Both sides arrive with little attacking force, but their fragile defenses provide the opening this contest needs. Thun’s back line looks especially vulnerable, while Hearts are far from secure; one breakthrough could expose both and turn a cautious start into a frantic exchange. The defensive cracks make a three-goal game the likeliest script.
Match GoalsOver 2.5
Best Pick
BTTS
55%
Correct Score
Top
1-1
11.5%
7.00
Top
1-0
10.3%
12.00
2-1
9.6%
9.50
2-0
8.6%
15.00
0-1
6.8%
15.00
1-2
6.4%
12.00
0-0
6.1%
17.00
2-2
5.4%
11.00
150%
1.95TOP
X24%
3.75
225%
3.40
1X74%
X249%
1275%
Combined Bet Builder
3 legs
FC Thun’s home edge and Hearts’ leaky defence make the hosts-or-draw the logical anchor. Both sides project 1.54 xG, while Thun’s defence is 39% weaker than average, pointing to chances at both ends and a likely Over 2.5. Their combined 9.77 expected corners also supports Over 8.5.
1Double ChanceFC Thun or Draw
2Match GoalsOver 2.5
3Corners Over/UnderOver 8.5
Confirmed XI4-3-3
1
Steffen
47
Fehr
23
Bürki
19
Bamert
2
Mambwa
70
Reichmuth
16
Roth
14
Käit
30
Maier
96
Labeau
9
Dursun
Impact Player Hot Head
FC Thun31 players
49.9/ 99Average
Top Rated
1Riccardo BraschiFWD86
2Jan BamertDEF74
3Genís MontolioDEF72
Hearts29 players
48.3/ 99Average
Top Rated
1Oisin McEnteeDEF77
2Laurent MendyMID65
3Cláudio BragaFWD65
Player Rankings
Snipers
Top goal threats
1
Riccardo BraschiFC Thun
93
2
Cláudio BragaHearts
55
3
Layton StewartFC Thun
46
4
Marc GutbubFC Thun
46
5
Simon LengenFC Thun
44
Wall
Top defenders
1
Craig HalkettHearts
80
2
Jamie McCart Hearts
73
3
Genís MontolioFC Thun
70
4
Jan BamertFC Thun
70
5
Louis PassavantFC Thun
70
Control
Top playmakers
1
Nassim ZoukitFC Thun
74
2
Blair SpittalHearts
71
3
Yan Dhanda Hearts
62
4
Mattias KäitFC Thun
48
5
Nico MaierFC Thun
48
Bad Boys
Most likely to get booked
1
Olivier MambwaFC Thun
1
Aggression 54
2
Christopher IbayiFC Thun
1
Aggression 45
3
Blair SpittalHearts
1
Aggression 31
4
Yan Dhanda Hearts
1
Aggression 35
5
Adam IlicFC Thun
9
Aggression 68
Power Rankings
Strongest overall
1
Riccardo BraschiFC Thun
86
2
Oisin McEnteeHearts
77
3
Jan BamertFC Thun
74
4
Genís MontolioFC Thun
72
5
Nils ReichmuthFC Thun
68
Frequently Asked Questions
Our Poisson model calculates the probability of every possible scoreline for FC Thun vs Hearts 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 FC Thun vs Hearts 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 FC Thun 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 FC Thun vs Hearts 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 FC Thun 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.