Norwegian Eliteserien4°0,6 mm9 km/h

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    KFUMKFUMBalanced & physical
    vs
    VålerengaVålerengaBalanced & physical
    The model's lean: 2 · Vålerenga (44%)

    KFUM vs Vålerenga · Norwegian Eliteserien

    1 · KFUM 29%X 27%44% Vålerenga · 2

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    Analysis: KFUM – Vålerenga

    Anna Karlsson · · A data-driven preview · How the predictions work

    TEXT: A subtle clash of form and projection shapes the upcoming battle between KFUM and Vålerenga. The visitors hold a clear edge with a 44% probability of victory according to model predictions, with the most likely scoreline being a 1-1 draw. Yet, KFUM's slight points lead in the standings (25 to 23) hints at their knack for converting chances when it matters. It's a delicate balance between the raw numbers and the tangible results these teams have mustered.

    KFUM's physical style, while balanced, hasn't translated into robust defensive metrics, conceding an average of 1.8 goals per game. Contrarily, Vålerenga’s defensive solidity is marginally better at 1.6 goals against per match. With rain expected to dampen the turf, both sides may find it tricky to maintain their usual physicality, which often dictates their gameplay. Nonetheless, these conditions have already been factored into the model’s expectations.

    Head-to-head, it's a small sample: just three meetings since 2021, with Vålerenga unbeaten. This history might suggest a psychological edge but pales against the season-long data where the xPoints favor Vålerenga 29 to 25. The scoring potential tips towards the visitors, too, with an expected 1.6 goals per match against KFUM's 1.1, adding weight to the probability of both teams finding the net, currently at 61%.

    Despite the balanced and physical nature of these sides, the over 2.5 goals probability sits at a tempting 59%. In a match poised on a knife-edge, Vålerenga's form and tactical edge suggest they might just edge it.

    KFUMKFUM
    Form DLLWW
    League ranking xG #16xGA #10xT #14xP/match #14Points #10
    Key players
    • Teodor Berg HaltvikFxG 0.37 · xT 0.07
    • Magnus Wolff EikremFxG 0.14 · xT 0.29
    • Bilal NjieLWxG 0.34 · xT 0.08
    VålerengaVålerenga
    Form DLDLD
    League ranking xG #7xGA #9xT #5xP/match #7Points #12
    Key players
    • Henrik BjordalRWxG 0.20 · xT 0.18
    • Mathias GrundetjernFxG 0.40 · xT 0.04
    • Lucas Janus Ravn-HarenLWxG 0.34 · xT 0.11

    Match prediction: KFUM – Vålerenga

    Predicted score matrix

    Vålerenga →
    KFUM →
    0
    1
    2
    3
    4+
    0
    0–05.0%
    0–17.8%
    0–27.1%
    0–34.1%
    0–4+2.7%
    1
    1–05.8%
    1–111.1%
    1–29.4%
    1–35.5%
    1–4+3.5%
    2
    2–04.1%
    2–17.1%
    2–26.2%
    2–33.6%
    2–4+2.3%
    3
    3–01.8%
    3–13.1%
    3–22.7%
    3–31.6%
    3–4+1.0%
    4+
    4+–00.8%
    4+–11.4%
    4+–21.2%
    4+–30.7%
    4+–4+0.5%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-111%
    2. 2.1-29%
    3. 3.0-18%
    4. 4.2-17%
    5. 5.0-27%
    Expected goals
    1,32–1,74
    Both teams to score
    61%

    Over/under goals

    Expected goals: 3,1
    Under 2,541%
    –
    Over 2,559%
    –

    Ready-made bet suggestions

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    01 · 2 legs

    Safe

    • Double chance Vålerenga or draw (X2)71%
    • Over 1.5 goals81%

    Combined probability

    58%

    Fair odds

    1.71

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

    02 · 3 legs

    Balanced

    • Double chance Vålerenga or draw (X2)71%
    • Over 2.5 goals59%
    • Mathias Grundetjern to score30%

    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 goals59%
    • Mathias Grundetjern to score30%
    • Magnus Hee Westergaard to be booked20%

    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

    No odds available yet.

    Statistics

    Head-to-head

    3 matches
    KFUM 0Draw 2Vålerenga 1
    Goals: 3–4 (⌀ 2,3)

    Head-to-head based on Eliteserien data since 2021.

    xG & xGA per match — 3-game rolling average

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

    KFUM
    Vålerenga
    When goals are scored and conceded — 2026
    KFUM (25–35)
    Vålerenga (34–43)
    Pass networks

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

    KFUM
    Brage Skaret: 180 passningar, xT 0.28SkaretHåkon Røsten: 150 passningar, xT 0.28RøstenFredrik Tobias Berglie: 134 passningar, xT 0.14BerglieJonas Lange Hjorth: 132 passningar, xT 0.1HjorthMartin Tangen Vinjor: 117 passningar, xT 0.02VinjorHakon Helland Hoseth: 112 passningar, xT 0.15HosethDaniel Schneider: 100 passningar, xT 0.15SchneiderJacob Blixt Flaten: 89 passningar, xT 0.21FlatenEirik Saunes: 87 passningar, xT 0.21SaunesEmil Ødegaard: 61 passningar, xT 0.12ØdegaardBilal Njie: 54 passningar, xT 0.44Njie
    Vålerenga
    Aaron Kiil Olsen: 320 passningar, xT 0.79OlsenKolbeinn Birgir Finnsson: 256 passningar, xT 1.1FinnssonCarl Lange: 247 passningar, xT 0.4LangeSebastian Jarl: 237 passningar, xT 0.33JarlHakon Sjatil: 235 passningar, xT 1.13SjatilMagnus Hee Westergaard: 160 passningar, xT -0.11WestergaardOscar Thore Hedvall: 129 passningar, xT 0.29HedvallIvan Tarek Fjellstad Näsberg: 88 passningar, xT 0.12NäsbergGhayas Zahid: 82 passningar, xT 0.27ZahidLucas Janus Ravn-Haren: 82 passningar, xT 0.85Ravn-HarenPetter Strand: 80 passningar, xT 0.09Strand
    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.

    KFUM
    Brage Skaret: 180 passningar, xT 0.28SkaretHåkon Røsten: 150 passningar, xT 0.28RøstenFredrik Tobias Berglie: 134 passningar, xT 0.14BerglieJonas Lange Hjorth: 132 passningar, xT 0.1HjorthMartin Tangen Vinjor: 117 passningar, xT 0.02VinjorHakon Helland Hoseth: 112 passningar, xT 0.15HosethDaniel Schneider: 100 passningar, xT 0.15SchneiderJacob Blixt Flaten: 89 passningar, xT 0.21FlatenEirik Saunes: 87 passningar, xT 0.21SaunesEmil Ødegaard: 61 passningar, xT 0.12ØdegaardBilal Njie: 54 passningar, xT 0.44Njie
    Vålerenga
    Aaron Kiil Olsen: 320 passningar, xT 0.79OlsenKolbeinn Birgir Finnsson: 256 passningar, xT 1.1FinnssonCarl Lange: 247 passningar, xT 0.4LangeSebastian Jarl: 237 passningar, xT 0.33JarlHakon Sjatil: 235 passningar, xT 1.13SjatilMagnus Hee Westergaard: 160 passningar, xT -0.11WestergaardOscar Thore Hedvall: 129 passningar, xT 0.29HedvallIvan Tarek Fjellstad Näsberg: 88 passningar, xT 0.12NäsbergGhayas Zahid: 82 passningar, xT 0.27ZahidLucas Janus Ravn-Haren: 82 passningar, xT 0.85Ravn-HarenPetter Strand: 80 passningar, xT 0.09Strand

    The teams in numbers

    PerformanceKFUMVålerenga
    Points2523
    xPoints2529
    xG per match1.11.6
    xGA per match1.81.6
    xG within 8s of winning the ball0.20.3
    xGA within 8s of losing the ball0.250.29
    Playing styleKFUMVålerenga
    Build-up efficiency0.350.35
    Field tilt0.40.52
    xT per match0.91.2
    xTA per match1.31.1
    Won balls, offensive half2326
    Pressing intensity0.230.23
    Pressing efficiency0.270.3
    Pressing efficiency, offensive half0.250.29
    Entries into the box per match1216
    Entries into the box against1716
    Pass completion %0.720.75
    Pass completion % under pressure0.70.7
    Passes per match326373
    Passes against per match441379
    Switches of play per match19.324.7
    Long balls per match2833
    Set piecesKFUMVålerenga
    xG from free kicks0.010.01
    Corners per match4.16.8
    Corners against per match5.55.7
    xG per corner0.020.03
    xGA per corner against0.050.03
    First touch, offensive corners %0.340.41
    First touch, defensive corners %0.530.57
    OtherKFUMVålerenga
    Throw-in control0.720.73
    The goalkeepersEmil Ødegaard (KFUM)Oscar Thore Hedvall (Vålerenga)
    Saves3668
    Save %74%61%
    xG prevented57%46%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins KFUM vs Vålerenga according to our model?

    The model gives Vålerenga a 44% win probability. Full 1X2 picture: KFUM 29%, draw 27%, Vålerenga 44%.

    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 59% and under at 41%.

    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.

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