Nottingham Forest 1–1 Wolves: Result & Stats

Nottingham Forest

FT

1 – 1

HT: 1 – 1

Wolves

C. Wood 10'

J. Bellegarde 12'

8/31/2024

Premier League · Round 3The City Ground

Match Prediction

Statistical Prediction

Based on xG from last 29+ matches

Nottingham Forest50%

×Draw26%

Wolves24%

✓ Correct in 49 of 100 matches — 5 more than always backing the home side

Model

48.6%

Always home

43.8%

The model picks a winner (home or away) for each finished match using only pre-kickoff data, then checks it against the real result: 48.6% correct across 15,072 matches, vs 43.8% for always backing the home side.

Home picks 50.1% correct · Away picks 45.3% correct

Football matches only. Past performance is not indicative of future results.

Nottingham ForestExpected goals in this matchWolves

Expected goals in this match

What is xG?

Every shot is scored 0–1 by how likely it is to be a goal from that spot — a chance in the middle of the box ≈ 0.4, a long shot from a tight angle ≈ 0.03, a penalty ≈ 0.76. Add them up over a match and that is the xG.

The scoreline can lie: you can win 1-0 on a fluke while creating half the chances. xG shows who was really closer to scoring — and over a season it predicts results better than goals alone.

1.54

0.99

Nottingham Forest

1.54

Wolves

0.99

Nottingham Forest creates 56% more chances

Season form · 31 home / 29 away

1.35

creates per match

0.79

1.19

allows per match

1.73

creates per match

Nottingham Forest

1.35

Wolves

0.79

allows per match

Nottingham Forest

1.19

Wolves

1.73

-0.16scores less than expected

finishing

-0.27scores less than expected

finishing

Nottingham Forest-0.16scores less

Wolves-0.27scores less

Total goals

Under54
Over46

Fewer than 3 goals likely

Both teams score

No51
Yes49

Close call

Score probability

Probability of each scoreline, %

Nottingham Forest ↓

Wolves →

0

1

2

3

4

0

0–08%

0–18%

0–24%

0–31%

0–40%

1

1–012%

1–112%

1–26%

1–32%

1–40%

2

2–09%

2–19%

2–25%

2–32%

2–40%

3

3–05%

3–15%

3–22%

3–31%

3–40%

4

4–02%

4–12%

4–21%

4–30%

4–40%

Most likely 1–0 (12%) · grid covers 98% of scorelines

More markets

Total goals

OverUnder0.5

92%8%1.5

72%28%2.5

46%54%3.5

25%75%4.5

11%89%

Double chance

Nottingham Forest or draw

76%

Nottingham Forest or Wolves

74%

Draw or Wolves

50%

Winning margin

Nottingham Forest wins by 2+

26%

Wolves wins by 2+

9%

Team goals

Nottingham Forest 1+ goals

79%

Nottingham Forest 2+ goals

45%

Nottingham Forest 3+ goals

20%

Wolves 1+ goals

63%

Wolves 2+ goals

26%

Wolves 3+ goals

8%

Draw no bet

Nottingham Forest (draw refunded)

67%

Wolves (draw refunded)

33%

Combos

Both score & 3+ goals

37%

Both score & under 3

12%

Model probabilities, not odds. For information only.

How is this calculated?

Every number below comes from this match — nothing is made up.

1

Recent form of each side

Nottingham Forest at home — creates 1.35, concedes 1.19 · 31 matches

Wolves away — creates 0.79, concedes 1.73 · 29 matches

⚑ Home and away form are counted separately — the home-field edge is already baked into these numbers.

2

Expected goals for this match

Nottingham Forest attack 1.35 + Wolves defence 1.73 → ÷2 → 1.54

Wolves attack 0.79 + Nottingham Forest defence 1.19 → ÷2 → 0.99

Each side's attack is blended with the other's defence, then averaged.

3

Chance of every scoreline

From those two numbers a Poisson distribution gives the probability of each exact score — the grid shown above.

4

The answer to "why 50%?"

Nottingham Forest scores more

50%

level

26%

Wolves scores more

24%

Nottingham Forest at 50% is simply the biggest of the three — that is the pick.

What the model can't see

It reads only the stats of recent matches. It knows nothing about:

injuries & suspensions
the matchday lineup
motivation — cup, relegation, a title race
weather & pitch condition
in-game coaching decisions

So 50% does not mean "Nottingham Forest will win" — it means "on the available stats, this is the most likely result."

Statistical model based on expected goals (xG). For informational purposes only.

Player of the match

12

Matheus Cunha

Wolves · F

8.2

Match Events

9'

Jean-Ricner Bellegarde

10'

C. Wood↳ E. Anderson

12'

J. Bellegarde↳ M. Lemina

32'

40'

45'

53'

58'

60'

Hwang Hee-Chan← R. Aït-Nouri

60'

T. Doyle← João Gomes

75'

M. Doherty← Nélson Semedo

75'

Gonçalo Guedes← J. Bellegarde

80'

R. Sosa← C. Hudson-Odoi

86'

André← J. Strand Larsen

90+10'

Morgan Gibbs-White

90'

Elliot Anderson

90+1'

T. Awoniyi← E. Anderson

90+1'

Jota Silva← A. Elanga

Possession

Shots

Pass accuracy

Statistics

NottinghamWolves

Overview

52%Possession48%

16Total Shots11

1.04Expected Goals (xG)0.74

7Corners3

15Fouls18

Shots

16Total Shots11

5On Target3

5Off Target6

6Blocked2

13Inside Box4

3Outside Box7

Passing

52%Possession48%

367Total Passes359

293Accurate Passes279

80%Pass Accuracy78%

Goalkeeping

1Saves4

0.73Goals Prevented0.73

Discipline

15Fouls18

3Yellow Cards4

4Offsides0