Slovak Super League16°0,6 mm12 km/h

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    SkalicaSkalicaLow block & direct
    vs
    PodbrezováPodbrezováLow block & direct
    The model's lean: 2 · Podbrezová (46%)

    SkalicaPodbrezová · Slovak Super League

    1 · Skalica 27%X 27%46% Podbrezová · 2

    Analysis: SkalicaPodbrezová

    Sofia Andersson · · The model's read on the match · How the predictions work

    In the four head-to-head clashes since 2023, Skalica has failed to secure a victory against Podbrezová, managing only a single draw. This small sample size suggests a pattern but weighs less than the current season's form and expected goals. Skalica's struggles are mirrored in their points tally, with only 8 compared to Podbrezová's 10, and their xPoints further highlight this disparity: 6.9 against the visitors' 10.3.

    Podbrezová's strength is evident not just in their head-to-head superiority but in their overall xG metrics. Averaging 2.0 expected goals per match, they outshine Skalica's meager 0.98. Defensively, the hosts also falter, conceding an average of 2.1 xGA per game, while Podbrezová's defense is comparatively sturdier, allowing just 1.7 xGA per match.

    The model probabilities lean towards Podbrezová with a 46% chance of victory, and the visitors are supported by the most likely scorelines of 1-2 and 0-1, each with a 9% probability. Skalica, profiling as a team with a low defensive line and direct play, faces a daunting task against Podbrezová's similarly direct but more efficient tactics. The expected goals tally of 1.23 for Skalica versus 1.70 for the visitors suggests the latter's attacking edge.

    For those seeking value in the betting markets, Podbrezová to win at 2.20 offers a compelling angle, given their superiority in both form and statistical projection. Meanwhile, with a 56% likelihood of over 2.5 goals and a 58% chance of both teams finding the net, the match leans towards a more open contest than the teams' defensive profiles might suggest.

    SkalicaSkalica
    Form WLLLD
    League ranking xG #12xGA #11xT #12xP/match #11Points #8
    Key players
    • Adam MorongCMxG 0.00 · xT 0.08
    • Erik DanielRWxG 0.14 · xT 0.06
    • Philip Obinna OnyedikaFxG 0.16 · xT 0.05
    PodbrezováPodbrezová
    Form WWLDL
    League ranking xG #4xGA #7xT #5xP/match #5Points #6
    Key players
    • Vincent ChylaCDMxG 0.05 · xT 0.08
    • Luka SilagadzeFxG 0.24 · xT 0.07
    • Radek SilerFxG 0.55 · xT 0.15

    Match prediction: SkalicaPodbrezová

    Predicted score matrix

    Podbrezová
    Skalica
    0
    1
    2
    3
    4+
    0
    0–05.7%
    0–18.8%
    0–27.7%
    0–34.4%
    0–4+2.7%
    1
    1–06.3%
    1–111.5%
    1–29.5%
    1–35.4%
    1–4+3.3%
    2
    2–04.0%
    2–16.9%
    2–25.8%
    2–33.3%
    2–4+2.0%
    3
    3–01.7%
    3–12.8%
    3–22.4%
    3–31.3%
    3–4+0.8%
    4+
    4+–00.7%
    4+–11.1%
    4+–20.9%
    4+–30.5%
    4+–4+0.3%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-112%
    2. 2.1-29%
    3. 3.0-19%
    4. 4.0-28%
    5. 5.2-17%
    Expected goals
    1,231,70
    Both teams to score
    58%

    Over/under goals

    Expected goals: 2,9
    Under 2,544%
    Over 2,556%

    Ready-made bet suggestions

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    01 · 2 legs

    Safe

    • Podbrezová to win46%
    • Over 1.5 goals79%

    Combined probability

    39%

    Fair odds

    2.55

    Two legs pulling the same way — the probability is computed exactly from the score matrix, not multiplied.

    02 · 3 legs

    Balanced

    • Podbrezová to win46%
    • Over 2.5 goals56%
    • Ondřej Deml to score16%

    Combined probability

    Fair odds

    The whole slip is priced jointly via 20,000 simulated matches — the scorer interacts with result and total goals, never naive multiplication.

    03 · 4 legs

    Bold

    • Both teams to score58%
    • Over 2.5 goals56%
    • Ondřej Deml to score16%
    • Vincent Chyla to be booked22%

    Combined probability

    Fair odds

    The goal-fest: both teams score with at least three goals, plus the match's most likely scorer and card candidate — all priced jointly via 20,000 simulated matches.

    Odds & value

    No odds available yet.

    Statistics

    Head-to-head

    4 matches
    Skalica 0Draw 1Podbrezová 3
    Goals: 413 (⌀ 4,2)

    Head-to-head based on Slovak Super League data since 2023.

    xG & xGA per match — 3-game rolling average

    Solid line = created (xG), dashed = conceded (xGA).

    Skalica
    Podbrezová
    When goals are scored and conceded 2026
    Skalica (915)
    Podbrezová (1115)
    Pass networks

    Last 5 matches. Circle size = pass volume, line width = combinations between players. Attacking left to right.

    Skalica
    Patrick Karhan: 124 passningar, xT 0.24KarhanSamuel Sula: 113 passningar, xT 0.3SulaLevan Nonikashvili: 98 passningar, xT 0.45NonikashviliErik Daniel: 97 passningar, xT 0.56DanielAdam Ravas: 80 passningar, xT 0.06RavasDamian Baris: 75 passningar, xT 0.01BarisPetr Pudhorocky: 68 passningar, xT 0.14PudhorockyLukas Simko: 68 passningar, xT 0.13SimkoRichard Ludha: 57 passningar, xT 0.13LudhaAdam Morong: 53 passningar, xT 0.05MorongMartin Cernek: 47 passningar, xT 0.1Cernek
    Podbrezová
    Jakub Luka: 270 passningar, xT 0.74LukaRene Rantusa Lampreht: 218 passningar, xT 0.31LamprehtPeter Kováčik: 135 passningar, xT 1.19KováčikVincent Chyla: 125 passningar, xT 0.72ChylaRene Paraj: 104 passningar, xT 0.6ParajOndrej Deml: 94 passningar, xT 0.27DemlMartin Chrien: 90 passningar, xT 0.05ChrienLukáš Domaniský: 87 passningar, xT 0.11DomaniskýJan Krivak: 79 passningar, xT 0.06KrivakFilip Mielke: 78 passningar, xT 0.08MielkeRadek Kejval: 65 passningar, xT 0.13Kejval
    xT networks

    The same network weighted by offensive threat (xT): circle size = threat created by the player, line width = threat of the combinations. Last 5 matches, attacking left to right.

    Skalica
    Patrick Karhan: 124 passningar, xT 0.24KarhanSamuel Sula: 113 passningar, xT 0.3SulaLevan Nonikashvili: 98 passningar, xT 0.45NonikashviliErik Daniel: 97 passningar, xT 0.56DanielAdam Ravas: 80 passningar, xT 0.06RavasDamian Baris: 75 passningar, xT 0.01BarisPetr Pudhorocky: 68 passningar, xT 0.14PudhorockyLukas Simko: 68 passningar, xT 0.13SimkoRichard Ludha: 57 passningar, xT 0.13LudhaAdam Morong: 53 passningar, xT 0.05MorongMartin Cernek: 47 passningar, xT 0.1Cernek
    Podbrezová
    Jakub Luka: 270 passningar, xT 0.74LukaRene Rantusa Lampreht: 218 passningar, xT 0.31LamprehtPeter Kováčik: 135 passningar, xT 1.19KováčikVincent Chyla: 125 passningar, xT 0.72ChylaRene Paraj: 104 passningar, xT 0.6ParajOndrej Deml: 94 passningar, xT 0.27DemlMartin Chrien: 90 passningar, xT 0.05ChrienLukáš Domaniský: 87 passningar, xT 0.11DomaniskýJan Krivak: 79 passningar, xT 0.06KrivakFilip Mielke: 78 passningar, xT 0.08MielkeRadek Kejval: 65 passningar, xT 0.13Kejval

    The teams in numbers

    PerformanceSkalicaPodbrezová
    Points810
    xPoints6.910.3
    xG per match0.982
    xGA per match2.11.7
    xG within 8s of winning the ball0.290.33
    xGA within 8s of losing the ball0.250.48
    Playing styleSkalicaPodbrezová
    Build-up efficiency0.310.33
    Field tilt0.380.55
    xT per match0.661.2
    xTA per match1.41.2
    Won balls, offensive half2124
    Pressing intensity0.220.22
    Pressing efficiency0.310.26
    Pressing efficiency, offensive half0.250.22
    Entries into the box per match915
    Entries into the box against1613
    Pass completion %0.630.73
    Pass completion % under pressure0.620.71
    Passes per match221312
    Passes against per match364355
    Switches of play per match14.920.3
    Long balls per match2728
    Set piecesSkalicaPodbrezová
    xG from free kicks0.010.08
    Corners per match5.16.3
    Corners against per match5.75.2
    xG per corner0.020.03
    xGA per corner against0.050.03
    First touch, offensive corners %0.470.64
    First touch, defensive corners %0.470.58
    OtherSkalicaPodbrezová
    Throw-in control0.70.73
    The goalkeepersErik Riska (Skalica)Martin Trnovsky (Podbrezová)
    Saves1811
    Save %78%58%
    xG prevented51%40%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Skalica vs Podbrezová according to our model?

    The model gives Podbrezová a 46% win probability. Full 1X2 picture: Skalica 27%, draw 27%, Podbrezová 46%.

    What is the most likely scoreline?

    The model's most likely final score is 1-1 at 12% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 56% and under at 44%.

    Will both teams score?

    The probability of both teams scoring is 58% according to the model.

    Why are some legs locked in the bet builder?

    The same rules as the bookmakers’ builders: legs that contradict or already follow from your slip cannot be combined — for example correct score 2–1 with under 2.5 goals. The difference is that we don’t look the rules up in a table; we compute them straight from the score matrix.

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    Predictions come from PlaymakerAI's match model and reflect the model's assessment — not betting advice. Gamble responsibly.