Nottingham Forest
L
L
L
D
L
W
-
(xG) 1.28 - 1.24
Manchester United
D
L
L
L
W
D
Mathematical Predictions
TOTAL GOALS
Under 2.5
Probability 53.93% Pending
MATCH RESULT
Draw
Pending

Nottingham Forest vs Manchester United

H2H, Match Stats & Analysis
England Premier League
City Ground
In their previous 9 head-to-head matches, Nottingham Forest scored an average of 1.33 goals per match, compared to Manchester United 1.89 goals.
Over their last 10 matches, Nottingham Forest scored an average of 0.50 and conceded 1.00, whereas Manchester United scored 0.83 and conceded 2.00.

What are the expected goals (xG) predicted in Nottingham Forest vs Manchester United match?

Based on the H2H and Form statistics, the expected goals (xG) for this match are 1.28 for Nottingham Forest and 1.24 for Manchester United. Mathematical prediction based on the algorithm is Under 2.5 with Poisson distribution probability of 53.93%.

H2H - Nottingham Forest vs. Manchester United

20-02-2027
Nottingham Forest
-
(HT -)
Manchester United
27-12-2026
Manchester United
-
(HT -)
Nottingham Forest
17-05-2026
Manchester United
3 - 2
(HT 1-0)
Nottingham Forest
01-11-2025
Nottingham Forest
2 - 2
(HT 0-1)
Manchester United
01-04-2025
Nottingham Forest
1 - 0
(HT 1-0)
Manchester United
07-12-2024
Manchester United
2 - 3
(HT 1-1)
Nottingham Forest
28-02-2024
Nottingham Forest
0 - 1
(HT 0-0)
Manchester United
30-12-2023
Nottingham Forest
2 - 1
(HT 0-0)
Manchester United
26-08-2023
Manchester United
3 - 2
(HT 1-2)
Nottingham Forest
16-04-2023
Nottingham Forest
0 - 2
(HT 0-1)
Manchester United
27-12-2022
Manchester United
3 - 0
(HT 2-0)
Nottingham Forest

Team Form (Last 6)

Home Crest Nottingham Forest

19.09 vs Coventry 0-1
L
11.10 @ Crystal Palace 3-1
L
18.10 vs Arsenal 0-1
L
23.10 @ Ipswich 1-1
D
31.10 @ Brentford 2-0
L
07.11 vs Manchester City 3-1
W

Away Crest Manchester United

18.10 @ Leeds 1-1
D
21.10 @ Como 4-1
L
25.10 vs Bournemouth 0-3
L
31.10 @ Chelsea 2-0
L
03.11 vs AS Roma 3-2
W
08.11 vs Aston Villa 4-4
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.