Swedish SuperettanSkarsjövallen, Uddevalla20°2,1 mm14 km/h

    Läs på svenska
    LjungskileLjungskilePossession control
    vs
    ÖsterÖsterCounter-attacks & crosses
    The model's lean: 1 · Ljungskile (51%)

    LjungskileÖster · Swedish Superettan

    1 · Ljungskile 51%X 25%24% Öster · 2

    Analysis: LjungskileÖster

    Sofia Andersson · · How the predictions work

    Ljungskile SK, with a model probability of 51%, finds itself in a favorable position against Östers IF, who come in at just 24%. This tilt towards the home side is backed by the expected goals — Ljungskile SK sits at 1.94 compared to Östers IF’s 1.36. Despite being behind on points with 23 to Östers IF's 26, Ljungskile shows more efficiency with an xPoints advantage of 26.1 to 20.3, suggesting their play has been more productive than the standings might reflect.

    With the most likely scorelines pointing towards a 1-1 or 2-1 result, the game seems poised for a close contest. However, the numbers suggest Ljungskile SK is more likely to come out on top, potentially with a 2-1 scoreline. They dominate the head-to-head records since 2024, albeit from a single match, which doesn't offer much weight but provides a psychological edge nevertheless.

    Östers IF's preference for counter-attacks and crosses might struggle against Ljungskile SK's possession control tactics. With Ljungskile allowing just 1.3 xGA per match compared to Östers IF’s 1.7, the visitors might find it challenging to break down the home defense, while Ljungskile seems poised to exploit their chances more fully.

    The weather isn't a factor here, so the model's outlook for a game exceeding 2.5 goals at 64% likely holds water. This suggests an entertaining match with plenty of attacking action, despite potential defensive resilience.

    For those seeking an intriguing betting angle, the draw offers value at odds of 4.04 with Pinnacle. The model rates a draw at 25%, which aligns perfectly with the bookmaker's odds, giving punters a chance to back a result that might just defy the expected home advantage. Still, Ljungskile SK looks the stronger side, and they might just edge a victory in what promises to be a competitive encounter.

    LjungskileLjungskile
    Form WWWDL
    League ranking xG #2xGA #8xT #7xP/match #6Points #11
    Key players
    • Issaka SeiduLWxG 0.15 · xT 0.20
    • Isaac ShearsFxG 0.42 · xT 0.03
    • Lukas Lindholm CornerFxG 0.23 · xT 0.01
    ÖsterÖster
    Form LWWLL
    League ranking xG #13xGA #16xT #13xP/match #13Points #7
    Key players
    • Linus CarlstrandFxG 0.46 · xT -0.02
    • Dennis OlssonLBxG 0.03 · xT 0.40
    • Oscar UddenäsRWxG 0.15 · xT 0.12

    Match prediction: LjungskileÖster

    Predicted score matrix

    Öster
    Ljungskile
    0
    1
    2
    3
    4+
    0
    0–03.9%
    0–14.7%
    0–23.4%
    0–31.5%
    0–4+0.7%
    1
    1–06.9%
    1–110.0%
    1–26.6%
    1–33.0%
    1–4+1.4%
    2
    2–06.9%
    2–19.4%
    2–26.4%
    2–32.9%
    2–4+1.3%
    3
    3–04.5%
    3–16.1%
    3–24.2%
    3–31.9%
    3–4+0.9%
    4+
    4+–03.4%
    4+–14.6%
    4+–23.1%
    4+–31.4%
    4+–4+0.7%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-110%
    2. 2.2-19%
    3. 3.2-07%
    4. 4.1-07%
    5. 5.1-27%
    Expected goals
    1,941,36
    Both teams to score
    64%

    Over/under goals

    Expected goals: 3,3
    Under 2,536%
    @2.48
    Over 2,564%
    @1.50

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Ljungskile to win51%
    • Over 1.5 goals84%

    Combined probability

    44%

    Fair odds

    2.29

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

    02 · 3 legs

    Balanced

    • Ljungskile to win51%
    • Over 2.5 goals64%
    • Vilmer Tyrén to score24%

    Combined probability

    9%

    Fair odds

    11.55

    Result and goals are priced jointly from the matrix; the scorer is the model's most likely in the picked side.

    03 · 4 legs

    Bold

    • Both teams to score64%
    • Over 2.5 goals64%
    • Vilmer Tyrén to score24%
    • Al-Hussein Shakir to be booked23%

    Combined probability

    3%

    Fair odds

    33.51

    The goal-fest: both teams score with at least three goals — combined with the match's most likely scorer and card candidate.

    Odds & value

    The model's value spots

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

    • 1 · Ljungskile51% probability@1.97BetsafeEV+1%
    • 1 · Ljungskile51% probability@1.97BetssonEV+1%
    • 1 · Ljungskile51% probability@1.97NordicbetEV+1%
    Bookmaker1 · LjungskileX2 · Öster
    Betsafe
    EV+ 1%
    1.97
    3.623.67
    Betsson
    EV+ 1%
    1.97
    3.623.67
    Nordicbet
    EV+ 1%
    1.97
    3.623.67
    Pinnacle1.903.284.21

    Odds updated 12 Aug, 15:56

    Odds movement

    Market signal

    The market has moved clearly towards the draw since 8 August — the odds have shortened from 4.09 to 3.28 (−20%).

    1+4 %
    55 %45 %

    1.831.90

    X-20 %
    31 %21 %

    4.093.28

    2+17 %
    29 %19 %

    3.614.21

    Pinnacle · 7 recorded price levels · 08/08/2026 → 12/08/2026 · fixed scale 10 percentage points

    Statistics

    Head-to-head

    1 matches
    Ljungskile 1Draw 0Öster 0
    Goals: 41 (⌀ 5)

    Head-to-head based on Superettan data since 2024.

    xG & xGA per match — 3-game rolling average

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

    Ljungskile
    Öster
    When goals are scored and conceded 2026
    Ljungskile (2524)
    Öster (2727)
    Pass networks

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

    Ljungskile
    Ivan Maric: 194 passningar, xT 0.4MaricFilip Ambroz: 170 passningar, xT 1.28AmbrozDaniel Ljung: 168 passningar, xT 0.46LjungEmilio Reljanovic: 158 passningar, xT 0.24ReljanovicGideon Mensah: 131 passningar, xT 0.17MensahDaniel Lagerlöf: 121 passningar, xT 1.62LagerlöfMehmet Uzel: 109 passningar, xT 1.58UzelAbdishakur Bashir Omar: 78 passningar, xT 0.32OmarHugo Borstam: 76 passningar, xT 0.58BorstamLukas Eriksson: 74 passningar, xT 0.31ErikssonWilliam Nilsson: 58 passningar, xT 0.31Nilsson
    Öster
    Sebastian Hedlund: 194 passningar, xT 0.13HedlundDennis Olsson: 185 passningar, xT 1.55OlssonDaniel Ask: 183 passningar, xT 1.03AskHannes Bladh Pijaca: 182 passningar, xT 0.15PijacaTatu Varmanen: 122 passningar, xT 0.06VarmanenMusa Jatta: 114 passningar, xT 0.11JattaKingsley Gyamfi: 85 passningar, xT -0.19GyamfiOscar Uddenäs: 82 passningar, xT 0.16UddenäsRaymond Adjei: 76 passningar, xT 0.17AdjeiSamuel Burakowsky: 74 passningar, xT 1.04BurakowskyCarl Lundahl Persson: 50 passningar, xT 0.14Persson
    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.

    Ljungskile
    Ivan Maric: 194 passningar, xT 0.4MaricFilip Ambroz: 170 passningar, xT 1.28AmbrozDaniel Ljung: 168 passningar, xT 0.46LjungEmilio Reljanovic: 158 passningar, xT 0.24ReljanovicGideon Mensah: 131 passningar, xT 0.17MensahDaniel Lagerlöf: 121 passningar, xT 1.62LagerlöfMehmet Uzel: 109 passningar, xT 1.58UzelAbdishakur Bashir Omar: 78 passningar, xT 0.32OmarHugo Borstam: 76 passningar, xT 0.58BorstamLukas Eriksson: 74 passningar, xT 0.31ErikssonWilliam Nilsson: 58 passningar, xT 0.31Nilsson
    Öster
    Sebastian Hedlund: 194 passningar, xT 0.13HedlundDennis Olsson: 185 passningar, xT 1.55OlssonDaniel Ask: 183 passningar, xT 1.03AskHannes Bladh Pijaca: 182 passningar, xT 0.15PijacaTatu Varmanen: 122 passningar, xT 0.06VarmanenMusa Jatta: 114 passningar, xT 0.11JattaKingsley Gyamfi: 85 passningar, xT -0.19GyamfiOscar Uddenäs: 82 passningar, xT 0.16UddenäsRaymond Adjei: 76 passningar, xT 0.17AdjeiSamuel Burakowsky: 74 passningar, xT 1.04BurakowskyCarl Lundahl Persson: 50 passningar, xT 0.14Persson

    The teams in numbers

    PerformanceLjungskileÖster
    Points2326
    xPoints26.120.3
    xG per match1.61.1
    xGA per match1.31.7
    xG within 8s of winning the ball0.290.22
    xGA within 8s of losing the ball0.250.29
    Playing styleLjungskileÖster
    Build-up efficiency0.360.36
    Field tilt0.520.49
    xT per match1.61.3
    xTA per match1.41.8
    Won balls, offensive half3228
    Pressing intensity0.580.56
    Pressing efficiency0.290.26
    Pressing efficiency, offensive half0.290.28
    Entries into the box per match1714
    Entries into the box against1419
    Pass completion %0.760.8
    Pass completion % under pressure0.710.75
    Passes per match338386
    Passes against per match326361
    Switches of play per match18.813.1
    Long balls per match3729
    Set piecesLjungskileÖster
    xG from free kicks0.20.13
    Corners per match5.75.5
    Corners against per match5.16
    xG per corner0.030.02
    xGA per corner against0.030.03
    First touch, offensive corners %0.410.38
    First touch, defensive corners %0.630.61
    OtherLjungskileÖster
    Throw-in control0.530.56
    The goalkeepersLukas Eriksson (Ljungskile)Carl Lundahl Persson (Öster)
    Saves5878
    Save %72%77%
    xG prevented52%56%
    Claims103 (94%)92 (86%)

    Frequently asked questions

    Who wins Ljungskile vs Öster according to our model?

    The model gives Ljungskile a 51% win probability. Full 1X2 picture: Ljungskile 51%, draw 25%, Öster 24%.

    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 64% and under at 36%.

    Will both teams score?

    The probability of both teams scoring is 64% 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.