Warri Wolves 0–0 Akwa United: Result & Stats | NPFL

Warri Wolves

FT

0 – 0

HT: 0 – 0

Akwa United

3/8/2021

NPFL · Round 14Warri Township Stadium

Match Prediction

Statistical Prediction

Based on goals from last 52+ matches

Warri Wolves52%

×Draw30%

Akwa United18%

✓ Correct in 50 of 100 matches — 6 more than always backing the home side

Model

49.7%

Always home

44.3%

The model picks a winner (home or away) for each finished match using only pre-kickoff data, then checks it against the real result: 49.7% correct across 106,786 matches, vs 44.3% for always backing the home side.

Home picks 50.7% correct · Away picks 47.3% correct

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

Warri WolvesExpected goals in this matchAkwa United

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.

1.23

0.60

Warri Wolves

1.23

Akwa United

0.60

Warri Wolves creates 105% more chances

Season form · 52 home / 112 away

1.17

creates per match

0.66

0.54

allows per match

1.29

creates per match

Warri Wolves

1.17

Akwa United

0.66

allows per match

Warri Wolves

0.54

Akwa United

1.29

+0.00on par

finishing

+0.00on par

finishing

Warri Wolves+0.00on par

Akwa United+0.00on par

Total goals

Under72
Over28

Fewer than 3 goals likely

Both teams score

No68
Yes32

One side may not score

Score probability

Probability of each scoreline, %

Warri Wolves ↓

Akwa United →

0

1

2

3

4

0

0–016%

0–110%

0–23%

0–31%

0–40%

1

1–020%

1–112%

1–24%

1–31%

1–40%

2

2–012%

2–17%

2–22%

2–30%

2–40%

3

3–05%

3–13%

3–21%

3–30%

3–40%

4

4–02%

4–11%

4–20%

4–30%

4–40%

Most likely 1–0 (20%) · grid covers 99% of scorelines

More markets

Total goals

OverUnder0.5

84%16%1.5

55%45%2.5

28%72%3.5

11%89%4.5

4%96%

Double chance

Warri Wolves or draw

82%

Warri Wolves or Akwa United

70%

Draw or Akwa United

48%

Winning margin

Warri Wolves wins by 2+

24%

Akwa United wins by 2+

4%

Team goals

Warri Wolves 1+ goals

71%

Warri Wolves 2+ goals

35%

Warri Wolves 3+ goals

13%

Akwa United 1+ goals

45%

Akwa United 2+ goals

12%

Akwa United 3+ goals

2%

Draw no bet

Warri Wolves (draw refunded)

74%

Akwa United (draw refunded)

26%

Combos

Both score & 3+ goals

20%

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

Warri Wolves at home — creates 1.17, concedes 0.54 · 52 matches

Akwa United away — creates 0.66, concedes 1.29 · 112 matches

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

2

Expected goals for this match

Warri Wolves attack 1.17 + Akwa United defence 1.29 → ÷2 → 1.23

Akwa United attack 0.66 + Warri Wolves defence 0.54 → ÷2 → 0.60

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 52%?"

Warri Wolves scores more

52%

level

30%

Akwa United scores more

18%

Warri Wolves at 52% 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 52% does not mean "Warri Wolves 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.

Match Events

46'

A. Daniel← A. Daniel

60'

N. Godswill

60'

O. Olalere

65'

D. Ojo← D. Ojo

65'

N. Ikechukwu← N. Ikechukwu

69'

76'

80'

F. Ubong← F. Ubong

90'

Probable lineups not yet announced

Starting lineups are usually confirmed ~1 hour before kickoff