Danish SuperligaNature Energy Park, Odense16°28 km/h

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    OdenseOdensePossession & high press
    05
    FC KøbenhavnFC KøbenhavnPossession & high press
    The model's lean: 2 · FC København (43%)

    OdenseFC København · Danish Superliga

    1 · Odense 32%X 25%43% FC København · 2

    Analysis: OdenseFC København

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

    FAKTA: Model probabilities: Odense Boldklub 32%, draw 25%, FC Copenhagen 43%. Model lean: FC Copenhagen. Most likely scorelines: 1-1 (12%), 1-2 (9%), 0-1 (9%). Expected goals: Odense Boldklub 1.27, FC Copenhagen 1.64. Over 2.5 goals: 56%. Both teams to score: 58%. Playing style: Odense Boldklub profiles as possession & high press, FC Copenhagen as possession & high press. Head-to-head since 2022: 4 matches, Odense Boldklub 1W 2D 1L. Points: Odense Boldklub 5 vs FC Copenhagen 15 (edge FC Copenhagen) xPoints: Odense Boldklub 8.2 vs FC Copenhagen 9.2 (edge FC Copenhagen) xG per match: Odense Boldklub 1.6 vs FC Copenhagen 1.5 (edge Odense Boldklub) xGA per match: Odense Boldklub 1.4 vs FC Copenhagen 1.3 (edge FC Copenhagen)

    Corrected TEXT:

    Odense's stronghold, the midfield, is where this contest may well hinge. Despite trailing FC Copenhagen by ten points in the standings, the hosts have demonstrated a knack for maximizing possession and employing a high press — a style that mirrors their opponent's approach. Yet, the intricacies lie in the execution, where Odense's higher expected goals per match of 1.6 slightly edge out the visitors' 1.5, hinting at an intriguing offensive potential.

    Yet, the numbers don't lie about Copenhagen's edge. With a model probability giving them a 43% chance to take three points, it’s clear the visitors come in as favorites. Their superior xG Against (1.3 compared to Odense’s 1.4) suggests a defensive discipline that could prove decisive, especially on the road.

    Still, Odense won't be easily subdued. The small sample size of their head-to-head record since 2022 — four matches, with one win, two draws, and one loss for Odense — shows a fairly even affair overall, though Copenhagen holds a slight edge. This suggests that when these teams clash, few clear patterns emerge from the past — making current form and expected goals more telling.

    The forecast of over 2.5 goals occurring 56% of the time aligns with the attacking tendencies both teams exhibit. The likelihood of both teams scoring sits slightly higher at 58%, reflecting their shared proclivity for offensive action. So, while the statistical model leans towards a Copenhagen victory, Odense's potential to disrupt should not be discounted. A predicted 1-1 draw at 12% is the most probable outcome according to the model, closely followed by a 1-2 away win at 9%.

    While far from a certainty, the model’s lean toward FC Copenhagen suggests an edge worth considering in a match where fine margins and tactical execution will decide the victor.

    OdenseOdense
    Form WLLDD
    League ranking xG #4xGA #6xT #2xP/match #7Points #9
    Key players
    • Fiete ArpCAMxG 0.23 · xT 0.21
    • Noah GanausFxG 0.46 · xT 0.04
    • Jakob BondeCMxG 0.29 · xT 0.13
    FC KøbenhavnFC København
    Form WWLWW
    League ranking xG #6xGA #5xT #9xP/match #4Points #1
    Key players
    • Mohamed ElyounoussiRWxG 0.48 · xT 0.09
    • Robert SilvaLWxG 0.26 · xT 0.02
    • Marcos LopezLWBxG 0.03 · xT 0.18
    Final score
    05
    The model called the outcome
    Predicted probabilities: Odense 32% · Draw 25% · FC København 43%

    Match prediction: OdenseFC København

    Predicted score matrix

    FC København
    Odense
    0
    1
    2
    3
    4+
    0
    0–05.8%
    0–18.6%
    0–27.3%
    0–34.0%
    0–4+2.4%
    1
    1–06.6%
    1–111.7%
    1–29.3%
    1–35.1%
    1–4+3.0%
    2
    2–04.4%
    2–17.2%
    2–25.9%
    2–33.2%
    2–4+1.9%
    3
    3–01.9%
    3–13.0%
    3–22.5%
    3–31.4%
    3–4+0.8%
    4+
    4+–00.8%
    4+–11.3%
    4+–21.0%
    4+–30.6%
    4+–4+0.3%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-112%
    2. 2.1-29%
    3. 3.0-19%
    4. 4.0-27%
    5. 5.2-17%
    Expected goals
    1,271,64
    Both teams to score
    58%

    Over/under goals

    Expected goals: 2,9
    Under 2,544%
    Over 2,556%

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Double chance FC København or draw (X2)71%
    • Over 1.5 goals79%

    Combined probability

    56%

    Fair odds

    1.77

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

    02 · 3 legs

    Balanced

    • Double chance FC København or draw (X2)71%
    • Over 2.5 goals56%
    • Andreas Evald Cornelius to score26%

    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 score58%
    • Over 2.5 goals56%
    • Noah Ganaus to score26%
    • Wandepanga Ismahila Ouédraogo to be booked22%

    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

    4 matches
    Odense 1Draw 2FC København 1
    Goals: 66 (⌀ 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).

    Odense
    FC København
    When goals are scored and conceded 2026
    Odense (57)
    FC København (158)
    Pass networks

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

    Odense
    James Gomez: 277 passningar, xT 0.38GomezJulius Askou: 253 passningar, xT 0.63AskouRasmus Falk: 252 passningar, xT 0.53FalkIsmahila Ouédraogo: 239 passningar, xT 0.31OuédraogoMarcus Mccoy: 179 passningar, xT 0.38MccoyViljar Myhra: 139 passningar, xT 0.25MyhraUlrik Yttergård Jenssen: 138 passningar, xT 0.21JenssenPeter Nysted Therkildsen: 95 passningar, xT 0.41TherkildsenJakob Bonde: 90 passningar, xT 0.04BondeTopi Keskinen: 82 passningar, xT 0.56KeskinenAdam Sorensen: 63 passningar, xT 0.44Sorensen
    FC København
    Felix Olof Allan Nelson Beijmo: 324 passningar, xT 0.18BeijmoGabriel Pereira: 246 passningar, xT 0.35PereiraWilliam Clem: 167 passningar, xT 0.08ClemMarcos Lopez: 163 passningar, xT 0.65LopezAsger Strømgaard Sørensen: 159 passningar, xT 0.2SørensenJunnosuke Suzuki: 144 passningar, xT 0.18SuzukiMohamed Elyounoussi: 143 passningar, xT 0.28ElyounoussiThomas Delaney: 139 passningar, xT 0.11DelaneyMads Emil Madsen: 109 passningar, xT 0.43MadsenAlex Král: 94 passningar, xT 0.24KrálRobert Silva: 90 passningar, xT 0.03Silva
    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.

    Odense
    James Gomez: 277 passningar, xT 0.38GomezJulius Askou: 253 passningar, xT 0.63AskouRasmus Falk: 252 passningar, xT 0.53FalkIsmahila Ouédraogo: 239 passningar, xT 0.31OuédraogoMarcus Mccoy: 179 passningar, xT 0.38MccoyViljar Myhra: 139 passningar, xT 0.25MyhraUlrik Yttergård Jenssen: 138 passningar, xT 0.21JenssenPeter Nysted Therkildsen: 95 passningar, xT 0.41TherkildsenJakob Bonde: 90 passningar, xT 0.04BondeTopi Keskinen: 82 passningar, xT 0.56KeskinenAdam Sorensen: 63 passningar, xT 0.44Sorensen
    FC København
    Felix Olof Allan Nelson Beijmo: 324 passningar, xT 0.18BeijmoGabriel Pereira: 246 passningar, xT 0.35PereiraWilliam Clem: 167 passningar, xT 0.08ClemMarcos Lopez: 163 passningar, xT 0.65LopezAsger Strømgaard Sørensen: 159 passningar, xT 0.2SørensenJunnosuke Suzuki: 144 passningar, xT 0.18SuzukiMohamed Elyounoussi: 143 passningar, xT 0.28ElyounoussiThomas Delaney: 139 passningar, xT 0.11DelaneyMads Emil Madsen: 109 passningar, xT 0.43MadsenAlex Král: 94 passningar, xT 0.24KrálRobert Silva: 90 passningar, xT 0.03Silva

    The teams in numbers

    PerformanceOdenseFC København
    Points515
    xPoints8.29.2
    xG per match1.61.5
    xGA per match1.41.3
    xG within 8s of winning the ball0.310.37
    xGA within 8s of losing the ball0.230.34
    Playing styleOdenseFC København
    Build-up efficiency0.320.32
    Field tilt0.480.56
    xT per match1.40.82
    xTA per match1.10.92
    Won balls, offensive half2630
    Pressing intensity0.240.23
    Pressing efficiency0.280.27
    Pressing efficiency, offensive half0.250.25
    Entries into the box per match1311
    Entries into the box against1610
    Pass completion %0.780.79
    Pass completion % under pressure0.720.73
    Passes per match410431
    Passes against per match399392
    Switches of play per match25.131.2
    Long balls per match2933
    Set piecesOdenseFC København
    xG from free kicks0.020.01
    Corners per match5.74.7
    Corners against per match7.43.7
    xG per corner0.020.03
    xGA per corner against0.010.03
    First touch, offensive corners %0.210.46
    First touch, defensive corners %0.640.5
    OtherOdenseFC København
    Throw-in control0.710.73
    The goalkeepersViljar Myhra (Odense)Marcos Lopez (FC København)
    Saves117
    Save %65%100%
    xG prevented46%100%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Odense vs FC København according to our model?

    The model gives FC København a 43% win probability. Full 1X2 picture: Odense 32%, draw 25%, FC København 43%.

    What is the most likely scoreline?

    The model's most likely final score is 1-1 at 12% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 56% and under at 44%.

    Will both teams score?

    The probability of both teams scoring is 58% 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.