Shao Jiang 6–0 Universidade de Macau

Shao Jiang

FT

6 – 0

HT: 3 – 0

Universidade de Macau

6/20/2026

Primeira Divisão · Round 13

Match Prediction

Statistical Prediction

Based on goals from last 19+ matches

Shao Jiang79%

×Draw12%

Universidade de Macau9%

✓ Correct in 50 of 100 matches — 5 more than always backing the home side

Model

50.3%

Always home

44.5%

The model picks a winner (home or away) for each finished match using only pre-kickoff data, then checks it against the real result: 50.3% correct across 582,450 matches, vs 44.5% for always backing the home side.

Home picks 50.5% correct · Away picks 49.5% correct

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

Shao JiangExpected goals in this matchUniversidade de Macau

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.

3.50

1.19

Shao Jiang

3.50

Universidade de Macau

1.19

Shao Jiang creates 194% more chances

Season form · 19 home / 26 away

4.37

creates per match

1.54

0.84

allows per match

2.62

creates per match

Shao Jiang

4.37

Universidade de Macau

1.54

allows per match

Shao Jiang

0.84

Universidade de Macau

2.62

+0.00on par

finishing

+0.00on par

finishing

Shao Jiang+0.00on par

Universidade de Macau+0.00on par

Total goals

Over84
Under16

3+ goals likely

Both teams score

Yes67
No33

Both teams likely to score

Score probability

Probability of each scoreline, %

Shao Jiang ↓

Universidade de Macau →

0

1

2

3

4

0

0–01%

0–11%

0–21%

0–30%

0–40%

1

1–03%

1–14%

1–22%

1–31%

1–40%

2

2–06%

2–17%

2–24%

2–32%

2–41%

3

3–07%

3–18%

3–25%

3–32%

3–41%

4

4–06%

4–17%

4–24%

4–32%

4–41%

Most likely 3–1 (8%) · grid covers 77% of scorelines

More markets

Total goals

OverUnder0.5

99%1%1.5

94%6%2.5

84%16%3.5

67%33%4.5

47%53%

Double chance

Shao Jiang or draw

91%

Shao Jiang or Universidade de Macau

88%

Draw or Universidade de Macau

21%

Winning margin

Shao Jiang wins by 2+

61%

Universidade de Macau wins by 2+

3%

Team goals

Shao Jiang 1+ goals

97%

Shao Jiang 2+ goals

85%

Shao Jiang 3+ goals

66%

Universidade de Macau 1+ goals

70%

Universidade de Macau 2+ goals

33%

Universidade de Macau 3+ goals

12%

Draw no bet

Shao Jiang (draw refunded)

89%

Universidade de Macau (draw refunded)

11%

Combos

Both score & 3+ goals

63%

Both score & under 3

4%

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

Shao Jiang at home — creates 4.37, concedes 0.84 · 19 matches

Universidade de Macau away — creates 1.54, concedes 2.62 · 26 matches

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

2

Expected goals for this match

Shao Jiang attack 4.37 + Universidade de Macau defence 2.62 → ÷2 → 3.50

Universidade de Macau attack 1.54 + Shao Jiang defence 0.84 → ÷2 → 1.19

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 79%?"

Shao Jiang scores more

79%

level

12%

Universidade de Macau scores more

9%

Shao Jiang at 79% 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 79% does not mean "Shao Jiang 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