Ekstraklasa11°9,0 mm21 km/h

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    Pogoń SzczecinPogoń SzczecinLow block & direct
    vs
    Korona KielceKorona KielcePossession control
    The model's lean: 1 · Pogoń Szczecin (45%)

    Pogoń Szczecin vs Korona Kielce · Ekstraklasa

    1 · Pogoń Szczecin 45%X 28%27% Korona Kielce · 2

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    Analysis: Pogoń Szczecin – Korona Kielce

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

    Pogoń Szczecin's unbeaten streak in the league, now stretching to seven matches, sets the stage for their clash with Korona Kielce. The home side's ability to capitalize on quick transitions, boasting an xG of 0.37 within eight seconds of regaining possession, is a critical factor that might tip the scales in their favor. This sharpness in exploiting defensive lapses aligns with their direct playing style, which stands in contrast to Korona's preference for possession control.

    The hosts have been formidable on their turf, winning 62% of their home matches historically. While the recent head-to-head record is limited to just four games, with two wins for Pogoń, this statistic is overshadowed by their current form and expected goals advantage. The model gives them a 45% chance to secure victory, a reflection of their xG superiority of 1.7 per match compared to Korona's 1.4. This offensive edge, coupled with a slightly better defensive record, suggests Pogoń has the upper hand.

    With the probability of over 2.5 goals sitting at 54% and both teams to score at 57%, the numbers indicate a game that could lean toward multiple goals. However, the expected rainfall of 9.0 mm is likely to dampen attacking flair, a factor already considered in the model's calculations. The most probable scorelines of 1-1 and 2-1 underscore a competitive yet not overly high-scoring affair.

    From a betting perspective, there's potential value in backing Pogoń Szczecin to win, especially if odds on offer exceed the model's implied probability of 45%. Their home form, recent run, and tactical efficiency position them as favorites to edge out a closely contested match. While predicting a definitive outcome remains a challenge, a 2-1 victory for Pogoń seems the most aligned with the data.

    Pogoń SzczecinPogoń Szczecin
    Form DDDWW
    League ranking xG #5xGA #7xT #15xP/match #3Points #5
    Key players
    • Darko ChurlinovFxG 0.62 · xT 0.12
    • Fredrik UlvestadCMxG 0.04 · xT 0.18
    • Dimitrios KeramitsisCBxG 0.06 · xT 0.08
    Korona KielceKorona Kielce
    Form WDWLW
    League ranking xG #15xGA #9xT #18xP/match #8Points #6
    Key players
    • Mariusz Paweł StępińskiFxG 0.61 · xT 0.04
    • Wiktor DlugoszRWBxG 0.04 · xT 0.18
    • Patrik HellebrandCMxG 0.06 · xT 0.05

    Match prediction: Pogoń Szczecin – Korona Kielce

    Predicted score matrix

    Korona Kielce →
    Pogoń Szczecin →
    0
    1
    2
    3
    4+
    0
    0–06.2%
    0–16.8%
    0–24.4%
    0–31.8%
    0–4+0.7%
    1
    1–09.2%
    1–111.9%
    1–27.0%
    1–32.9%
    1–4+1.1%
    2
    2–07.7%
    2–19.3%
    2–25.7%
    2–32.3%
    2–4+0.9%
    3
    3–04.1%
    3–15.0%
    3–23.1%
    3–31.2%
    3–4+0.5%
    4+
    4+–02.4%
    4+–12.9%
    4+–21.8%
    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. 2.2-19%
    3. 3.1-09%
    4. 4.2-08%
    5. 5.1-27%
    Expected goals
    1,62–1,22
    Both teams to score
    57%

    Over/under goals

    Expected goals: 2,8
    Under 2,546%
    @2.08
    Over 2,554%
    @1.74

    Ready-made bet suggestions

    More combos & build your own →

    01 · 2 legs

    Safe

    • Double chance Pogoń Szczecin or draw (1X)72%
    • Over 1.5 goals78%

    Combined probability

    56%

    Fair odds

    1.78

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

    02 · 3 legs

    Balanced

    • Double chance Pogoń Szczecin or draw (1X)72%
    • Over 2.5 goals54%
    • Paul Omo Mukairu to score18%

    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 score57%
    • Over 2.5 goals54%
    • Mariusz Paweł Stępiński to score18%
    • Slobodan Rubežić 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

    The model's value spots

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

    • 1 · Pogoń Szczecin45% probability@2.27PinnacleEV+2%reference odds
    Bookmaker1 · Pogoń SzczecinX2 · Korona Kielce
    Betsafe2.153.253.10
    Nordicbet2.153.253.10
    Pinnacle
    EV+ 2%
    2.27
    3.103.38

    Odds updated 2 Oct, 08:36

    Statistics

    Head-to-head

    4 matches
    Pogoń Szczecin 2Draw 1Korona Kielce 1
    Goals: 5–2 (⌀ 1,8)

    Head-to-head based on Ekstraklasa data since 2023.

    Key facts

    • Pogon Szczecin are unbeaten in their last 7 league matches.
    • Pogon Szczecin win 62% of their home matches all-time (39 played).
    xG & xGA per match — 3-game rolling average

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

    Pogoń Szczecin
    Korona Kielce
    When goals are scored and conceded — 2026
    Pogoń Szczecin (12–6)
    Korona Kielce (12–10)
    Pass networks

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

    Pogoń Szczecin
    Patryk Dziczek: 213 passningar, xT 0.53DziczekDimitrios Keramitsis: 207 passningar, xT 0.62KeramitsisLukas Willen: 152 passningar, xT 0.13WillenValentin Cojocaru: 124 passningar, xT 0.3CojocaruBenjamin Mendy: 107 passningar, xT 0.65MendyMaciej Wojciechowski: 106 passningar, xT 0.13WojciechowskiHussein Haydar Hussein Ali: 78 passningar, xT 0.17AliDarko Churlinov: 67 passningar, xT 0.49ChurlinovJan Bieganski: 62 passningar, xT 0.05BieganskiLeonardo Borges da Silva: 61 passningar, xT 0.17SilvaPaul Mukairu: 54 passningar, xT -0.02Mukairu
    Korona Kielce
    Patrik Hellebrand: 305 passningar, xT 0.2HellebrandAriel Mosor: 195 passningar, xT 0.15MosorSlobodan Rubežić: 178 passningar, xT 0.56RubežićWiktor Dlugosz: 171 passningar, xT 1.34DlugoszMarcel Pieczek: 151 passningar, xT 0.32PieczekKamil Jakubczyk: 150 passningar, xT 0.29JakubczykXavier Dziekonski: 110 passningar, xT 0.07DziekonskiMartin Remacle: 87 passningar, xT 0.15RemacleOndřej Lingr: 58 passningar, xT 0.07LingrMariusz Paweł Stępiński: 52 passningar, xT -0.06StępińskiCamilo Mena: 42 passningar, xT 0Mena
    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.

    Pogoń Szczecin
    Patryk Dziczek: 213 passningar, xT 0.53DziczekDimitrios Keramitsis: 207 passningar, xT 0.62KeramitsisLukas Willen: 152 passningar, xT 0.13WillenValentin Cojocaru: 124 passningar, xT 0.3CojocaruBenjamin Mendy: 107 passningar, xT 0.65MendyMaciej Wojciechowski: 106 passningar, xT 0.13WojciechowskiHussein Haydar Hussein Ali: 78 passningar, xT 0.17AliDarko Churlinov: 67 passningar, xT 0.49ChurlinovJan Bieganski: 62 passningar, xT 0.05BieganskiLeonardo Borges da Silva: 61 passningar, xT 0.17SilvaPaul Mukairu: 54 passningar, xT -0.02Mukairu
    Korona Kielce
    Patrik Hellebrand: 305 passningar, xT 0.2HellebrandAriel Mosor: 195 passningar, xT 0.15MosorSlobodan Rubežić: 178 passningar, xT 0.56RubežićWiktor Dlugosz: 171 passningar, xT 1.34DlugoszMarcel Pieczek: 151 passningar, xT 0.32PieczekKamil Jakubczyk: 150 passningar, xT 0.29JakubczykXavier Dziekonski: 110 passningar, xT 0.07DziekonskiMartin Remacle: 87 passningar, xT 0.15RemacleOndřej Lingr: 58 passningar, xT 0.07LingrMariusz Paweł Stępiński: 52 passningar, xT -0.06StępińskiCamilo Mena: 42 passningar, xT 0Mena

    The teams in numbers

    PerformancePogoń SzczecinKorona Kielce
    Points1515
    xPoints13.712.5
    xG per match1.71.4
    xGA per match1.41.6
    xG within 8s of winning the ball0.370.17
    xGA within 8s of losing the ball0.150.21
    Playing stylePogoń SzczecinKorona Kielce
    Build-up efficiency0.320.32
    Field tilt0.410.51
    xT per match0.990.76
    xTA per match1.21.3
    Won balls, offensive half2425
    Pressing intensity0.240.23
    Pressing efficiency0.290.3
    Pressing efficiency, offensive half0.220.25
    Entries into the box per match1211
    Entries into the box against1414
    Pass completion %0.730.76
    Pass completion % under pressure0.70.7
    Passes per match287340
    Passes against per match429371
    Switches of play per match25.528.1
    Long balls per match3532
    Set piecesPogoń SzczecinKorona Kielce
    xG from free kicks0.150.07
    Corners per match3.64.7
    Corners against per match45.9
    xG per corner0.050.03
    xGA per corner against0.030.04
    First touch, offensive corners %0.310.44
    First touch, defensive corners %0.560.52
    OtherPogoń SzczecinKorona Kielce
    Throw-in control0.730.75
    The goalkeepersValentin Cojocaru (Pogoń Szczecin)Xavier Dziekonski (Korona Kielce)
    Saves3325
    Save %87%71%
    xG prevented62%55%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Pogoń Szczecin vs Korona Kielce according to our model?

    The model gives Pogoń Szczecin a 45% win probability. Full 1X2 picture: Pogoń Szczecin 45%, draw 28%, Korona Kielce 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 54% and under at 46%.

    Will both teams score?

    The probability of both teams scoring is 57% 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.