· UEFA U21 Championship Qualification
Germany U21
ATT
7/10
DEF
6/10
vs
Georgia U21
5/10
ATT
6/10
DEF
Scheduled· Tue 6 Oct · 16:00
Best Pick
Over 2.5
64%
Correct Score
Top
2-1
9.7%
10.32
Top
1-1
9.4%
10.58
2-0
7.7%
12.96
1-0
7.5%
13.29
3-1
6.6%
15.10
2-2
6.1%
16.44
1-2
5.9%
16.85
3-0
5.3%
18.96
156%
1.80TOP
X21%
4.71
223%
4.34
1X77%
X244%
1279%
Probable XI4-4-2
Seimen
Zehnter
Arrey-Mbi
Kleine-Bekel
Baum
Kemlein
Kade
Ouédraogo
Gruda
Knauff
Ibrahimovic
Impact Player Hot Head
Lineups not yet announced — full squad analysis below
Germany U2136 players
75.1/ 99Elite
Top Rated
1Tom BischofMID97
2Nicolò TresoldiFWD96
3Noel AsekoMID95
Georgia U2128 players
42.7/ 99Average
Top Rated
1Akaki GiunashviliDEF77
2J. KarseDEF72
3Tsotne BerelidzeMID69
Germany U2170
PlayerOverall RatingImpactAggressionDiscipline
Tom Bischof97999991
Nicolò Tresoldi96998078
Noel Aseko95999978
Lukas Ullrich94929991
Aljoscha Kemlein 92999963
Nelson Weiper92997261
Joshua Quarshie91996569
Mert Kömür91998061
Muhammed Damar91999961
Ilyas Ansah90998650
Dzenan Pejcinovic89997056
Finn Jeltsch 85819971
Mio Backhaus83912850
Georgia U2178
PlayerOverall RatingImpactAggressionDiscipline
Akaki Giunashvili77995250
J. Karse72993450
Tsotne Berelidze69727950
Giorgi Gvasalia60597447
Papuna Beruashvili54552350
D. Bukia47553647
Khalid Doltmurziev47474550
Giorgi Kavlashvili46454550
Aleksandre Peikrishvili46454550
Giorgi Robakidze46454550
George Chubinidze45454550
Mikheil Makatsaria41393950
Andria Bartishvili41393950
Player Rankings
Snipers
Top goal threats
1
Dzenan PejcinovicGermany U21
99
2
Ilyas AnsahGermany U21
99
3
Nelson WeiperGermany U21
99
4
Nicolò TresoldiGermany U21
99
5
Said El MalaGermany U21
76
Wall
Top defenders
1
Joshua QuarshieGermany U21
99
2
Tom RotheGermany U21
99
3
Akaki GiunashviliGeorgia U21
99
4
J. KarseGeorgia U21
99
5
Lukas UllrichGermany U21
92
Control
Top playmakers
1
Aljoscha Kemlein Germany U21
99
2
Mert KömürGermany U21
99
3
Muhammed DamarGermany U21
99
4
Noel AsekoGermany U21
99
5
Tom BischofGermany U21
99
Bad Boys
Most likely to get booked
1
Nikoloz DadianiGeorgia U21
37
2
Diego DeisadzeGeorgia U21
44
3
D. BukiaGeorgia U21
47
4
Giorgi GvasaliaGeorgia U21
47
5
Dennis SeimenGermany U21
50
Power Rankings
Strongest overall
1
Tom BischofGermany U21
97
2
Nicolò TresoldiGermany U21
96
3
Noel AsekoGermany U21
95
4
Lukas UllrichGermany U21
94
5
Aljoscha Kemlein Germany U21
92

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Germany U21 vs Georgia U21 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 Germany U21 vs Georgia U21 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 Germany U21 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 Germany U21 vs Georgia U21 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 Germany U21 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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