Danish SuperligaJYSK park, Silkeborg16°0,1 mm17 km/h

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    SilkeborgSilkeborgBalanced & physical
    vs
    ViborgViborgCounter-attacks & crosses
    The model's lean: 2 · Viborg (50%)Best value by the model: Under 0,5 @ 19.00 (+11 %)

    SilkeborgViborg · Danish Superliga

    1 · Silkeborg 26%X 24%50% Viborg · 2

    Analysis: SilkeborgViborg

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

    Silkeborg's defensive frailties could be glaring as they take on Viborg, given that their expected goals against (xGA) sits at 1.6 per match compared to their guests' more conservative 1.2. While this suggests a vulnerability at the back for the hosts, Viborg's robust counter-attacking style is likely to exploit these weaknesses, especially given their superior xG at 1.5. Viborg has shown an ability to capitalize on such opportunities, accumulating 13 points compared to Silkeborg's 6.

    The head-to-head record since 2022 shows an even balance, each team claiming three wins, but with only six matches played, this small sample size should carry less weight than current form and statistical expectations. Viborg's ability to navigate through the rain might be crucial, as the expected 13.5 mm of rain could suppress scoring, but this is already considered in the model's numbers. The weather may further highlight the visitors' edge in xPoints (11.7 vs 9.0), reflecting their stronger overall form.

    Given the model’s probabilities, Viborg holds a 50% chance of claiming victory, with a likely scoreline of 1-2 or 0-1 favoring them. Silkeborg’s physicality may disrupt Viborg’s rhythm, but it’s unlikely to fully counteract the visitors' plan to penetrate through crosses and swift counters. The expected goals (Silkeborg 1.18 and Viborg 1.72) reinforce the likelihood of Viborg edging the matchup, even if Silkeborg manages to put up a defensive fight.

    For those seeking value bets, Silkeborg’s win at odds of 4.3 with Betsson and Nordicbet offers a 12% edge. However, with form and stats leaning towards Viborg, such a punt carries risk. A more grounded play lies in the under 2.5 goals at odds of 2.48 with Betsafe, offering an 11% value edge. Despite the fixture's historic high-scoring nature, the combination of rain and Viborg's defensive superiority may tilt the scales toward a more subdued affair.

    SilkeborgSilkeborg
    Form WLLDD
    League ranking xG #10xGA #10xT #11xP/match #7Points #9
    Key players
    • Mads LarsenCMxG 0.02 · xT 0.03
    • Callum MccowattCMxG 0.16 · xT 0.15
    • Villads WesthCMxG 0.05 · xT 0.04
    ViborgViborg
    Form DWWWL
    League ranking xG #6xGA #3xT #7xP/match #3Points #4
    Key players
    • Oliver BundgaardLWBxG 0.15 · xT 0.16
    • Charly NouckLWxG 0.26 · xT 0.21
    • Lukas Emil KirkegaardCBxG 0.05 · xT 0.15

    Match prediction: SilkeborgViborg

    Predicted score matrix

    Viborg
    Silkeborg
    0
    1
    2
    3
    4+
    0
    0–05.9%
    0–19.2%
    0–28.2%
    0–34.7%
    0–4+3.0%
    1
    1–06.2%
    1–111.5%
    1–29.6%
    1–35.5%
    1–4+3.5%
    2
    2–03.8%
    2–16.6%
    2–25.7%
    2–33.2%
    2–4+2.0%
    3
    3–01.5%
    3–12.6%
    3–22.2%
    3–31.3%
    3–4+0.8%
    4+
    4+–00.6%
    4+–11.0%
    4+–20.8%
    4+–30.5%
    4+–4+0.3%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-112%
    2. 2.1-210%
    3. 3.0-19%
    4. 4.0-28%
    5. 5.2-17%
    Expected goals
    1,181,72
    Both teams to score
    57%

    Over/under goals

    Expected goals: 2,9
    Under 2,545%
    @2.48EV+11%
    Over 2,555%
    @1.52

    Ready-made bet suggestions

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    01 · 2 legs

    Safe

    • Viborg to win50%
    • Over 1.5 goals79%

    Combined probability

    40%

    Fair odds

    2.47

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

    02 · 3 legs

    Balanced

    • Viborg to win50%
    • Over 2.5 goals55%
    • Dorian Junior Hanza Meha to score21%

    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 score57%
    • Over 2.5 goals55%
    • Malthe Emil Sogaard Hansen to score26%
    • Mads Larsen 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

    The model's value spots

    Bets where the model's probability beats what the odds imply (EV+).

    • Under 0.56% probability@19.00BetsafeEV+11%reference odds
    • Under 0.56% probability@19.00BetssonEV+11%reference odds
    • Under 0.56% probability@19.00NordicbetEV+11%reference odds
    Bookmaker1 · SilkeborgX2 · Viborg
    Betsafe3.653.851.88
    Betsson3.703.901.90
    Nordicbet3.703.901.90
    Pinnacle3.464.161.90

    Odds updated 11 Sept, 16:39

    Odds movement

    Market signal

    The market has moved clearly towards a Silkeborg win since 6 September — the odds have shortened from 3.88 to 3.46 (−11%).

    1-11 %
    28 %23 %

    3.883.46

    X-4 %
    25 %20 %

    4.334.16

    2+8 %
    54 %49 %

    1.761.90

    Pinnacle · 7 recorded price levels · 06/09/2026 → 11/09/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    6 matches
    Silkeborg 3Draw 0Viborg 3
    Goals: 1210 (⌀ 3,7)

    Head-to-head based on Danish Superliga data since 2022.

    Key facts

    • A high-scoring fixture: 3.7 goals per meeting on average.
    xG & xGA per match — 3-game rolling average

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

    Silkeborg
    Viborg
    When goals are scored and conceded 2026
    Silkeborg (711)
    Viborg (106)
    Pass networks

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

    Silkeborg
    Mads Larsen: 260 passningar, xT 0.17LarsenRobin Ostrom: 229 passningar, xT 0.15OstromVillads Westh: 201 passningar, xT 0.17WesthAlexander Madsen: 142 passningar, xT 0.22MadsenWilliam Lokke Moller: 140 passningar, xT 0.13MollerRami Al Hajj: 137 passningar, xT 0.37HajjJens Martin Gammelby: 119 passningar, xT 0.03GammelbyAske Andresen: 116 passningar, xT 0.03AndresenCallum Mccowatt: 104 passningar, xT 0.23MccowattOliver Ross: 68 passningar, xT 0.16RossLucas Thorst Riisgaard: 54 passningar, xT 0.93Riisgaard
    Viborg
    Zan Zaletel: 375 passningar, xT 0.48ZaletelLukas Emil Kirkegaard: 365 passningar, xT 0.79KirkegaardJeppe Gronning: 217 passningar, xT 0.28GronningOliver Bundgaard: 199 passningar, xT 0.91BundgaardKasper Hartly Kiilerich: 137 passningar, xT 0.08KiilerichAsker Beck: 120 passningar, xT 0.23BeckSami Jalal: 116 passningar, xT 0.87JalalSrdjan Kuzmic: 115 passningar, xT 0.17KuzmicHjalte Bidstrup: 70 passningar, xT 0.35BidstrupMads Sondergaard: 69 passningar, xT 0.23SondergaardCharly Nouck: 62 passningar, xT 1Nouck
    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.

    Silkeborg
    Mads Larsen: 260 passningar, xT 0.17LarsenRobin Ostrom: 229 passningar, xT 0.15OstromVillads Westh: 201 passningar, xT 0.17WesthAlexander Madsen: 142 passningar, xT 0.22MadsenWilliam Lokke Moller: 140 passningar, xT 0.13MollerRami Al Hajj: 137 passningar, xT 0.37HajjJens Martin Gammelby: 119 passningar, xT 0.03GammelbyAske Andresen: 116 passningar, xT 0.03AndresenCallum Mccowatt: 104 passningar, xT 0.23MccowattOliver Ross: 68 passningar, xT 0.16RossLucas Thorst Riisgaard: 54 passningar, xT 0.93Riisgaard
    Viborg
    Zan Zaletel: 375 passningar, xT 0.48ZaletelLukas Emil Kirkegaard: 365 passningar, xT 0.79KirkegaardJeppe Gronning: 217 passningar, xT 0.28GronningOliver Bundgaard: 199 passningar, xT 0.91BundgaardKasper Hartly Kiilerich: 137 passningar, xT 0.08KiilerichAsker Beck: 120 passningar, xT 0.23BeckSami Jalal: 116 passningar, xT 0.87JalalSrdjan Kuzmic: 115 passningar, xT 0.17KuzmicHjalte Bidstrup: 70 passningar, xT 0.35BidstrupMads Sondergaard: 69 passningar, xT 0.23SondergaardCharly Nouck: 62 passningar, xT 1Nouck

    The teams in numbers

    PerformanceSilkeborgViborg
    Points613
    xPoints911.7
    xG per match0.981.5
    xGA per match1.61.2
    xG within 8s of winning the ball0.220.26
    xGA within 8s of losing the ball0.350.22
    Playing styleSilkeborgViborg
    Build-up efficiency0.320.31
    Field tilt0.360.43
    xT per match0.641.1
    xTA per match1.40.89
    Won balls, offensive half1923
    Pressing intensity0.250.24
    Pressing efficiency0.240.27
    Pressing efficiency, offensive half0.190.22
    Entries into the box per match1215
    Entries into the box against1811
    Pass completion %0.790.78
    Pass completion % under pressure0.750.73
    Passes per match397381
    Passes against per match474403
    Switches of play per match14.831.9
    Long balls per match2132
    Set piecesSilkeborgViborg
    xG from free kicks0.040.03
    Corners per match4.74.9
    Corners against per match6.36.5
    xG per corner0.010.02
    xGA per corner against0.020.02
    First touch, offensive corners %0.610.24
    First touch, defensive corners %0.640.64
    OtherSilkeborgViborg
    Throw-in control0.690.66
    The goalkeepersAske Andresen (Silkeborg)Kasper Hartly Kiilerich (Viborg)
    Saves2321
    Save %68%78%
    xG prevented43%49%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Silkeborg vs Viborg according to our model?

    The model gives Viborg a 50% win probability. Full 1X2 picture: Silkeborg 26%, draw 24%, Viborg 50%.

    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 55% and under at 45%.

    Will both teams score?

    The probability of both teams scoring is 57% 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.