Las Palmas’ home pressure should generate sustained chances, while Sociedad B’s vulnerable back line offers a clear route to goals. Their attacking threat can add to the drama, making the match appear destined to break beyond a cautious stalemate.
Match GoalsOver 2.5
Best Pick
Under 2.5
52%
Correct Score
Top
1-1
12%
6.50
Top
1-0
11.6%
9.00
2-1
9.4%
9.00
2-0
9.1%
10.00
0-1
7.7%
13.00
0-0
7.4%
12.00
1-2
6.2%
13.00
2-2
4.9%
12.00
150%
2.00TOP
X25%
3.40
225%
3.75
1X75%
X250%
1275%
Combined Bet Builder
4 legs
Las Palmas’ home advantage and stronger defensive structure set the platform, while their attacking threat should find openings against a leaky Sociedad B back line. The visitors can contribute to an open contest, with chances and sustained pressure pointing toward a high-scoring game and a busy corner count. Elías Romero looks well placed to seize his moment as Las Palmas take control.
1Match WinnerLas Palmas
2Match GoalsOver 2.5
3GoalscorersAnytime
4Corners Over/UnderOver 8.5
Confirmed XI4-5-1
13
Caro
25
Pezzolesi
4
Suárez
15
Herzog
23
Rodríguez
20
Rodríguez
12
Loiodice
11
Miyashiro
14
Fuster
24
Jaime
10
Jesé
Impact Player Hot Head
Las Palmas28 players
48.3/ 99Average
Top Rated
1Sandro Ramírez FWD93
2Juanma HerzogDEF69
3Iñaki GonzálezMID66
Real Sociedad B28 players
53.6/ 99Average
Top Rated
1Iker CalderonDEF79
2Joan OleagaMID77
3Sydney OsazuwaFWD77
Player Rankings
Snipers
Top goal threats
1
Sandro Ramírez Las Palmas
99
2
Jefté BetancorLas Palmas
76
3
Sydney OsazuwaReal Sociedad B
69
4
Dani DíazReal Sociedad B
67
5
Javier SoroetaReal Sociedad B
67
Wall
Top defenders
1
Juanma HerzogLas Palmas
79
2
Kazunari KitaReal Sociedad B
76
3
Iker CalderonReal Sociedad B
65
4
Unax LarrañagaReal Sociedad B
65
5
Peru Larrañaga VázquezReal Sociedad B
64
Control
Top playmakers
1
Kirian Rodríguez Las Palmas
82
2
Joan OleagaReal Sociedad B
76
3
Iñaki GonzálezLas Palmas
69
4
Tomy CarbonellReal Sociedad B
64
5
Edward CedeñoLas Palmas
63
Bad Boys
Most likely to get booked
1
Iván JaimeLas Palmas
1
Aggression 41
2
Elías RomeroLas Palmas
1
Aggression 62
3
Jon GarroReal Sociedad B
1
Aggression 23
4
Alex LebarbierReal Sociedad B
10
Aggression 54
5
Sergio Ruiz Las Palmas
11
Aggression 57
Power Rankings
Strongest overall
1
Sandro Ramírez Las Palmas
93
2
Iker CalderonReal Sociedad B
79
3
Joan OleagaReal Sociedad B
77
4
Sydney OsazuwaReal Sociedad B
77
5
Kazunari KitaReal Sociedad B
76
Frequently Asked Questions
Our Poisson model calculates the probability of every possible scoreline for Las Palmas vs Real Sociedad B 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 Las Palmas vs Real Sociedad B 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 Las Palmas 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 Las Palmas vs Real Sociedad B 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 Las Palmas 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.