Al-Shabab Club Stadium
Al Shabab
L D W D W W
VS
xG 2.28 - 1.56
NEOM
W W D L L W

Mathematical Predictions: Al Shabab vs NEOM

TOTAL GOALS
Over 2.5
Probability 73.64% Pending
MATCH RESULT
Draw
Pending

Historical Prediction Track Records

Al Shabab team crest Al Shabab Past Prediction Accuracy

Historical prediction accuracy and match outcomes for Al Shabab
Date Fixture 1X2 O/U 2.5 FT
30 Oct 26 vs Al-Ahli Jeddah X O2.5 6-1
22 Oct 26 @ Al-Fateh X U2.5 1-3
19 Oct 26 vs Al-Faisaly FC 1 O2.5 2-2
11 Oct 26 vs Al Taawon 2 O2.5 3-0
12 Sep 26 vs Al-Fayha 1 O2.5 0-0

NEOM team crest NEOM Past Prediction Accuracy

Historical prediction accuracy and match outcomes for NEOM
Date Fixture 1X2 O/U 2.5 FT
30 Oct 26 @ Al Diriyah X U2.5 1-2
24 Oct 26 vs Abha 1 O2.5 2-0
20 Oct 26 @ Al-Nassr 1 U2.5 1-0
17 Oct 26 vs Al-Ettifaq X U2.5 0-1
10 Oct 26 @ Al-Hazm X U2.5 1-1

Al Shabab vs NEOM

H2H, Match Stats & Analysis
Al-Shabab Club Stadium
In their previous 2 head-to-head matches, Al Shabab scored an average of 2.00 goals per match, compared to NEOM 2.00 goals.
Over their last 10 matches, Al Shabab scored an average of 2.33 and conceded 1.33, whereas NEOM scored 1.17 and conceded 0.67.

What are the expected goals (xG) predicted in Al Shabab vs NEOM match?

Based on the H2H and Form statistics, the expected goals (xG) for this match are 2.28 for Al Shabab and 1.56 for NEOM. Mathematical prediction based on the algorithm is Over 2.5 with Poisson distribution probability of 73.64%.

H2H - Al Shabab vs. NEOM

16 Dec 26
Al Shabab
-
(HT -)
NEOM
11 May 26
NEOM
2 - 1
(HT 2-0)
Al Shabab
14 Jan 26
Al Shabab
3 - 2
(HT 1-1)
NEOM

Team Form (Last 6)

Home Crest Al Shabab

09 Sep @ Al Kholood 2-1
L
12 Sep vs Al-Fayha 0-0
D
11 Oct vs Al Taawon 3-0
W
19 Oct vs Al-Faisaly FC 2-2
D
22 Oct @ Al-Fateh 1-3
W
30 Oct vs Al-Ahli Jeddah 6-1
W

Away Crest NEOM

07 Sep @ Al-Hilal Saudi FC 0-2
W
13 Sep vs Al-Fateh 4-2
W
10 Oct @ Al-Hazm 1-1
D
17 Oct vs Al-Ettifaq 0-1
L
20 Oct @ Al-Nassr 1-0
L
24 Oct vs Abha 2-0
W

Poisson Distribution Algorithm

We utilize a Poisson distribution model to evaluate goal probability (such as the 2.5 threshold) in professional fixtures. By assessing expected offensive and defensive ratings for both home and away sides, our engine calculates precise percentage outcomes for your match predictions.