← Match Finder
Premier League
Referee: C Pawson
Bournemouth
U S S U S
5–0
Full-time
Nott'm Forest
S S S U S

Retrospective analysis — the model is trained only on matches played before this one.

🔒 Who wins? Pro

The model's probabilities for a home win, draw and away win — with reasoning and recommended markets.

Unlock with Pro

Already have an account? Log in

Team trends

Bournemouth Nott'm Forest
Last 6 — all competitions · 6/6 matches
Win Ø 67%
50%
83%
Points per game
2,0
2,7
Over 2.5 Ø 50%
67%
33%
Both score Ø 50%
67%
33%
Average goals
3,3
2,5
Scored
2,3
2,0
Conceded
1,0
0,5
Goal diff per game
+1,3
+1,5
xG created Pro
xG conceded Pro
xG diff Pro
This season — Premier League · 22/22 matches
Win Ø 52%
45%
59%
Points per game
1,7
2,0
Over 2.5 Ø 50%
55%
45%
Both score Ø 55%
64%
45%
Average goals
2,8
2,5
Scored
1,6
1,5
Conceded
1,2
1,0
Goal diff per game
+0,5
+0,5
xG created Pro
xG conceded Pro
xG diff Pro
🔒 Goal markets Pro

Expected goals, over/under and both teams to score — priced by the model before kick-off.

Unlock with Pro

Already have an account? Log in

🔒 Most likely result Pro

The model's top final scores with the best bookmaker odds.

Unlock with Pro

Already have an account? Log in

Match stats

Half-time score: 1–0

1,69 xG 0,98
51% Possession 49%
16 Shots 18
10 Shots on target 4
3 Blocked shots 5
4 Goalkeeper saves 5
3 Corners 9
2 Offside 2
9 Free kicks against 12
2 Yellow cards 3
0 Red cards 0
The table before the match Bournemouth 7. · Nott'm Forest 3.
# Team K V U T +/− xG +/− P
1 Liverpool 21 15 5 1 +30 +31.5 50
2 Arsenal 22 12 8 2 +22 +17.9 44
3 Nott'm Forest 22 13 5 4 +11 +3.5 44
4 Chelsea 22 11 7 4 +17 +14.9 40
5 Man City 22 11 5 6 +15 +9.8 38
6 Newcastle 22 11 5 6 +12 +10.4 38
7 Bournemouth 22 10 7 5 +10 +14.9 37
8 Aston Villa 22 10 6 6 -1 +6.5 36
9 Brighton 22 8 10 4 +5 -1.2 34
10 Fulham 22 8 9 5 +4 +5.1 33
11 Brentford 22 8 4 10 +1 -2.8 28
12 Crystal Palace 22 6 9 7 -3 -0.4 27
13 Man United 22 7 5 10 -5 -1.1 26
14 West Ham 22 7 5 10 -16 -9.1 26
15 Tottenham 22 7 3 12 +10 +0.8 24
16 Everton 21 4 8 9 -10 -7.6 20
17 Wolves 22 4 4 14 -19 -14.7 16
18 Ipswich 22 3 7 12 -23 -25.4 16
19 Leicester 22 3 5 14 -25 -22.7 14
20 Southampton 22 1 3 18 -35 -30.2 6

Calculated from our results data. “xG +/−” is expected goal difference — a positive number with a low league position suggests an undervalued team. Ties on points are sorted by goal difference; some leagues use other rules.

Match report

Bournemouth Nott'm Forest
-5′
🟨 Ramón Sosa
-5′
🟨 Morato
1–0 J. Kluivert
T. Adams
9′
Lewis Cook 🟨
15′
Half-time 1–0
46′
🔁 N. Domínguez
↦ R. Yates
2–0 D. Ouattara
J. Kluivert
55′
Justin Kluivert ℹ️
VAR: Goal cancelled
59′
3–0 D. Ouattara
T. Adams
61′
64′
🟨 Jota Silva
66′
🔁 Morato
↦ Jota Silva
66′
🔁 Álex Moreno
↦ N. Williams
79′
🔁 R. Sosa
↦ O. Aina
79′
🔁 T. Awoniyi
↦ M. Gibbs-White
M. Tavernier 🔁
↦ D. Brooks
80′
4–0 D. Ouattara
87′
D. Jebbison 🔁
↦ J. Kluivert
88′
5–0 A. Semenyo
M. Tavernier
91′
Z. Silcott-Duberry 🔁
↦ D. Ouattara
92′
Illia Zabarnyi 🟨
93′
Full-time 5–0

Line-ups

Bournemouth

4-2-3-1
13 Kepa G
4 L. Cook D
27 I. Zabarnyi D
2 Dean Huijsen D
3 M. Kerkez D
10 R. Christie M
12 T. Adams M
7 D. Brooks M
19 J. Kluivert M
24 A. Semenyo M
11 D. Ouattara F
Bench (9)
16 M. Tavernier
21 D. Jebbison
43 Z. Silcott-Duberry
44 D. Adu-Adjei
48 M. Kinsey
42 M. Travers
51 R. Rees-Dottin
47 B. Winterburn
45 M. Akinmboni

Coach: Andoni Iraola

Nott'm Forest

4-2-3-1
26 M. Sels G
34 O. Aina D
31 N. Milenković D
5 Murillo D
7 N. Williams D
22 R. Yates M
8 E. Anderson M
20 Jota Silva M
10 M. Gibbs-White M
21 A. Elanga M
11 C. Wood F
Bench (9)
16 N. Domínguez
4 Morato
19 Álex Moreno
24 R. Sosa
9 T. Awoniyi
15 H. Toffolo
33 Carlos Miguel
30 W. Boly
18 J. Ward-Prowse

Coach: Nuno Espírito Santo

Odds comparison

Green columns are the outcomes that came in.

1X2
H ✓
2,09
U
3,64
B
3,42
Over/under goals
O1,5 ✓
O2,5 ✓
1,82
U2,5
2,02
O3,5 ✓
Both teams to score
BLS ja
BLS nei ✓

Referee

C Pawson · 173 kamper i vår database

🟨 Yellow cards
3,8 / match
Average
⚽ Free kicks
22,7 / match
Above average

🟥 Red cards: 0,12 per match

The analysis is a statistical estimate based on the teams' results and underlying performances (xG) — not a guarantee. See the model's results.