Slovak Super League22°0,1 mm22 km/h

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    KomárnoKomárnoCounter-attacks & crosses
    00
    SkalicaSkalicaLow block & direct
    The model's lean: 1 · Komárno (46%)Best value by the model: 2 · Skalica @ 4.50 (+23 %)

    KomárnoSkalica · Slovak Super League

    1 · Komárno 46%X 26%27% Skalica · 2

    Analysis: KomárnoSkalica

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

    TEXT: Komárno holds a statistical edge in expected goals, creating a dynamic tension against Skalica’s superior points tally so far this season. The model leans towards a Komárno win with a 46% probability, reflecting their more robust underlying numbers, particularly in defense with a lower xGA compared to the visitors’ 2.1. This suggests Komárno could capitalize on Skalica's porous defense, especially considering their counter-attacking style which might exploit Skalica's recent defensive woes.

    Skalica, mired in a three-game losing streak, faces a daunting task on the road. Despite their higher points total at this point, their recent form and defensive frailty could be their undoing. The matchup’s small head-to-head sample, since 2023, shows 8 matches with Komárno taking 2 wins, 3 draws, and 3 losses, but it is Komárno’s superior expected points and defensive statistics that weigh more heavily here.

    The expected goals tally suggests a relatively balanced contest, with Komárno at 1.55 and Skalica at 1.24. This fits with the model’s most likely scorelines of 1-1, 1-0, or 2-1. However, the slight lean towards over 2.5 goals at 53% could be influenced by Komárno's ability to exploit Skalica's defensive lapses, making a 2-1 home win a plausible outcome.

    Both teams are likely to find the net, supported by a 56% probability, so the “both teams to score” market holds interest. Yet, the key angle here is the value on a Komárno win. With bookmakers potentially undervaluing this likelihood based on the lean, there could be value in Komárno to win if found at odds greater than their implied probability of 46%. This is where the sharpest punters might find the edge.

    KomárnoKomárno
    Form LDLLD
    League ranking xG #9xGA #4xT #5xP/match #10Points #11
    Key players
    • Ján BernátLWxG 0.11 · xT 0.11
    • Dominik ZakCMxG 0.27 · xT 0.14
    • Jakub SylvestrFxG 0.39 · xT 0.13
    SkalicaSkalica
    Form WWLLL
    League ranking xG #11xGA #11xT #12xP/match #11Points #7
    Key players
    • Philip Obinna OnyedikaFxG 0.45 · xT 0.08
    • Levan NonikashviliCAMxG 0.19 · xT 0.11
    • Petr PudhorockyCMxG 0.01 · xT 0.09
    Final score
    00
    The model missed the outcome
    Predicted probabilities: Komárno 46% · Draw 26% · Skalica 27%

    How the bookmaker bet builders went

    The verdict on the pre-built bet builders for this match, priced against the model’s score matrix before kickoff. Graded on the 90-minute result.

    Matchresultat - MFK SkalicaBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 11,62fair 12,40-6 %
    Miss
    Matchresultat - KFC KomarnoBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 6,02fair 8,01-25 %
    Miss

    Match prediction: KomárnoSkalica

    Predicted score matrix

    Skalica
    Komárno
    0
    1
    2
    3
    4+
    0
    0–06.5%
    0–17.3%
    0–24.7%
    0–32.0%
    0–4+0.8%
    1
    1–09.2%
    1–112.2%
    1–27.3%
    1–33.0%
    1–4+1.2%
    2
    2–07.4%
    2–19.1%
    2–25.7%
    2–32.3%
    2–4+1.0%
    3
    3–03.8%
    3–14.7%
    3–22.9%
    3–31.2%
    3–4+0.5%
    4+
    4+–02.1%
    4+–12.6%
    4+–21.6%
    4+–30.7%
    4+–4+0.3%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-112%
    2. 2.1-09%
    3. 3.2-19%
    4. 4.2-07%
    5. 5.1-27%
    Expected goals
    1,551,24
    Both teams to score
    56%

    Over/under goals

    Expected goals: 2,8
    Under 2,547%
    @2.08
    Over 2,553%
    @1.78

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Komárno to win46%
    • Over 1.5 goals77%

    Combined probability

    35%

    Fair odds

    2.87

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

    02 · 3 legs

    Balanced

    • Komárno to win46%
    • Over 2.5 goals53%
    • Andy Masaryk to score19%

    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 score56%
    • Over 2.5 goals53%
    • Philip Obinna Onyedika to score23%
    • Dominik Žák to be booked20%

    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

    The model's value spots

    Bets where the model's probability beats what the odds imply (EV+).

    • 2 · Skalica27% probability@4.50PinnacleEV+23%reference odds
    • X · Draw26% probability@3.94PinnacleEV+4%reference odds
    Bookmaker1 · KomárnoX2 · Skalica
    Betsafe1.903.353.65
    Betsson1.903.353.65
    Nordicbet1.903.353.65
    Pinnacle1.72
    EV+ 4%
    3.94
    EV+ 23%
    4.50

    Odds updated 5 Sept, 08:31

    Odds movement

    Market signal

    The market has moved clearly towards a Komárno win since 31 August — the odds have shortened from 1.93 to 1.72 (−11%).

    1-11 %
    57 %47 %

    1.931.72

    X+12 %
    30 %20 %

    3.523.94

    2+22 %
    28 %18 %

    3.704.50

    Over 2,5-4 %
    58 %48 %

    1.811.75

    Pinnacle · 11 recorded price levels · 31/08/2026 → 05/09/2026 · fixed scale 10 percentage points

    Statistics

    Head-to-head

    8 matches
    Komárno 2Draw 3Skalica 3
    Goals: 59 (⌀ 1,8)

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

    Key facts

    • Skalica have lost 3 in a row.
    xG & xGA per match — 3-game rolling average

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

    Komárno
    Skalica
    When goals are scored and conceded 2026
    Komárno (611)
    Skalica (915)
    Pass networks

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

    Komárno
    Robert Pillar: 211 passningar, xT 0.52PillarKristof Domonkos: 203 passningar, xT 0.28DomonkosDominik Zak: 176 passningar, xT 0.81ZakDominik Spiriak: 173 passningar, xT 0.41SpiriakFilip Kiss: 147 passningar, xT 0.14KissJán Bernát: 136 passningar, xT 0.13BernátAdam Krcik: 130 passningar, xT 0.57KrcikMartin Simko: 122 passningar, xT 0.29SimkoSimon Smehyl: 108 passningar, xT 1.24SmehylBranislav Pindroch: 108 passningar, xT 0.13PindrochFilip Dlubac: 64 passningar, xT 0.08Dlubac
    Skalica
    Patrick Karhan: 130 passningar, xT 0.24KarhanSamuel Sula: 112 passningar, xT 0.21SulaErik Daniel: 104 passningar, xT 0.84DanielLevan Nonikashvili: 86 passningar, xT 0.44NonikashviliDamian Baris: 81 passningar, xT 0.04BarisPetr Pudhorocky: 81 passningar, xT 0.32PudhorockyAdam Ravas: 80 passningar, xT 0.19RavasLukas Simko: 71 passningar, xT 0.49SimkoPhilip Obinna Onyedika: 57 passningar, xT 0.06OnyedikaAdam Morong: 56 passningar, xT 0.06MorongErik Riska: 50 passningar, xT 0.1Riska
    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.

    Komárno
    Robert Pillar: 211 passningar, xT 0.52PillarKristof Domonkos: 203 passningar, xT 0.28DomonkosDominik Zak: 176 passningar, xT 0.81ZakDominik Spiriak: 173 passningar, xT 0.41SpiriakFilip Kiss: 147 passningar, xT 0.14KissJán Bernát: 136 passningar, xT 0.13BernátAdam Krcik: 130 passningar, xT 0.57KrcikMartin Simko: 122 passningar, xT 0.29SimkoSimon Smehyl: 108 passningar, xT 1.24SmehylBranislav Pindroch: 108 passningar, xT 0.13PindrochFilip Dlubac: 64 passningar, xT 0.08Dlubac
    Skalica
    Patrick Karhan: 130 passningar, xT 0.24KarhanSamuel Sula: 112 passningar, xT 0.21SulaErik Daniel: 104 passningar, xT 0.84DanielLevan Nonikashvili: 86 passningar, xT 0.44NonikashviliDamian Baris: 81 passningar, xT 0.04BarisPetr Pudhorocky: 81 passningar, xT 0.32PudhorockyAdam Ravas: 80 passningar, xT 0.19RavasLukas Simko: 71 passningar, xT 0.49SimkoPhilip Obinna Onyedika: 57 passningar, xT 0.06OnyedikaAdam Morong: 56 passningar, xT 0.06MorongErik Riska: 50 passningar, xT 0.1Riska

    The teams in numbers

    PerformanceKomárnoSkalica
    Points37
    xPoints6.46.2
    xG per match1.21.1
    xGA per match1.32.1
    xG within 8s of winning the ball0.190.33
    xGA within 8s of losing the ball0.210.26
    Playing styleKomárnoSkalica
    Build-up efficiency0.340.31
    Field tilt0.530.4
    xT per match1.20.72
    xTA per match0.831.4
    Won balls, offensive half2620
    Pressing intensity0.220.22
    Pressing efficiency0.290.32
    Pressing efficiency, offensive half0.260.26
    Entries into the box per match169
    Entries into the box against1216
    Pass completion %0.770.64
    Pass completion % under pressure0.760.63
    Passes per match378222
    Passes against per match315343
    Switches of play per match24.615.6
    Long balls per match3726
    Set piecesKomárnoSkalica
    xG from free kicks0.10.02
    Corners per match6.25.1
    Corners against per match6.45.8
    xG per corner0.030.02
    xGA per corner against0.030.05
    First touch, offensive corners %0.590.48
    First touch, defensive corners %0.580.49
    OtherKomárnoSkalica
    Throw-in control0.720.7
    The goalkeepersBranislav Pindroch (Komárno)Erik Riska (Skalica)
    Saves1718
    Save %71%78%
    xG prevented71%51%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Komárno vs Skalica according to our model?

    The model gives Komárno a 46% win probability. Full 1X2 picture: Komárno 46%, draw 26%, Skalica 27%.

    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 53% and under at 47%.

    Will both teams score?

    The probability of both teams scoring is 56% 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.