Queen's University 6–1 Moyola Park: Result & Stats

Queen's University

FT

6 – 1

Moyola Park

12/21/2024

League #561 · Round 10Queen's University Malone Playing Fields

Match Prediction

Statistical Prediction

Based on goals from last 19+ matches

Queen's University57%

×Draw20%

Moyola Park23%

✓ 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.

Queen's UniversityExpected goals in this matchMoyola Park

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.

2.30

1.40

Queen's University

2.30

Moyola Park

1.40

Queen's University creates 64% more chances

Season form · 19 home / 30 away

2.58

creates per match

1.53

1.26

allows per match

2.03

creates per match

Queen's University

2.58

Moyola Park

1.53

allows per match

Queen's University

1.26

Moyola Park

2.03

+0.00on par

finishing

+0.00on par

finishing

Queen's University+0.00on par

Moyola Park+0.00on par

Total goals

Over71
Under29

3+ goals likely

Both teams score

Yes68
No32

Both teams likely to score

Score probability

Probability of each scoreline, %

Queen's University ↓

Moyola Park →

0

1

2

3

4

0

0–02%

0–13%

0–22%

0–31%

0–40%

1

1–06%

1–18%

1–26%

1–33%

1–41%

2

2–07%

2–19%

2–26%

2–33%

2–41%

3

3–05%

3–17%

3–25%

3–32%

3–41%

4

4–03%

4–14%

4–23%

4–31%

4–40%

Most likely 2–1 (9%) · grid covers 91% of scorelines

More markets

Total goals

OverUnder0.5

98%2%1.5

88%12%2.5

71%29%3.5

50%50%4.5

31%69%

Double chance

Queen's University or draw

77%

Queen's University or Moyola Park

80%

Draw or Moyola Park

43%

Winning margin

Queen's University wins by 2+

36%

Moyola Park wins by 2+

10%

Team goals

Queen's University 1+ goals

90%

Queen's University 2+ goals

67%

Queen's University 3+ goals

40%

Moyola Park 1+ goals

75%

Moyola Park 2+ goals

41%

Moyola Park 3+ goals

17%

Draw no bet

Queen's University (draw refunded)

72%

Moyola Park (draw refunded)

28%

Combos

Both score & 3+ goals

60%

Both score & under 3

8%

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

Queen's University at home — creates 2.58, concedes 1.26 · 19 matches

Moyola Park away — creates 1.53, concedes 2.03 · 30 matches

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

2

Expected goals for this match

Queen's University attack 2.58 + Moyola Park defence 2.03 → ÷2 → 2.30

Moyola Park attack 1.53 + Queen's University defence 1.26 → ÷2 → 1.40

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 57%?"

Queen's University scores more

57%

level

20%

Moyola Park scores more

23%

Queen's University at 57% 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 57% does not mean "Queen's University 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.

Probable lineups not yet announced

Starting lineups are usually confirmed ~1 hour before kickoff