Danish SuperligaCeres Park, Aarhus14°0,3 mm29 km/h

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    AGFAGFCounter-attacks & crosses
    vs
    OdenseOdensePossession & high press
    The model's lean: 1 · AGF (43%)
    Limited dataThe model has thin or uncertain data for this match — the forecast may be unreliable and the match is excluded from our value lists.

    AGFOdense · Danish Superliga

    1 · AGF 43%X 27%30% Odense · 2

    Analysis: AGFOdense

    Erik Lindberg · · Written from the model's numbers · How the predictions work

    Two games are hardly enough to paint a complete picture, but AGF Aarhus holds a perfect head-to-head record against Odense Boldklub since 2022. Yet, don't let this minor sample distract you from the broader narrative: Odense Boldklub has demonstrated a sharper edge in both points and expected metrics this season. Their 3-point haul eclipses AGF’s modest 2, and their expected points tally of 5.9 outstrips their hosts' 3.9. In a match tinged with Danish drizzle, goals may just splash down like rain.

    AGF Aarhus, despite their penchant for a counter-attacking style, will need to be wary of Odense Boldklub's high press and possession-based game. The expected goals model pegs AGF at 1.64, but Odense isn’t far behind at 1.39. Both teams show a capacity to find the back of the net, a notion supported by a 61% chance of both sides scoring. The over 2.5 goals market is leaning towards a favourable 58% — despite the weather's dampening potential.

    AGF Aarhus may enter this match with the model nudging them as slight favourites at 43%, but Odense Boldklub's 30% chance can't be discounted, particularly given their superior xG and xGA figures this season. Expect AGF to test Odense’s defense with crosses and counter-attacks, though it’s Odense who might just nick the advantage, leveraging their tighter defensive setup — a 1.1 xGA per match tells a compelling story.

    The most likely scorelines are tantalisingly close: 1-1 at 11% and 2-1 to AGF at 9% — suggesting a tight contest. However, the value bet lies in a nod to Odense Boldklub sneaking a win. The bookmaker odds on a 1-2 scoreline, valued at 8%, could offer an edge for the bold punter. With AGF's tendency to concede matched by Odense's scoring ability, backing an Odense victory at the right odds might be the shrewd move.

    AGFAGF
    Form WWDDL
    League ranking xG #4xGA #11xT #6xP/match #6Points #10
    Key players
    • Gift LinksRWxG 0.21 · xT 0.10
    • Kristian ArnstadFxG 0.56 · xT 0.09
    • Frederik TingagerCBxG 0.07 · xT 0.27
    OdenseOdense
    Form LLWLL
    League ranking xG #3xGA #4xT #2xP/match #4Points #9
    Key players
    • Fiete ArpRWxG 0.32 · xT 0.27
    • Rasmus FalkCMxG 0.12 · xT 0.16
    • James GomezCBxG 0.01 · xT 0.11

    Match prediction: AGFOdense

    Predicted score matrix

    Odense
    AGF
    0
    1
    2
    3
    4+
    0
    0–05.2%
    0–16.4%
    0–24.7%
    0–32.2%
    0–4+1.0%
    1
    1–07.6%
    1–111.3%
    1–27.7%
    1–33.6%
    1–4+1.7%
    2
    2–06.5%
    2–19.0%
    2–26.3%
    2–32.9%
    2–4+1.4%
    3
    3–03.5%
    3–14.9%
    3–23.4%
    3–31.6%
    3–4+0.8%
    4+
    4+–02.1%
    4+–12.9%
    4+–22.0%
    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. 2.2-19%
    3. 3.1-28%
    4. 4.1-08%
    5. 5.2-06%
    Expected goals
    1,641,39
    Both teams to score
    61%

    Over/under goals

    Expected goals: 3,0
    Under 2,542%
    Over 2,558%

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Double chance AGF or draw (1X)68%
    • Over 1.5 goals81%

    Combined probability

    55%

    Fair odds

    1.82

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

    02 · 3 legs

    Balanced

    • Double chance AGF or draw (1X)68%
    • Over 2.5 goals58%
    • Kristian Fredrik Malt Arnstad to score28%

    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 goals58%
    • Kristian Fredrik Malt Arnstad to score28%
    • Julius Berthel Askou Harvey 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

    No odds available yet.

    Statistics

    Head-to-head

    2 matches
    AGF 2Draw 0Odense 0
    Goals: 72 (⌀ 4,5)

    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).

    AGF
    Odense
    When goals are scored and conceded 2026
    AGF (45)
    Odense (24)
    Pass networks

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

    AGF
    Mouhammade Camara: 110 passningar, xT 0.13CamaraKristian Arnstad: 109 passningar, xT 0.18ArnstadGift Links: 92 passningar, xT 0.16LinksJacob Andersen: 90 passningar, xT 0.1AndersenEric Kahl: 85 passningar, xT 0.19KahlJesper Hansen: 62 passningar, xT 0.01HansenFrederik Tingager: 60 passningar, xT 0.3TingagerSebastian Jorgensen: 55 passningar, xT 0.19JorgensenFrederik Emmery: 54 passningar, xT 0.75EmmeryMagnus Nordengen Knudsen: 52 passningar, xT 0KnudsenMarkus Solbakken: 48 passningar, xT 0.08Solbakken
    Odense
    James Gomez: 258 passningar, xT 0.4GomezIsmahila Ouédraogo: 227 passningar, xT 0.32OuédraogoJulius Askou: 193 passningar, xT 0.52AskouMarcus Mccoy: 191 passningar, xT 0.46MccoyRasmus Falk: 161 passningar, xT 0.31FalkJakob Bonde: 129 passningar, xT 0.12BondeUlrik Yttergård Jenssen: 117 passningar, xT 0.22JenssenViljar Myhra: 80 passningar, xT 0.16MyhraTopi Keskinen: 79 passningar, xT 0.41KeskinenAdam Sorensen: 74 passningar, xT 0.47SorensenPeter Nysted Therkildsen: 69 passningar, xT 0.31Therkildsen
    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.

    AGF
    Mouhammade Camara: 110 passningar, xT 0.13CamaraKristian Arnstad: 109 passningar, xT 0.18ArnstadGift Links: 92 passningar, xT 0.16LinksJacob Andersen: 90 passningar, xT 0.1AndersenEric Kahl: 85 passningar, xT 0.19KahlJesper Hansen: 62 passningar, xT 0.01HansenFrederik Tingager: 60 passningar, xT 0.3TingagerSebastian Jorgensen: 55 passningar, xT 0.19JorgensenFrederik Emmery: 54 passningar, xT 0.75EmmeryMagnus Nordengen Knudsen: 52 passningar, xT 0KnudsenMarkus Solbakken: 48 passningar, xT 0.08Solbakken
    Odense
    James Gomez: 258 passningar, xT 0.4GomezIsmahila Ouédraogo: 227 passningar, xT 0.32OuédraogoJulius Askou: 193 passningar, xT 0.52AskouMarcus Mccoy: 191 passningar, xT 0.46MccoyRasmus Falk: 161 passningar, xT 0.31FalkJakob Bonde: 129 passningar, xT 0.12BondeUlrik Yttergård Jenssen: 117 passningar, xT 0.22JenssenViljar Myhra: 80 passningar, xT 0.16MyhraTopi Keskinen: 79 passningar, xT 0.41KeskinenAdam Sorensen: 74 passningar, xT 0.47SorensenPeter Nysted Therkildsen: 69 passningar, xT 0.31Therkildsen

    The teams in numbers

    PerformanceAGFOdense
    Points23
    xPoints3.95.9
    xG per match1.61.7
    xGA per match1.61.1
    xG within 8s of winning the ball0.380.43
    xGA within 8s of losing the ball0.290.15
    Playing styleAGFOdense
    Build-up efficiency0.30.32
    Field tilt0.510.64
    xT per match11.5
    xTA per match10.88
    Won balls, offensive half2028
    Pressing intensity0.240.23
    Pressing efficiency0.290.28
    Pressing efficiency, offensive half0.210.23
    Entries into the box per match1614
    Entries into the box against1410
    Pass completion %0.750.79
    Pass completion % under pressure0.690.73
    Passes per match362456
    Passes against per match305362
    Switches of play per match23.125.4
    Long balls per match2727
    Set piecesAGFOdense
    xG from free kicks0.020.01
    Corners per match7.47
    Corners against per match4.46.3
    xG per corner0.040.02
    xGA per corner against0.040.01
    First touch, offensive corners %0.360.21
    First touch, defensive corners %0.540.6
    OtherAGFOdense
    Throw-in control0.750.71
    The goalkeepersMouhammade Camara (AGF)Viljar Myhra (Odense)
    Saves68
    Save %100%73%
    xG prevented100%69%
    Claims0 (0%)0 (0%)

    Frequently asked questions

    Who wins AGF vs Odense according to our model?

    The model gives AGF a 43% win probability. Full 1X2 picture: AGF 43%, draw 27%, Odense 30%.

    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 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.