SSV Ulm 1846
W
W
W
W
L
L
-
(xG) 2.00 - 2.50
FC Zurich
W
D
W
W
W
D

Mathematical Predictions: SSV Ulm 1846 vs FC Zurich

TOTAL GOALS
Over 2.5
Probability 82.64% Pending
MATCH RESULT
Away Win
Pending

Historical Prediction Track Records

SSV Ulm 1846 team crest SSV Ulm 1846 Past Prediction Accuracy

Historical prediction accuracy and match outcomes for SSV Ulm 1846
Date Fixture 1X2 O/U 2.5 FT
01 Aug 26 @ SSV Jahn Regensburg X O2.5 1-0
25 Jul 26 vs Stuttgart II X O2.5 0-4
19 Jul 26 vs Bayern München II X O2.5 3-1
14 Jul 26 vs Augsburg II 1 O2.5 2-1

FC Zurich team crest FC Zurich Past Prediction Accuracy

Historical prediction accuracy and match outcomes for FC Zurich
Date Fixture 1X2 O/U 2.5 FT
08 Nov 26 @ Servette FC 1 O2.5 0-0
01 Nov 26 @ BSC Young Boys 1 O2.5 3-5
24 Oct 26 vs FC Luzern X O2.5 2-1
10 Oct 26 vs FC Thun X O2.5 4-2
19 Sep 26 @ FC Sion X O2.5 1-1

SSV Ulm 1846 vs FC Zurich

H2H, Match Stats & Analysis
World Friendlies Clubs
TBC
In their previous 0 head-to-head matches, SSV Ulm 1846 scored an average of 0.00 goals per match, compared to FC Zurich 0.00 goals.
Over their last 10 matches, SSV Ulm 1846 scored an average of 2.00 and conceded 2.00, whereas FC Zurich scored 3.00 and conceded 2.00.

What are the expected goals (xG) predicted in SSV Ulm 1846 vs FC Zurich match?

Based on the H2H and Form statistics, the expected goals (xG) for this match are 2.00 for SSV Ulm 1846 and 2.50 for FC Zurich. Mathematical prediction based on the algorithm is Over 2.5 with Poisson distribution probability of 82.64%.

H2H - SSV Ulm 1846 vs. FC Zurich

20 Jul 25
SSV Ulm 1846
-
(HT -)
FC Zurich

Team Form (Last 6)

Home Crest SSV Ulm 1846

01 Jul @ Schwabmünchen 1-3
W
10 Jul vs Eichstätt 4-3
W
14 Jul vs Augsburg II 2-1
W
19 Jul vs Bayern München II 3-1
W
25 Jul vs Stuttgart II 0-4
L
01 Aug @ Jahn Regensburg 1-0
L

Away Crest FC Zurich

13 Sep vs FC Vaduz 2-1
W
19 Sep @ FC Sion 1-1
D
10 Oct vs FC Thun 4-2
W
24 Oct vs FC Luzern 2-1
W
01 Nov @ BSC Young Boys 3-5
W
08 Nov @ Servette FC 0-0
D

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.