Swedish SuperettanSkarsjövallen, Uddevalla15°1,1 mm17 km/h

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    LjungskileLjungskilePossession control
    21
    NorrbyNorrbyCounter-attacks & crosses
    The model's lean: 1 · Ljungskile (43%)Best value by the model: 2 · Norrby @ 3.40 (+9 %)

    LjungskileNorrby · Swedish Superettan

    1 · Ljungskile 43%X 25%32% Norrby · 2

    Analysis: LjungskileNorrby

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

    Ljungskile enters this clash with a slight edge according to model probabilities, but the match is far from a straightforward affair. The hosts lean on possession control, hoping to dictate the game through careful build-up play, while Norrby thrives on counter attacks and crosses, a style that can exploit any slip in concentration from their opponents. With only one head-to-head encounter since 2024, which Norrby won, the sample size is too small to draw significant conclusions from their previous meeting.

    The expected goals tell an intriguing story of balance and tension. Ljungskile is expected to score 1.75 goals to Norrby's 1.25, underscoring the home side's slight upper hand. However, Ljungskile's possession approach may leave gaps for Norrby's counters, potentially allowing the visitors to punch above their weight. The likelihood of a 1-1 draw or a narrow 2-1 or 1-0 victory for Ljungskile reflects this delicate balance between possession and counter-attacking dynamism.

    The model's lean towards an over 2.5 goals scenario at 58% suggests an open game, despite Ljungskile's controlled style. While both teams are likely to find the net (59% chance), the key lies in how effectively Norrby can counter Ljungskile's possession without being overly exposed at the back. The match might feel like a chess game, but with opportunities created from rapid transitions and width exploitation.

    While Ljungskile holds a slight edge in terms of points and xG metrics, Norrby's counter-attacking prowess could be the equalizer. Interestingly, the away win offers substantial value at odds of 3.7 across multiple bookmakers, including Betsafe, Betsson, and Nordicbet. Despite Ljungskile's home advantage, that 18% edge in value makes the visitors an enticing prospect for bettors looking to capitalize on a potential upset. Ending with a sharp angle, Norrby's ability to counter and the inherent value in their odds could define this encounter.

    LjungskileLjungskile
    Form LLDLD
    League ranking xG #3xGA #13xT #6xP/match #7Points #11
    Key players
    • Vilmer TyrénFxG 0.31 · xT 0.15
    • Issaka SeiduLWxG 0.15 · xT 0.20
    • Lukas Lindholm CornerFxG 0.21 · xT 0.01
    NorrbyNorrby
    Form WLDLL
    League ranking xG #7xGA #14xT #15xP/match #3Points #12
    Key players
    • Julius JohanssonFxG 0.21 · xT 0.15
    • Azeez Temitope YusufFxG 0.28 · xT 0.00
    • Olle BacklundRWxG 0.06 · xT 0.19
    Final score
    21
    The model called the outcome
    Predicted probabilities: Ljungskile 43% · Draw 25% · Norrby 32%

    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 - Ljungskile SKBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 4,94fair 6,33-22 %
    Miss
    Matchresultat - Norrby IFBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 7,67fair 12,45-38 %
    Miss

    Match prediction: LjungskileNorrby

    Predicted score matrix

    Norrby
    Ljungskile
    0
    1
    2
    3
    4+
    0
    0–05.3%
    0–15.9%
    0–23.9%
    0–31.6%
    0–4+0.7%
    1
    1–08.4%
    1–111.2%
    1–26.8%
    1–32.8%
    1–4+1.2%
    2
    2–07.7%
    2–19.5%
    2–25.9%
    2–32.5%
    2–4+1.0%
    3
    3–04.5%
    3–15.6%
    3–23.5%
    3–31.4%
    3–4+0.6%
    4+
    4+–02.9%
    4+–13.6%
    4+–22.2%
    4+–30.9%
    4+–4+0.4%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-111%
    2. 2.2-110%
    3. 3.1-08%
    4. 4.2-08%
    5. 5.1-27%
    Expected goals
    1,751,25
    Both teams to score
    59%

    Over/under goals

    Expected goals: 3,0
    Under 2,542%
    @2.38EV+1%
    Over 2,558%
    @1.57

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Double chance Ljungskile or draw (1X)73%
    • Over 1.5 goals80%

    Combined probability

    59%

    Fair odds

    1.69

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

    02 · 3 legs

    Balanced

    • Double chance Ljungskile or draw (1X)73%
    • Over 2.5 goals58%
    • Lukas Lindholm Corner to score29%

    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 score59%
    • Over 2.5 goals58%
    • Lukas Lindholm Corner to score29%
    • Filip Ambroz to be booked19%

    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 · Norrby32% probability@3.40Paddy PowerEV+9%reference odds
    • 2 · Norrby32% probability@3.37BetsafeEV+8%reference odds
    • 2 · Norrby32% probability@3.37BetssonEV+8%reference odds
    Bookmaker1 · LjungskileX2 · Norrby
    Betsafe2.053.60
    EV+ 8%
    3.37
    Betsson2.053.60
    EV+ 8%
    3.37
    Nordicbet2.053.60
    EV+ 8%
    3.37
    Paddy Power1.913.70
    EV+ 9%
    3.40
    Pinnacle2.013.89
    EV+ 8%
    3.37

    Odds updated 9 Sept, 16:31

    Odds movement

    1-5 %
    53 %43 %

    2.112.01

    X+5 %
    30 %20 %

    3.713.89

    2+8 %
    33 %23 %

    3.113.37

    Pinnacle · 15 recorded price levels · 05/09/2026 → 09/09/2026 · fixed scale 10 percentage points

    Statistics

    Head-to-head

    1 matches
    Ljungskile 0Draw 0Norrby 1
    Goals: 12 (⌀ 3)

    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
    Norrby
    When goals are scored and conceded 2026
    Ljungskile (2930)
    Norrby (2631)
    Pass networks

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

    Ljungskile
    Filip Ambroz: 243 passningar, xT 1.15AmbrozIvan Maric: 226 passningar, xT 0.36MaricGideon Mensah: 178 passningar, xT 0.2MensahDaniel Lagerlöf: 164 passningar, xT 0.62LagerlöfDaniel Ljung: 153 passningar, xT 0.61LjungGustav Johanströmmer Hedin: 130 passningar, xT 0.22HedinMehmet Uzel: 124 passningar, xT 0.4UzelEmilio Reljanovic: 119 passningar, xT 0.77ReljanovicVilmer Tyrén: 93 passningar, xT 0.43TyrénLukas Eriksson: 87 passningar, xT 0.28ErikssonElton Hedström: 45 passningar, xT 0.26Hedström
    Norrby
    Vidar Svendsén: 254 passningar, xT 0.37SvendsénJoel Hjalmar: 211 passningar, xT 0.9HjalmarTure Spendler: 182 passningar, xT 2.02SpendlerCharlie Axede: 156 passningar, xT 0.41AxedeJohannes Engvall: 155 passningar, xT 0.39EngvallSebastian Banozic: 123 passningar, xT 0.34BanozicJulius Johansson: 104 passningar, xT 0.56JohanssonOlle Backlund: 77 passningar, xT 0.61BacklundAzeez Temitope Yusuf: 73 passningar, xT -0.01YusufJamie Bichis: 52 passningar, xT 0.04BichisKevin Liimatainen: 44 passningar, xT -0.12Liimatainen
    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
    Filip Ambroz: 243 passningar, xT 1.15AmbrozIvan Maric: 226 passningar, xT 0.36MaricGideon Mensah: 178 passningar, xT 0.2MensahDaniel Lagerlöf: 164 passningar, xT 0.62LagerlöfDaniel Ljung: 153 passningar, xT 0.61LjungGustav Johanströmmer Hedin: 130 passningar, xT 0.22HedinMehmet Uzel: 124 passningar, xT 0.4UzelEmilio Reljanovic: 119 passningar, xT 0.77ReljanovicVilmer Tyrén: 93 passningar, xT 0.43TyrénLukas Eriksson: 87 passningar, xT 0.28ErikssonElton Hedström: 45 passningar, xT 0.26Hedström
    Norrby
    Vidar Svendsén: 254 passningar, xT 0.37SvendsénJoel Hjalmar: 211 passningar, xT 0.9HjalmarTure Spendler: 182 passningar, xT 2.02SpendlerCharlie Axede: 156 passningar, xT 0.41AxedeJohannes Engvall: 155 passningar, xT 0.39EngvallSebastian Banozic: 123 passningar, xT 0.34BanozicJulius Johansson: 104 passningar, xT 0.56JohanssonOlle Backlund: 77 passningar, xT 0.61BacklundAzeez Temitope Yusuf: 73 passningar, xT -0.01YusufJamie Bichis: 52 passningar, xT 0.04BichisKevin Liimatainen: 44 passningar, xT -0.12Liimatainen

    The teams in numbers

    PerformanceLjungskileNorrby
    Points2523
    xPoints30.334.5
    xG per match1.51.4
    xGA per match1.41.5
    xG within 8s of winning the ball0.270.28
    xGA within 8s of losing the ball0.30.26
    Playing styleLjungskileNorrby
    Build-up efficiency0.360.35
    Field tilt0.470.36
    xT per match1.61.3
    xTA per match1.51.7
    Won balls, offensive half3230
    Pressing intensity0.550.55
    Pressing efficiency0.280.25
    Pressing efficiency, offensive half0.280.25
    Entries into the box per match1712
    Entries into the box against1518
    Pass completion %0.760.73
    Pass completion % under pressure0.70.67
    Passes per match337293
    Passes against per match349465
    Switches of play per match18.919.4
    Long balls per match3631
    Set piecesLjungskileNorrby
    xG from free kicks0.170.14
    Corners per match5.74.9
    Corners against per match5.45.7
    xG per corner0.030.03
    xGA per corner against0.030.02
    First touch, offensive corners %0.40.35
    First touch, defensive corners %0.630.46
    OtherLjungskileNorrby
    Throw-in control0.540.44
    The goalkeepersLukas Eriksson (Ljungskile)Sebastian Banozic (Norrby)
    Saves7967
    Save %73%68%
    xG prevented58%50%
    Claims131 (95%)137 (93%)

    Frequently asked questions

    Who wins Ljungskile vs Norrby according to our model?

    The model gives Ljungskile a 43% win probability. Full 1X2 picture: Ljungskile 43%, draw 25%, Norrby 32%.

    What is the most likely scoreline?

    The model's most likely final score is 1-1 at 11% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 58% and under at 42%.

    Will both teams score?

    The probability of both teams scoring is 59% 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.