Danish SuperligaCeres Park, Aarhus9°0,6 mm17 km/h

    Läs på svenska
    AGFAGFPossession & high press
    vs
    SønderjyskESønderjyskELow block & direct
    The model's lean: 1 · AGF (63%)Best value by the model: Under 3,5 @ 1.64 (+4 %)

    AGF vs SønderjyskE · Danish Superliga

    1 · AGF 63%X 22%16% SønderjyskE · 2

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    Analysis: AGF – SønderjyskE

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

    TEXT: A clash between contrasting styles shapes up as AGF hosts Sønderjyske in the Danish Superliga. The home side is all about possession and high pressing, a strategy that often dictates the tempo in their favor. In contrast, the visitors prefer to sit back and strike directly, a tactic that could struggle against AGF's pressing game. With a model probability giving AGF a 63% chance to win, the hosts are clear favorites.

    The expected goals paint a similar picture, with AGF generating 2.02 xG compared to Sønderjyske's 1.02. AGF's ability to create chances quickly after winning the ball, boasting an xG of 0.37 in such scenarios, highlights their dangerous press. In comparison, Sønderjyske has a mere 0.2 in the same metric, indicating their limited threat when trying to catch opponents off guard. Despite this, the head-to-head record since 2022 is surprisingly even at 1 win apiece and 2 draws, though a sample of four matches carries less weight than the current form.

    The numbers suggest a game where AGF should dominate possession and chances, but with a 56% chance of both teams scoring, Sønderjyske can't be counted out entirely. The likelihood of over 2.5 goals at 59% indicates a reasonable chance for goals, with the model's most probable scorelines of 2-1, 2-0, or even 1-1 underlining the hosts' slight edge.

    Keep an eye on the pressing game; it's AGF's sharpest tool and could be the decisive factor in carving out a victory.

    AGFAGF
    Form LLDLD
    League ranking xG #5xGA #9xT #6xP/match #8Points #11
    Key players
    • Gift LinksRWxG 0.19 · xT 0.24
    • Sebastian JørgensenRWxG 0.22 · xT 0.24
    • Frederik EmmeryLWxG 0.15 · xT 0.27
    SønderjyskESønderjyskE
    Form LLLDW
    League ranking xG #12xGA #12xT #10xP/match #12Points #12
    Key players
    • Osaze De RosarioFxG 0.32 · xT 0.05
    • Mohamed Cherif HaidaraCAMxG 0.25 · xT -0.01
    • Ismaïl SeydiRWxG 0.17 · xT 0.10

    Match prediction: AGF – SønderjyskE

    Predicted score matrix

    SønderjyskE →
    AGF →
    0
    1
    2
    3
    4+
    0
    0–05.0%
    0–14.6%
    0–22.5%
    0–30.8%
    0–4+0.3%
    1
    1–09.3%
    1–110.1%
    1–25.0%
    1–31.7%
    1–4+0.5%
    2
    2–09.7%
    2–110.0%
    2–25.1%
    2–31.7%
    2–4+0.6%
    3
    3–06.6%
    3–16.7%
    3–23.4%
    3–31.2%
    3–4+0.4%
    4+
    4+–05.3%
    4+–15.4%
    4+–22.8%
    4+–30.9%
    4+–4+0.3%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-110%
    2. 2.2-110%
    3. 3.2-010%
    4. 4.1-09%
    5. 5.3-17%
    Expected goals
    2,02–1,02
    Both teams to score
    56%

    Over/under goals

    Expected goals: 3,0
    Under 2,541%
    @2.48EV+2%
    Over 2,559%
    @1.52

    Ready-made bet suggestions

    More combos & build your own →

    01 · 2 legs

    Safe

    • AGF to win63%
    • Over 1.5 goals81%

    Combined probability

    51%

    Fair odds

    1.97

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

    02 · 3 legs

    Balanced

    • AGF to win63%
    • Over 2.5 goals59%
    • Jens Jønsson to score28%

    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 goals59%
    • Jens Jønsson to score28%
    • Sefer Emini to be booked23%

    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+).

    • Under 3.564% probability@1.64PinnacleEV+4%reference odds
    • 1 · AGF63% probability@1.65BetsafeEV+4%reference odds
    • 1 · AGF63% probability@1.65NordicbetEV+4%reference odds
    Bookmaker1 · AGFX2 · SønderjyskE
    Betsafe
    EV+ 4%
    1.65
    3.955.05
    Nordicbet
    EV+ 4%
    1.65
    4.005.10
    Pinnacle1.594.404.91

    Odds updated 3 Oct, 07:36

    Statistics

    Head-to-head

    4 matches
    AGF 1Draw 2SønderjyskE 1
    Goals: 6–6 (⌀ 3)

    Head-to-head based on Danish Superliga data since 2022.

    xG & xGA per match — 3-game rolling average

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

    AGF
    SønderjyskE
    When goals are scored and conceded — 2026
    AGF (11–17)
    SønderjyskE (12–21)
    Pass networks

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

    AGF
    Eric Kahl: 249 passningar, xT 0.73KahlColin Rösler: 239 passningar, xT 0.55RöslerMagnus Knudsen: 213 passningar, xT 0.12KnudsenKristian Arnstad: 207 passningar, xT 0.47ArnstadLuka Callo: 187 passningar, xT 0.09CalloMads Hedenstad Christiansen: 138 passningar, xT 0.13ChristiansenDaniel Leo Gretarsson: 132 passningar, xT 0.11GretarssonRasmus Carstensen: 110 passningar, xT 0.06CarstensenSebastian Jørgensen: 98 passningar, xT 0.44JørgensenFrederik Emmery: 89 passningar, xT 1.14EmmeryMikael Anderson: 87 passningar, xT 0.47Anderson
    SønderjyskE
    Maxime Soulas: 207 passningar, xT 0.72SoulasAlexander Munksgaard: 131 passningar, xT 0.75MunksgaardBrynjar Ingi Bjarnason: 108 passningar, xT 0.07BjarnasonRasmus Vinderslev: 105 passningar, xT 0.43VinderslevJacob Steen Christensen: 103 passningar, xT 0.02ChristensenDaniel Leo Gretarsson: 97 passningar, xT 0.49GretarssonNick Shinton: 86 passningar, xT 0.17ShintonEbube Duru: 84 passningar, xT 0.18DuruDalton Wilkins: 69 passningar, xT 0.08WilkinsMohamed Cherif Haidara: 68 passningar, xT -0.03HaidaraAndreas Oggesen: 65 passningar, xT 0.09Oggesen
    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.

    AGF
    Eric Kahl: 249 passningar, xT 0.73KahlColin Rösler: 239 passningar, xT 0.55RöslerMagnus Knudsen: 213 passningar, xT 0.12KnudsenKristian Arnstad: 207 passningar, xT 0.47ArnstadLuka Callo: 187 passningar, xT 0.09CalloMads Hedenstad Christiansen: 138 passningar, xT 0.13ChristiansenDaniel Leo Gretarsson: 132 passningar, xT 0.11GretarssonRasmus Carstensen: 110 passningar, xT 0.06CarstensenSebastian Jørgensen: 98 passningar, xT 0.44JørgensenFrederik Emmery: 89 passningar, xT 1.14EmmeryMikael Anderson: 87 passningar, xT 0.47Anderson
    SønderjyskE
    Maxime Soulas: 207 passningar, xT 0.72SoulasAlexander Munksgaard: 131 passningar, xT 0.75MunksgaardBrynjar Ingi Bjarnason: 108 passningar, xT 0.07BjarnasonRasmus Vinderslev: 105 passningar, xT 0.43VinderslevJacob Steen Christensen: 103 passningar, xT 0.02ChristensenDaniel Leo Gretarsson: 97 passningar, xT 0.49GretarssonNick Shinton: 86 passningar, xT 0.17ShintonEbube Duru: 84 passningar, xT 0.18DuruDalton Wilkins: 69 passningar, xT 0.08WilkinsMohamed Cherif Haidara: 68 passningar, xT -0.03HaidaraAndreas Oggesen: 65 passningar, xT 0.09Oggesen

    The teams in numbers

    PerformanceAGFSønderjyskE
    Points55
    xPoints11.59.8
    xG per match1.60.96
    xGA per match1.51.9
    xG within 8s of winning the ball0.370.2
    xGA within 8s of losing the ball0.290.6
    Playing styleAGFSønderjyskE
    Build-up efficiency0.310.31
    Field tilt0.590.34
    xT per match1.10.85
    xTA per match0.951.2
    Won balls, offensive half2523
    Pressing intensity0.240.23
    Pressing efficiency0.280.24
    Pressing efficiency, offensive half0.270.18
    Entries into the box per match1710
    Entries into the box against1216
    Pass completion %0.780.7
    Pass completion % under pressure0.710.66
    Passes per match423275
    Passes against per match312474
    Switches of play per match23.123.9
    Long balls per match2634
    Set piecesAGFSønderjyskE
    xG from free kicks0.050.09
    Corners per match7.14.4
    Corners against per match35.5
    xG per corner0.030.02
    xGA per corner against0.030.02
    First touch, offensive corners %0.30.38
    First touch, defensive corners %0.560.62
    OtherAGFSønderjyskE
    Throw-in control0.710.74
    The goalkeepersMads Hedenstad Christiansen (AGF)Nicolai Flo (SønderjyskE)
    Saves1912
    Save %58%67%
    xG prevented39%52%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins AGF vs SønderjyskE according to our model?

    The model gives AGF a 63% win probability. Full 1X2 picture: AGF 63%, draw 22%, SønderjyskE 16%.

    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 59% and under at 41%.

    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.