· AFC Champions League
Newcastle Jets
ATT
5/10
DEF
5/10
vs
Gamba Osaka
5/10
ATT
6/10
DEF
Naplánováno· Tue 13 Oct · 07:45
Nejlepší tip
OBÁ SKÓRUJÍ
54%
Přesný výsledek
Výborná
1-1
11.9%
8.38
Výborná
1-0
10.5%
9.50
2-1
9.3%
10.70
2-0
8.2%
12.13
0-1
7.6%
13.12
1-2
6.8%
14.77
0-0
6.7%
14.88
2-2
5.3%
18.87
147%
2.11TOP
X25%
3.98
228%
3.63
1X72%
X253%
1275%
Probable XI4-4-2
Nassiep
Grant
Wilmering
Shaughnessy
Bertolissio
Badolato
Nunes
Burgess
Dobson
Debono
Goodwin
Impact Player Hot Head
Sestavy ještě nebyly oznámeny — níže kompletní analýza kádru
Newcastle Jets10 hráči
49.3/ 99Průměrný
Nejlepší
1Zane SchreiberMID59
2Max BurgessMID53
3Daniel WilmeringDEF52
Gamba Osaka18 hráči
46.8/ 99Průměrný
Nejlepší
1Koshiro SumiFWD60
2Yusei ToshidaFWD57
3Jun IchimoriGK51
Newcastle Jets25
PlayerCelkové HodnoceníImpaktAgreseDisciplína
Zane Schreiber59584861
Max Burgess53524956
Daniel Wilmering52485356
Joel Bertolissio52495156
James Delianov48484550
J. Shaughnessy48504550
Will Dobson46464550
Nikos Vergos46464550
Xavier Bertoncello45454550
P. Wood44585310
Alex Nassiep————
Jordan Baylis————
Alexander Grant————
Gamba Osaka44
PlayerCelkové HodnoceníImpaktAgreseDisciplína
Koshiro Sumi60635250
Yusei Toshida57525467
Jun Ichimori51524550
Shuto Abe51514456
Rin Mito49464656
Shinnosuke Nakatani47464156
Rui Araki46454550
Shu Kurata46454550
Tokuma Suzuki46454550
Issam Jebali46414861
Ginjiro Ikegaya45454550
Shinya Nakano45454550
Shogo Sasaki45454550
Žebříčky hráčů
Střelci
Největší gólová hrozba
1
Koshiro SumiGamba Osaka
63
2
P. WoodNewcastle Jets
58
3
Yusei ToshidaGamba Osaka
52
4
Nikos VergosNewcastle Jets
46
5
Xavier BertoncelloNewcastle Jets
45
Zeď
Nejlepší obránci
1
Shota FukuokaGamba Osaka
53
2
J. ShaughnessyNewcastle Jets
50
3
Joel BertolissioNewcastle Jets
49
4
Daniel WilmeringNewcastle Jets
48
5
Shinnosuke NakataniGamba Osaka
46
Kontrola
Nejlepší tvůrci hry
1
Zane SchreiberNewcastle Jets
58
2
Max BurgessNewcastle Jets
52
3
Shuto AbeGamba Osaka
51
4
Will DobsonNewcastle Jets
46
5
Rin MitoGamba Osaka
46
Zlobivci
Nejpravděpodobnější žlutá karta
1
P. WoodNewcastle Jets
10
2
Ryo HatsuseGamba Osaka
25
3
Shota FukuokaGamba Osaka
31
4
James DelianovNewcastle Jets
50
5
J. ShaughnessyNewcastle Jets
50
Žebříček síly
Nejsilnější celkově
1
Koshiro SumiGamba Osaka
60
2
Zane SchreiberNewcastle Jets
59
3
Yusei ToshidaGamba Osaka
57
4
Max BurgessNewcastle Jets
53
5
Daniel WilmeringNewcastle Jets
52

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Newcastle Jets vs Gamba Osaka 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 Newcastle Jets vs Gamba Osaka 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 Newcastle Jets 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 Newcastle Jets vs Gamba Osaka 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 Newcastle Jets 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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