· Australian Championship
South Melbourne
ATT
5/10
DEF
7/10
1:1
Sydney United
5/10
ATT
5/10
DEF
Fine
Migliore scelta
GOL DI ENTRAMBE
55%
Risultato esatto100′
Eccellente
1-1
10.9%
8.00
Eccellente
1-0
10.1%
8.00
2-1
9.8%
8.50
2-0
9.2%
8.50
0-1
6%
13.00
3-1
5.9%
13.00
1-2
5.8%
15.00
0-0
5.6%
13.00
155%
1.83TOP
X23%
4.34
222%
4.48
1X78%
X245%
1277%
ogni 15 min
0–15′
15–30′
30–45′
45–60′
60–75′
75–90′
South Melbourne
Sydney United
Confirmed XI3-4-3
1
López
23
Eliopoulos
4
Jankovic
3
Lampard
27
Painter-Andrews
8
Retre
21
Pasquali
16
Cocks
15
Swibel
9
Barbarouses
11
Uchida
Impact Player Hot Head
South Melbourne31 giocatori
Nessuna metrica rosa
Jake CharlstonGK
Javier LópezGK
Hassan RamazaniDEF
J. LampardDEF
J. MarshallDEF
J. Painter-AndrewsDEF
Jacob EliopoulosDEF
M. JankovicDEF
R. NkomoDEF
Sasha MurphyDEF
Thomas GiannakopoulosDEF
Alexander MenelaouMID
C. LeechMID
Sydney United7 giocatori
50.3/ 99Medio
Migliori
1Tomoki WadaMID57
2B. RuleDEF50
3Liam McGingDEF50
Classifiche giocatori
Muro
Migliori difensori
1
Liam McGingSydney United
51
2
M. VlastelicaSydney United
49
3
B. RuleSydney United
48
4
Koya NakanoSydney United
46
Controllo
Migliori registi
1
Tomoki WadaSydney United
58
2
Carlos De OliveriaSydney United
49
3
Tomislav OzanicSydney United
46
Cattivi ragazzi
Più propensi ai cartellini
1
B. RuleSydney United
50
2
Koya NakanoSydney United
50
3
Liam McGingSydney United
50
4
M. VlastelicaSydney United
50
5
Carlos De OliveriaSydney United
50
Classifica potenza
Più forti in assoluto
1
Tomoki WadaSydney United
57
2
B. RuleSydney United
50
3
Liam McGingSydney United
50
4
Tomislav OzanicSydney United
50
5
Koya NakanoSydney United
49

Domande frequenti

Our Poisson model calculates the probability of every possible scoreline for South Melbourne vs Sydney United based on each team's expected goals (xG). The top-3 most likely scorelines are shown above with their probability percentages. Even the highest-probability score rarely exceeds 12-15% chance, as football is a low-scoring sport.

The Bet Builder combines multiple selections from the South Melbourne vs Sydney United match into one bet. Our AI identifies outcomes that complement each other — for example, a home win paired with over 2.5 goals and both teams to score. All selections must win for the combined bet to pay out, which means higher combined odds but also higher risk.

xG (expected goals) measures the quality of scoring chances. If South Melbourne has an xG of 1.8, it means they are expected to score around 1-2 goals based on chance quality. The model uses pre-match xG to build a probability table for all possible scorelines. A team can overperform xG (score more than expected) or underperform xG (score fewer).

Yes, all predictions on ProSoccer are completely free. You can view predicted scorelines, over/under probabilities, and bet builder suggestions for South Melbourne vs Sydney United without paying or registering. Odds values are revealed after a tap to keep the page compliant with search engine guidelines.

A value bet occurs when the probability of an outcome is higher than what the bookmaker odds suggest. For example, if our model gives South Melbourne a 55% chance of winning but the odds imply only 40%, that is a value bet. Our AI highlights selections where the model probability exceeds the implied probability from the odds.

AI predictions use statistical modeling (Poisson distribution) based on historical data and pre-match metrics. They are more reliable over large samples than for any single match. No prediction is guaranteed — football has inherent unpredictability. Our model typically identifies the correct top-3 scorelines in 25-30% of matches, which is significantly better than random chance.

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