze
8
Camara
6
Zakaria
18
Minamino
10
Golovin
31
Fati
29
Brunner
Impact Player Hot Head
AS Monaco32 players
53.4/ 99Average
Top Rated
1Paris BrunnerFWD91
2Paul PogbaMID86
3Aladji BambaMID80
SC Freiburg23 players
45.7/ 99Average
Top Rated
1Igor MatanovicFWD77
2Lukas KüblerDEF65
3Yuito SuzukiFWD63
Player Rankings
Snipers
Top goal threats
1
Ansu FatiAS Monaco
90
2
Paris BrunnerAS Monaco
90
3
Lucas MichalAS Monaco
85
4
Igor MatanovicSC Freiburg
69
5
Folarin BalogunAS Monaco
67
Wall
Top defenders
1
Mohammed SalisuAS Monaco
89
2
Sadibou Sané AS Monaco
70
3
Anthony JungSC Freiburg
65
4
Eric DierAS Monaco
62
5
J. TezeAS Monaco
54
Control
Top playmakers
1
Paul PogbaAS Monaco
99
2
Lamine CamaraAS Monaco
80
3
Aladji BambaAS Monaco
69
4
Ilane TouréAS Monaco
64
5
Anis SoubeirAS Monaco
55
Bad Boys
Most likely to get booked
1
Christian MawissaAS Monaco
1
Aggression 76
2
J. TezeAS Monaco
1
Aggression 65
3
Matthis AblineAS Monaco
1
Aggression 34
4
Cyriaque IriéSC Freiburg
1
Aggression 99
5
NazinhoAS Monaco
3
Aggression 55
Power Rankings
Strongest overall
1
Paris BrunnerAS Monaco
91
2
Paul PogbaAS Monaco
86
3
Aladji BambaAS Monaco
80
4
Igor MatanovicSC Freiburg
77
5
Ansu FatiAS Monaco
72
Frequently Asked Questions
Our Poisson model calculates the probability of every possible scoreline for AS Monaco vs SC Freiburg based on each team's expected goals (xG). The top-3 most likely scorelines are shown above with their probability percentages. Even the highest-probability score rarely exceeds 12-15% chance, as football is a low-scoring sport.
The Bet Builder combines multiple selections from the AS Monaco vs SC Freiburg match into one bet. Our AI identifies outcomes that complement each other — for example, a home win paired with over 2.5 goals and both teams to score. All selections must win for the combined bet to pay out, which means higher combined odds but also higher risk.
xG (expected goals) measures the quality of scoring chances. If AS Monaco has an xG of 1.8, it means they are expected to score around 1-2 goals based on chance quality. The model uses pre-match xG to build a probability table for all possible scorelines. A team can overperform xG (score more than expected) or underperform xG (score fewer).
Yes, all predictions on ProSoccer are completely free. You can view predicted scorelines, over/under probabilities, and bet builder suggestions for AS Monaco vs SC Freiburg without paying or registering. Odds values are revealed after a tap to keep the page compliant with search engine guidelines.
A value bet occurs when the probability of an outcome is higher than what the bookmaker odds suggest. For example, if our model gives AS Monaco a 55% chance of winning but the odds imply only 40%, that is a value bet. Our AI highlights selections where the model probability exceeds the implied probability from the odds.
AI predictions use statistical modeling (Poisson distribution) based on historical data and pre-match metrics. They are more reliable over large samples than for any single match. No prediction is guaranteed — football has inherent unpredictability. Our model typically identifies the correct top-3 scorelines in 25-30% of matches, which is significantly better than random chance.