· Copa Del Rey
Covadonga
ATT
5/10
DEF
5/10
0:1
Real Valladolid
5/10
ATT
5/10
DEF
Konec
Nejlepší tip
OBÁ SKÓRUJÍ
65%
Přesný výsledek92′
Výborná
1-1
9.9%
11.00
Výborná
2-1
9.1%
41.00
1-2
7.2%
10.00
1-0
6.8%
34.00
2-2
6.7%
23.00
2-0
6.3%
67.00
3-1
5.6%
101.00
0-1
5.3%
8.50
147%
2.13TOP
X23%
4.43
230%
3.29
1X70%
X253%
1277%
xG — Očekávané góly
Covadonga
Covadonga oček.
Real Valladolid
Real Valladolid oček.
goal
za 15 min
0–15′
15–30′
30–45′
45–60′
60–75′
75–90′
Covadonga
Real Valladolid
Probable XI4-4-2
Buru
Trabanco
Morilla
Hervás
Arias
Cid
Fernández
Shawahna
Pelaez
Impact Player Hot Head
Sestavy ještě nebyly oznámeny — níže kompletní analýza kádru
Covadonga10 hráči
Žádná data kádru
BuruGK
Raul RodriguezGK
Adrián TrabancoDEF
Emilio MorillaDEF
Aitor Elena HervásMID
Álex AriasMID
Carlos CidMID
Iván FernándezMID
Rashid ShawahnaMID
Vicente Alvarez PelaezMID
Real Valladolid13 hráči
48.3/ 99Průměrný
Nejlepší
1Miguel RubioDEF74
2Dani MartínGK52
3Thiago OjedaMID51
Covadonga10
PlayerCelkové HodnoceníImpaktAgreseDisciplína
Buru————
Raul Rodriguez————
Adrián Trabanco————
Emilio Morilla————
Aitor Elena Hervás————
Álex Arias————
Carlos Cid————
Iván Fernández————
Rashid Shawahna————
Vicente Alvarez Pelaez————
Real Valladolid40
PlayerCelkové HodnoceníImpaktAgreseDisciplína
Miguel Rubio74636178
Dani Martín52533950
Thiago Ojeda51704231
Álvaro Aceves46454550
Julien Ponceau46454550
Mathis Lachuer46454550
Stanko Juric46454550
Luis Chacón46455250
David Torres45454550
Trilli45454550
Adrián Arnu45454550
Marcos André45454550
Jorge Delgado41393950
Žebříčky hráčů
Střelci
Největší gólová hrozba
1
Adrián ArnuReal Valladolid
45
2
Luis ChacónReal Valladolid
45
3
Marcos AndréReal Valladolid
45
4
Jorge DelgadoReal Valladolid
39
Zeď
Nejlepší obránci
1
Miguel RubioReal Valladolid
63
2
David TorresReal Valladolid
45
3
TrilliReal Valladolid
45
Kontrola
Nejlepší tvůrci hry
1
Thiago OjedaReal Valladolid
70
2
Julien PonceauReal Valladolid
45
3
Mathis LachuerReal Valladolid
45
4
Stanko JuricReal Valladolid
45
Zlobivci
Nejpravděpodobnější žlutá karta
1
Thiago OjedaReal Valladolid
31
2
Álvaro AcevesReal Valladolid
50
3
Dani MartínReal Valladolid
50
4
David TorresReal Valladolid
50
5
TrilliReal Valladolid
50
Žebříček síly
Nejsilnější celkově
1
Miguel RubioReal Valladolid
74
2
Dani MartínReal Valladolid
52
3
Thiago OjedaReal Valladolid
51
4
Álvaro AcevesReal Valladolid
46
5
Julien PonceauReal Valladolid
46

Frequently Asked Questions

Our Poisson model calculates the probability of every possible scoreline for Covadonga vs Real Valladolid 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 Covadonga vs Real Valladolid 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 Covadonga 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 Covadonga vs Real Valladolid 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 Covadonga 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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