Ekstraklasa14°2,2 mm21 km/h

    Läs på svenska
    Jagiellonia BiałystokJagiellonia BiałystokPossession control
    21
    Slask WroclawSlask WroclawLow block & direct
    The model's lean: 1 · Jagiellonia Białystok (59%)Best value by the model: Over 4,5 @ 4.80 (+5 %)

    Jagiellonia BiałystokSlask Wroclaw · Ekstraklasa

    1 · Jagiellonia Białystok 59%X 20%20% Slask Wroclaw · 2

    Analysis: Jagiellonia BiałystokSlask Wroclaw

    Marcus Johansson · · Analysis from the match model · How the predictions work

    The model gives Jagiellonia Białystok a solid 59% win probability, a clear lean towards the hosts. Their possession-based style contrasts sharply with Slask Wroclaw's low block and direct approach, hinting at a clash of football philosophies. Despite an unbeaten head-to-head record since 2023, the small sample of two draws weighs less than their current form and expected goals. Slask's defensive resilience could be tested against Jagiellonia's controlled build-up.

    Both teams have vulnerabilities—Jagiellonia's 1.6 xGA suggests they struggle defensively, while Slask's 1.4 xG indicates inefficiencies in attacking play. Yet, the expected goals tilt in Jagiellonia's favor at 1.98 to 1.22, reinforcing their edge. With 62% probability of over 2.5 goals and 61% for both teams to score, the numbers hint at a match that could open up, despite the potential dampening effect of rain.

    The likeliest scorelines—1-1 and 2-1—reflect the delicate balance between these sides. However, Jagiellonia's home advantage and superior xG suggest a 2-1 victory is within reach. For those seeking value, the over 2.5 goals at odds of 1.80 with Unibet aligns well with the statistical outlook, offering an enticing punt.

    Jagiellonia BiałystokJagiellonia Białystok
    Form WWLWL
    League ranking xG #6xGA #9xT #7xP/match #10Points #6
    Key players
    • Guilherme Manuel Serrão MontóiaLBxG 0.18 · xT 0.27
    • Kajetan SzmytLWxG 0.12 · xT 0.09
    • Nik PrelecFxG 0.51 · xT 0.04
    Slask WroclawSlask Wroclaw
    Form WDLDD
    League ranking xG #14xGA #8xT #2xP/match #9Points #14
    Key players
    • Piotr Samiec-TalarRWxG 0.32 · xT 0.31
    • Luka MarjanacFxG 0.43 · xT 0.23
    • Przemyslaw BanaszakFxG 0.30 · xT 0.12
    Final score
    21
    The model called the outcome
    Predicted probabilities: Jagiellonia Białystok 59% · Draw 20% · Slask Wroclaw 20%

    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 - Jagiellonia BialystokBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 4,36fair 5,10-14 %
    Miss
    Matchresultat - Slask WroclawBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 10,74fair 13,42-20 %
    Miss

    Match prediction: Jagiellonia BiałystokSlask Wroclaw

    Predicted score matrix

    Slask Wroclaw
    Jagiellonia Białystok
    0
    1
    2
    3
    4+
    0
    0–04.4%
    0–14.7%
    0–23.0%
    0–31.2%
    0–4+0.5%
    1
    1–07.8%
    1–110.2%
    1–26.0%
    1–32.5%
    1–4+1.0%
    2
    2–08.0%
    2–19.7%
    2–26.0%
    2–32.4%
    2–4+1.0%
    3
    3–05.3%
    3–16.4%
    3–23.9%
    3–31.6%
    3–4+0.6%
    4+
    4+–04.1%
    4+–15.0%
    4+–23.0%
    4+–31.2%
    4+–4+0.5%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-110%
    2. 2.2-110%
    3. 3.2-08%
    4. 4.1-08%
    5. 5.3-16%
    Expected goals
    1,981,22
    Both teams to score
    61%

    Over/under goals

    Expected goals: 3,2
    Under 2,538%
    @2.35
    Over 2,562%
    @1.60

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Jagiellonia Białystok to win59%
    • Over 1.5 goals83%

    Combined probability

    47%

    Fair odds

    2.14

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

    02 · 3 legs

    Balanced

    • Jagiellonia Białystok to win59%
    • Over 2.5 goals62%
    • Sergio Lozano Lluch to score38%

    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 score61%
    • Over 2.5 goals62%
    • Sergio Lozano Lluch to score38%
    • Irodotos Christodoulou 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+).

    • Over 4.522% probability@4.80Paddy PowerEV+5%reference odds
    • Over 3.540% probability@2.60Paddy PowerEV+3%reference odds
    Bookmaker1 · Jagiellonia BiałystokX2 · Slask Wroclaw
    Betfair Exchange1.101.101.10
    Betsafe1.683.854.10
    Betsson1.683.854.10
    Nordicbet1.683.854.10
    Paddy Power1.673.804.20
    Pinnacle1.684.324.57

    Odds updated 6 Sept, 11:36

    Odds movement

    1+2 %
    59 %54 %

    1.641.68

    X+2 %
    25 %20 %

    4.244.32

    2+1 %
    23 %18 %

    4.534.57

    Pinnacle · 7 recorded price levels · 04/09/2026 → 06/09/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    2 matches
    Jagiellonia Białystok 0Draw 2Slask Wroclaw 0
    Goals: 33 (⌀ 3)

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

    xG & xGA per match — 3-game rolling average

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

    Jagiellonia Białystok
    Slask Wroclaw
    When goals are scored and conceded 2026
    Jagiellonia Białystok (97)
    Slask Wroclaw (89)
    Pass networks

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

    Jagiellonia Białystok
    Bernardo Vital: 248 passningar, xT 0.44VitalGuilherme Manuel Serrão Montóia: 241 passningar, xT 1.15MontóiaNorbert Wojtuszek: 237 passningar, xT 0.23WojtuszekYuki Kobayashi: 208 passningar, xT 0.15KobayashiTaras Romanczuk: 184 passningar, xT 0.21RomanczukSlawomir Abramowicz: 129 passningar, xT -0.1AbramowiczSergio Lozano: 83 passningar, xT 0.46LozanoApostolos Konstantopoulos: 79 passningar, xT 0.26KonstantopoulosJesus Imaz: 77 passningar, xT 0.52ImazRodrigo Fernandes da Conceição: 74 passningar, xT 0.86ConceiçãoKajetan Szmyt: 73 passningar, xT 0.17Szmyt
    Slask Wroclaw
    Yehor Matsenko: 177 passningar, xT 0.68MatsenkoGrzegorz Tomasiewicz: 171 passningar, xT 0.35TomasiewiczPiotr Samiec-Talar: 161 passningar, xT 1.4Samiec-TalarMarc Llinares: 149 passningar, xT 0.23LlinaresMariusz Malec: 137 passningar, xT 0.19MalecIrodotos Christodoulou: 132 passningar, xT -0.02ChristodoulouMichał Rosiak: 107 passningar, xT 0.22RosiakJorge Luis Yriarte González: 101 passningar, xT 0.23GonzálezKarol Stanisław Niemczycki: 73 passningar, xT 0.11NiemczyckiLuka Marjanac: 70 passningar, xT 0.54MarjanacLamine Ba: 69 passningar, xT 0.11Ba
    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.

    Jagiellonia Białystok
    Bernardo Vital: 248 passningar, xT 0.44VitalGuilherme Manuel Serrão Montóia: 241 passningar, xT 1.15MontóiaNorbert Wojtuszek: 237 passningar, xT 0.23WojtuszekYuki Kobayashi: 208 passningar, xT 0.15KobayashiTaras Romanczuk: 184 passningar, xT 0.21RomanczukSlawomir Abramowicz: 129 passningar, xT -0.1AbramowiczSergio Lozano: 83 passningar, xT 0.46LozanoApostolos Konstantopoulos: 79 passningar, xT 0.26KonstantopoulosJesus Imaz: 77 passningar, xT 0.52ImazRodrigo Fernandes da Conceição: 74 passningar, xT 0.86ConceiçãoKajetan Szmyt: 73 passningar, xT 0.17Szmyt
    Slask Wroclaw
    Yehor Matsenko: 177 passningar, xT 0.68MatsenkoGrzegorz Tomasiewicz: 171 passningar, xT 0.35TomasiewiczPiotr Samiec-Talar: 161 passningar, xT 1.4Samiec-TalarMarc Llinares: 149 passningar, xT 0.23LlinaresMariusz Malec: 137 passningar, xT 0.19MalecIrodotos Christodoulou: 132 passningar, xT -0.02ChristodoulouMichał Rosiak: 107 passningar, xT 0.22RosiakJorge Luis Yriarte González: 101 passningar, xT 0.23GonzálezKarol Stanisław Niemczycki: 73 passningar, xT 0.11NiemczyckiLuka Marjanac: 70 passningar, xT 0.54MarjanacLamine Ba: 69 passningar, xT 0.11Ba

    The teams in numbers

    PerformanceJagiellonia BiałystokSlask Wroclaw
    Points96
    xPoints6.78.3
    xG per match1.71.4
    xGA per match1.61.4
    xG within 8s of winning the ball0.130.36
    xGA within 8s of losing the ball0.490.32
    Playing styleJagiellonia BiałystokSlask Wroclaw
    Build-up efficiency0.280.3
    Field tilt0.570.57
    xT per match1.21.3
    xTA per match1.11.2
    Won balls, offensive half2225
    Pressing intensity0.230.24
    Pressing efficiency0.330.28
    Pressing efficiency, offensive half0.280.24
    Entries into the box per match1518
    Entries into the box against1316
    Pass completion %0.790.73
    Pass completion % under pressure0.740.7
    Passes per match397305
    Passes against per match293346
    Switches of play per match23.119.6
    Long balls per match3127
    Set piecesJagiellonia BiałystokSlask Wroclaw
    xG from free kicks0.010.01
    Corners per match4.23.7
    Corners against per match4.65.5
    xG per corner0.020.02
    xGA per corner against0.040.03
    First touch, offensive corners %0.330.57
    First touch, defensive corners %0.610.62
    OtherJagiellonia BiałystokSlask Wroclaw
    Throw-in control0.760.74
    The goalkeepersSlawomir Abramowicz (Jagiellonia Białystok)Karol Stanisław Niemczycki (Slask Wroclaw)
    Saves1320
    Save %65%74%
    xG prevented43%65%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Jagiellonia Białystok vs Slask Wroclaw according to our model?

    The model gives Jagiellonia Białystok a 59% win probability. Full 1X2 picture: Jagiellonia Białystok 59%, draw 20%, Slask Wroclaw 20%.

    What is the most likely scoreline?

    The model's most likely final score is 1-1 at 10% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 62% and under at 38%.

    Will both teams score?

    The probability of both teams scoring is 61% 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.

    More matches in the league

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