Crystal Palace and Newcastle arrive with enough attacking intent to stretch this contest, while both leaky defenses invite sustained danger. Their combined chance-creation profile points toward an open, end-to-end battle, with momentum and defensive gaps making further scoring likely.
Match GoalsOver 2.5
Best Pick
BTTS
53%
Correct Score
Top
1-1
12.5%
7.50
Top
1-0
10.3%
15.00
0-1
9.1%
12.00
2-1
8.6%
12.00
1-2
7.6%
10.00
0-0
7.5%
15.00
2-0
7.1%
19.00
0-2
5.5%
15.00
141%
2.88TOP
X26%
3.60
233%
2.38
1X67%
X259%
1274%
Combined Bet Builder
3 legs
Crystal Palace’s 1.38 xG and Newcastle’s 1.35 point to chances at both ends, while leaky defences make goals more attainable despite modest attacking ratings. Newcastle’s 5.39 expected corners, added to Palace’s 4.31, supports Over 8.5 corners. Over 2.5 goals and both teams to score appear the logical match narrative.
1Match GoalsOver 2.5
2Both Teams to ScoreYes
3Corners Over/UnderOver 8.5
Confirmed XI3-5-2
44
Benítez
6
Canvot
26
Richards
21
Ahanor
25
Khalaili
20
Wharton
23
Timber
3
Mitchell
18
Kamada
10
Pino
22
Larsen
Impact Player Hot Head
Crystal Palace32 players
50.9/ 99Average
Top Rated
1Maxence LacroixDEF77
2Quinten TimberMID68
3Romain EsseMID68
Newcastle United27 players
52.2/ 99Average
Top Rated
1Fabian SchärDEF76
2Alex MurphyDEF74
3William OsulaFWD71
Player Rankings
Snipers
Top goal threats
1
William OsulaNewcastle United
70
2
Bazoumana TouréNewcastle United
58
3
Eddie Nketiah Crystal Palace
57
4
Harvey BarnesNewcastle United
56
5
Sean NeaveNewcastle United
54
Wall
Top defenders
1
Alex MurphyNewcastle United
99
2
Sven BotmanNewcastle United
81
3
Maxence LacroixCrystal Palace
78
4
Fabian SchärNewcastle United
71
5
Chris RichardsCrystal Palace
68
Control
Top playmakers
1
Nico GonzálezNewcastle United
73
2
Bruno GuimarãesNewcastle United
72
3
Adam WhartonCrystal Palace
71
4
Jefferson LermaCrystal Palace
64
5
Romain EsseCrystal Palace
58
Bad Boys
Most likely to get booked
1
Yoane WissaNewcastle United
1
Aggression 38
2
Sven BotmanNewcastle United
9
Aggression 27
3
Brennan JohnsonCrystal Palace
15
Aggression 51
4
Jacob MurphyNewcastle United
16
Aggression 16
5
Jacob RamseyNewcastle United
17
Aggression 60
Power Rankings
Strongest overall
1
Maxence LacroixCrystal Palace
77
2
Fabian SchärNewcastle United
76
3
Alex MurphyNewcastle United
74
4
William OsulaNewcastle United
71
5
Quinten TimberCrystal Palace
68
Frequently Asked Questions
Our Poisson model calculates the probability of every possible scoreline for Crystal Palace vs Newcastle United 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 Crystal Palace vs Newcastle United 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 Crystal Palace 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 Crystal Palace vs Newcastle United 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 Crystal Palace 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.