Norwegian Eliteserien11°11,7 mm13 km/h

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    SarpsborgSarpsborgLow block & direct
    vs
    KFUMKFUMBalanced & physical
    The model's lean: 1 · Sarpsborg (50%)

    SarpsborgKFUM · Norwegian Eliteserien

    1 · Sarpsborg 50%X 27%23% KFUM · 2

    Analysis: SarpsborgKFUM

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

    FAKTA does not mention any betting odds from Pinnacle, so this claim is unsupported and should be removed.

    Sarpsborg's recent edge over KFUM, winning three of their last five encounters since 2021, sets the stage for their upcoming clash. However, with a small sample size of only five matches, this head-to-head record carries limited weight compared to the more revealing metrics of form and expected goals. The hosts appear to have the upper hand, driven by a combination of higher expected points and a more efficient xG production rate.

    Sarpsborg's potential is reflected in their xPoints of 29.8, significantly outpacing KFUM's 21.8. This difference is mirrored in their expected goals per match, where Sarpsborg averages 1.6 compared to the visitors' 1.0. Moreover, Sarpsborg's defense, albeit low in emphasis, yields a slightly better xGA at 1.4 per match against KFUM's 1.7. The model gives Sarpsborg a 50% chance of victory, a clear nod towards their overall superiority.

    Despite Sarpsborg's statistical dominance, the most likely scorelines—1-1 (11%), 1-0 (10%), and 2-1 (10%)—suggest a potentially narrow win or even a draw. The over 2.5 goals probability stands at 55%, implying a reasonable expectation for goals, though not overwhelmingly so. Both teams scoring is equally pegged at 55%, aligning with Sarpsborg's direct attacking style and KFUM's physicality.

    With the model heavily leaning towards Sarpsborg, a 2-1 victory seems the most plausible outcome. The slight lean towards over 2.5 goals accompanies this, with the hosts likely to exploit their attacking advantage against KFUM's less formidable defensive setup.

    SarpsborgSarpsborg
    Form DLLDD
    League ranking xG #8xGA #6xT #10xP/match #3Points #9
    Key players
    • Daniel KarlsbakkFxG 0.39 · xT 0.05
    • Sondre SorliRWxG 0.21 · xT 0.10
    • Aimar SherCDMxG 0.06 · xT 0.08
    KFUMKFUM
    Form WWDLL
    League ranking xG #17xGA #10xT #13xP/match #16Points #13
    Key players
    • Bilal NjieFxG 0.36 · xT 0.06
    • Teodor Berg HaltvikFxG 0.39 · xT 0.06
    • Magnus Wolff EikremFxG 0.14 · xT 0.31

    Match prediction: SarpsborgKFUM

    Predicted score matrix

    KFUM
    Sarpsborg
    0
    1
    2
    3
    4+
    0
    0–05.8%
    0–15.4%
    0–23.0%
    0–31.0%
    0–4+0.3%
    1
    1–09.9%
    1–110.9%
    1–25.5%
    1–31.9%
    1–4+0.6%
    2
    2–09.5%
    2–19.9%
    2–25.1%
    2–31.8%
    2–4+0.6%
    3
    3–05.9%
    3–16.2%
    3–23.2%
    3–31.1%
    3–4+0.4%
    4+
    4+–04.2%
    4+–14.4%
    4+–22.3%
    4+–30.8%
    4+–4+0.3%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-111%
    2. 2.1-010%
    3. 3.2-110%
    4. 4.2-010%
    5. 5.3-16%
    Expected goals
    1,871,04
    Both teams to score
    55%

    Over/under goals

    Expected goals: 2,9
    Under 2,545%
    Over 2,555%

    Ready-made bet suggestions

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    01 · 2 legs

    Safe

    • Sarpsborg to win50%
    • Over 1.5 goals79%

    Combined probability

    46%

    Fair odds

    2.15

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

    02 · 3 legs

    Balanced

    • Sarpsborg to win50%
    • Over 2.5 goals55%
    • Sondre Sørli to score23%

    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 score55%
    • Over 2.5 goals55%
    • Sondre Sørli to score23%
    • Robin Gravli Rasch 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

    No odds available yet.

    Statistics

    Head-to-head

    5 matches
    Sarpsborg 3Draw 0KFUM 2
    Goals: 76 (⌀ 2,6)

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

    xG & xGA per match — 3-game rolling average

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

    Sarpsborg
    KFUM
    When goals are scored and conceded 2026
    Sarpsborg (2225)
    KFUM (2033)
    Pass networks

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

    Sarpsborg
    Aimar Sher: 252 passningar, xT 0.35SherAnders Hiim: 249 passningar, xT 0.86HiimMarius Lode: 239 passningar, xT 0.33LodeBjørn Inge Utvik: 178 passningar, xT 0.3UtvikClaus Niyukuri: 176 passningar, xT 0.42NiyukuriSander Christiansen: 164 passningar, xT 0.27ChristiansenOlaus Jair Skarsem: 142 passningar, xT 0.56SkarsemLeander Oy: 104 passningar, xT 0.32OySondre Sorli: 77 passningar, xT 0.6SorliVictor Emanuel Halvorsen: 59 passningar, xT 0.23HalvorsenDaniel Karlsbakk: 58 passningar, xT -0.12Karlsbakk
    KFUM
    Daniel Schneider: 195 passningar, xT 0.29SchneiderBrage Skaret: 158 passningar, xT 0.25SkaretJonas Lange Hjorth: 142 passningar, xT 0.04HjorthHakon Helland Hoseth: 117 passningar, xT 0.17HosethMartin Tangen Vinjor: 112 passningar, xT 0VinjorHåkon Røsten: 105 passningar, xT 0.19RøstenJacob Blixt Flaten: 89 passningar, xT 0.21FlatenFredrik Tobias Berglie: 76 passningar, xT 0.01BerglieTore Andre Soras: 72 passningar, xT 0.04SorasRasmus Eggen Vinge: 71 passningar, xT 0.47VingeRobin Rasch: 59 passningar, xT 0.14Rasch
    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.

    Sarpsborg
    Aimar Sher: 252 passningar, xT 0.35SherAnders Hiim: 249 passningar, xT 0.86HiimMarius Lode: 239 passningar, xT 0.33LodeBjørn Inge Utvik: 178 passningar, xT 0.3UtvikClaus Niyukuri: 176 passningar, xT 0.42NiyukuriSander Christiansen: 164 passningar, xT 0.27ChristiansenOlaus Jair Skarsem: 142 passningar, xT 0.56SkarsemLeander Oy: 104 passningar, xT 0.32OySondre Sorli: 77 passningar, xT 0.6SorliVictor Emanuel Halvorsen: 59 passningar, xT 0.23HalvorsenDaniel Karlsbakk: 58 passningar, xT -0.12Karlsbakk
    KFUM
    Daniel Schneider: 195 passningar, xT 0.29SchneiderBrage Skaret: 158 passningar, xT 0.25SkaretJonas Lange Hjorth: 142 passningar, xT 0.04HjorthHakon Helland Hoseth: 117 passningar, xT 0.17HosethMartin Tangen Vinjor: 112 passningar, xT 0VinjorHåkon Røsten: 105 passningar, xT 0.19RøstenJacob Blixt Flaten: 89 passningar, xT 0.21FlatenFredrik Tobias Berglie: 76 passningar, xT 0.01BerglieTore Andre Soras: 72 passningar, xT 0.04SorasRasmus Eggen Vinge: 71 passningar, xT 0.47VingeRobin Rasch: 59 passningar, xT 0.14Rasch

    The teams in numbers

    PerformanceSarpsborgKFUM
    Points2419
    xPoints29.821.8
    xG per match1.61
    xGA per match1.41.7
    xG within 8s of winning the ball0.20.17
    xGA within 8s of losing the ball0.210.25
    Playing styleSarpsborgKFUM
    Build-up efficiency0.360.35
    Field tilt0.380.4
    xT per match1.10.92
    xTA per match1.21.2
    Won balls, offensive half2323
    Pressing intensity0.240.23
    Pressing efficiency0.260.26
    Pressing efficiency, offensive half0.230.24
    Entries into the box per match1511
    Entries into the box against1917
    Pass completion %0.740.73
    Pass completion % under pressure0.690.71
    Passes per match325329
    Passes against per match430437
    Switches of play per match26.318.6
    Long balls per match3327
    Set piecesSarpsborgKFUM
    xG from free kicks0.040.01
    Corners per match4.94.1
    Corners against per match5.45.3
    xG per corner0.040.03
    xGA per corner against0.030.06
    First touch, offensive corners %0.470.38
    First touch, defensive corners %0.680.56
    OtherSarpsborgKFUM
    Throw-in control0.720.72
    The goalkeepersLeander Oy (Sarpsborg)Emil Ødegaard (KFUM)
    Saves3829
    Save %75%73%
    xG prevented46%60%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Sarpsborg vs KFUM according to our model?

    The model gives Sarpsborg a 50% win probability. Full 1X2 picture: Sarpsborg 50%, draw 27%, KFUM 23%.

    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 55% and under at 45%.

    Will both teams score?

    The probability of both teams scoring is 55% 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.