· UEFA Youth League
Benfica U19
ATT
7/10
DEF
5/10
6:0
Pafos U19
5/10
ATT
5/10
DEF
Konec
Nejlepší tip
Nad 2.5
73%
Přesný výsledek91′
Výborná
2-1
9%
19.00
1-1
7.7%
29.00
3-1
7.1%
15.00
2-2
6.5%
34.00
2-0
6.3%
13.00
1-2
5.5%
51.00
1-0
5.4%
23.00
3-2
5.1%
34.00
158%
1.73TOP
X19%
5.13
223%
4.40
1X77%
X242%
1281%
xG — Očekávané góly
Benfica U19
Benfica U19 oček.
Pafos U19
Pafos U19 oček.
goal
za 15 min
0–15′
15–30′
30–45′
45–60′
60–75′
75–90′
Benfica U19
Pafos U19
Probable XI4-4-2
1
Ferreira
2
Coelho
4
Queiroz
5
Neto
14
Neto
16
Ferreira
8
Figueiredo
6
Quintas
10
Stevan
9
Silva
15
Semedo
Impact Player Hot Head
Sestavy ještě nebyly oznámeny — níže kompletní analýza kádru
Benfica U199 hráči
74.7/ 99Elitní
Nejlepší
1Miguel FigueiredoMID96
2Francisco SilvaFWD86
3StevanMID82
Pafos U193 hráči
40.7/ 99Průměrný
Nejlepší
1Paris Gregory PapastylianouFWD45
2Georgios MichaelMID41
3Ioannis IgnatiadisDEF36
Benfica U1915
PlayerCelkové HodnoceníImpaktAgreseDisciplína
8
Miguel Figueiredo96999983
9
Francisco Silva86999737
10
Stevan82997250
6
Rafael Quintas77995150
14
Ricardo Neto75994550
5
José Neto74628367
3
Rui Pedro Ferreira da Silva74576989
1
Diogo José de Nazaré e Jesus Ferreira57591750
12
Léo Lopes51524550
2
Diogo Alexandre Palma Coelho————
4
Gabriel Queiroz————
16
Isaac Gonçalves Ferreira————
15
Nilson Semedo————
Pafos U199
PlayerCelkové HodnoceníImpaktAgreseDisciplína
11
Paris Gregory Papastylianou45454550
14
Georgios Michael41393950
22
Ioannis Ignatiadis36343450
1
Andreas Andreou————
18
Constantinos Christofi————
2
Lucca Vetter Paulino————
7
Melinos Kais————
94
Nicolas Aristodemou————
77
Victoras Neokleous————
Žebříčky hráčů
Střelci
Největší gólová hrozba
1
Francisco SilvaBenfica U19
99
2
Paris Gregory PapastylianouPafos U19
45
Zeď
Nejlepší obránci
1
Ricardo NetoBenfica U19
99
2
José NetoBenfica U19
62
3
Rui Pedro Ferreira da SilvaBenfica U19
57
4
Ioannis IgnatiadisPafos U19
34
Kontrola
Nejlepší tvůrci hry
1
Miguel FigueiredoBenfica U19
99
2
Rafael QuintasBenfica U19
99
3
StevanBenfica U19
99
4
Georgios MichaelPafos U19
39
Zlobivci
Nejpravděpodobnější žlutá karta
1
Francisco SilvaBenfica U19
37
2
Diogo José de Nazaré e Jesus FerreiraBenfica U19
50
3
Léo LopesBenfica U19
50
4
Ricardo NetoBenfica U19
50
5
Rafael QuintasBenfica U19
50
Žebříček síly
Nejsilnější celkově
1
Miguel FigueiredoBenfica U19
96
2
Francisco SilvaBenfica U19
86
3
StevanBenfica U19
82
4
Rafael QuintasBenfica U19
77
5
Ricardo NetoBenfica U19
75

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Benfica U19 vs Pafos U19 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 Benfica U19 vs Pafos U19 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 Benfica U19 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 Benfica U19 vs Pafos U19 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 Benfica U19 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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