2. BundesligaBBBank Wildpark, Karlsruhe21°15 km/h

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    KarlsruheKarlsruhePossession control
    25
    WolfsburgWolfsburgPossession control
    The model's lean: 1 · Karlsruhe (39%)

    KarlsruheWolfsburg · 2. Bundesliga

    1 · Karlsruhe 39%X 26%35% Wolfsburg · 2

    Analysis: KarlsruheWolfsburg

    Marcus Johansson · · Analysis from the match model · How the predictions work

    Wolfsburg carries a statistical edge in xG per match heading into their clash with Karlsruhe, averaging 1.6 compared to Karlsruhe's 1.3. Despite this, the home side shows resilience in transition, producing an xG of 0.3 within 8 seconds of winning the ball, outperforming the visitors' 0.23. Karlsruhe's ability to exploit rapid counter-attacks could be a pivotal factor, particularly if Wolfsburg's possession control strategy leaves gaps at the back.

    Both teams favor a possession-based style, yet Karlsruhe's defensive numbers in rapid transition scenarios offer them a slight edge. The hosts only concede an xGA of 0.09 within 8 seconds of losing the ball, better than Wolfsburg’s 0.13. This suggests that if Karlsruhe can disrupt Wolfsburg's rhythm, they might have opportunities to strike on quick breaks. The match is likely to be a tactical battle of who can maintain possession while remaining defensively organized.

    The model leans towards Karlsruhe with a 39% win probability, slightly higher than Wolfsburg's 35%. Meanwhile, the likelihood of a draw sits at 26%, with a 1-1 scoreline as the most probable outcome (11%). Goals are expected, with a 60% chance of over 2.5 goals and a 62% likelihood that both teams will find the net. Still, the under 3.5 goals at odds of 1.7 with Betsson offers a tempting value proposition, given the model's 63% rating.

    For punters seeking an edge, the home win is intriguing. Available at 4.0 odds with both Betsson and Nordicbet, the model's 39% win probability suggests a 57% value edge. Considering Karlsruhe's strengths in quick transitions and defensive solidity, they might just edge this closely contested matchup, but the safer play could be the under 3.5 goals angle.

    KarlsruheKarlsruhe
    Form WDLWD
    League ranking xG #12xGA #1xT #14xP/match #3Points #3
    Key players
    • Moritz BroschinskiFxG 0.55 · xT -0.26
    • Marvin WanitzekCAMxG 0.24 · xT 0.13
    • Rafael Pinto PedrosaRWxG 0.09 · xT 0.08
    WolfsburgWolfsburg
    Form DW
    League ranking xG #9xGA #2xT #6xP/match #4Points #4
    Key players
    • Fabian ReeseFxG 0.51 · xT 0.16
    • Kilian FischerRBxG 0.05 · xT 0.00
    • Hauke Finn WahlCBxG 0.00 · xT 0.29
    Final score
    25
    The model missed the outcome
    Predicted probabilities: Karlsruhe 39% · Draw 26% · Wolfsburg 35%

    How the bookmaker bet builders went

    The verdict on the pre-built bet builders for this match, priced against the model’s score matrix before kickoff. Graded on the 90-minute result.

    Matchresultat - KarlsruherBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 8,16fair 7,52+8 %
    Miss
    Matchresultat - VfL WolfsburgBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 4,01fair 8,14-51 %
    Hit

    Match prediction: KarlsruheWolfsburg

    Predicted score matrix

    Wolfsburg
    Karlsruhe
    0
    1
    2
    3
    4+
    0
    0–04.9%
    0–16.6%
    0–25.2%
    0–32.6%
    0–4+1.4%
    1
    1–06.8%
    1–111.2%
    1–28.2%
    1–34.2%
    1–4+2.2%
    2
    2–05.6%
    2–18.6%
    2–26.5%
    2–33.3%
    2–4+1.7%
    3
    3–03.0%
    3–14.5%
    3–23.4%
    3–31.7%
    3–4+0.9%
    4+
    4+–01.7%
    4+–12.5%
    4+–21.9%
    4+–31.0%
    4+–4+0.5%
    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. 4.1-07%
    5. 5.0-17%
    Expected goals
    1,581,52
    Both teams to score
    62%

    Over/under goals

    Expected goals: 3,1
    Under 2,540%
    @2.70EV+9%
    Over 2,560%
    @1.44

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Double chance Karlsruhe or draw (1X)64%
    • Over 1.5 goals82%

    Combined probability

    52%

    Fair odds

    1.92

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

    02 · 3 legs

    Balanced

    • Double chance Karlsruhe or draw (1X)64%
    • Over 2.5 goals60%
    • Fabian Schleusener to score19%

    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 score62%
    • Over 2.5 goals60%
    • Fabian Schleusener to score19%
    • Vinicius de Souza Costa to be booked24%

    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+).

    • 1 · Karlsruhe39% probability@4.33Bet365EV+70%reference odds
    • 1 · Karlsruhe39% probability@4.00BetssonEV+57%reference odds
    • 1 · Karlsruhe39% probability@4.00NordicbetEV+57%reference odds
    Bookmaker1 · KarlsruheX2 · Wolfsburg
    Bet365
    EV+ 70%
    4.33
    3.601.73
    Betsson
    EV+ 57%
    4.00
    3.601.78
    Nordicbet
    EV+ 57%
    4.00
    3.601.78
    Pinnacle
    EV+ 44%
    3.67
    3.752.02

    Odds updated 29 Aug, 10:25

    Odds movement

    10 %
    30 %25 %

    3.663.67

    X-2 %
    28 %23 %

    3.823.75

    2+4 %
    50 %45 %

    1.932.02

    Pinnacle · 19 recorded price levels · 21/08/2026 → 29/08/2026 · fixed scale 5 percentage points

    Statistics

    xG & xGA per match — 3-game rolling average

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

    Karlsruhe
    Wolfsburg
    When goals are scored and conceded 2026
    Karlsruhe (21)
    Wolfsburg (10)
    Pass networks

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

    Karlsruhe
    Marcel Franke: 94 passningar, xT 0.09FrankeChristoph Kobald: 85 passningar, xT 0.24KobaldMarvin Wanitzek: 77 passningar, xT 0.22WanitzekDanyal Zor: 65 passningar, xT -0.03ZorDeniz Emre Ofli: 63 passningar, xT 0.04OfliSebastian Jung: 53 passningar, xT 0.1JungKevin Wiethaup: 49 passningar, xT 0.2WiethaupHans Christian Bernat: 42 passningar, xT 0.09BernatNoel Eichinger: 38 passningar, xT 0.46EichingerRafael Pinto Pedrosa: 28 passningar, xT 0.01PedrosaLilian Niclas Egloff: 26 passningar, xT -0.02Egloff
    Wolfsburg
    Hauke Finn Wahl: 134 passningar, xT 0.58WahlVini Souza: 89 passningar, xT 0.14SouzaSael Kumbedi: 77 passningar, xT 0.19KumbediElvis Rexhbeçaj: 75 passningar, xT 0.24RexhbeçajMuhammed Mehmet Damar: 75 passningar, xT 0.1DamarJakub Zieliński: 70 passningar, xT 0.15ZielińskiMathys Angély: 64 passningar, xT 0.07AngélyFabian Reese: 60 passningar, xT 0.29ReeseKilian Fischer: 45 passningar, xT 0FischerFraser Hornby: 32 passningar, xT 0.02HornbyJoakim Mæhle: 25 passningar, xT 0.15Mæhle
    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.

    Karlsruhe
    Marcel Franke: 94 passningar, xT 0.09FrankeChristoph Kobald: 85 passningar, xT 0.24KobaldMarvin Wanitzek: 77 passningar, xT 0.22WanitzekDanyal Zor: 65 passningar, xT -0.03ZorDeniz Emre Ofli: 63 passningar, xT 0.04OfliSebastian Jung: 53 passningar, xT 0.1JungKevin Wiethaup: 49 passningar, xT 0.2WiethaupHans Christian Bernat: 42 passningar, xT 0.09BernatNoel Eichinger: 38 passningar, xT 0.46EichingerRafael Pinto Pedrosa: 28 passningar, xT 0.01PedrosaLilian Niclas Egloff: 26 passningar, xT -0.02Egloff
    Wolfsburg
    Hauke Finn Wahl: 134 passningar, xT 0.58WahlVini Souza: 89 passningar, xT 0.14SouzaSael Kumbedi: 77 passningar, xT 0.19KumbediElvis Rexhbeçaj: 75 passningar, xT 0.24RexhbeçajMuhammed Mehmet Damar: 75 passningar, xT 0.1DamarJakub Zieliński: 70 passningar, xT 0.15ZielińskiMathys Angély: 64 passningar, xT 0.07AngélyFabian Reese: 60 passningar, xT 0.29ReeseKilian Fischer: 45 passningar, xT 0FischerFraser Hornby: 32 passningar, xT 0.02HornbyJoakim Mæhle: 25 passningar, xT 0.15Mæhle

    The teams in numbers

    PerformanceKarlsruheWolfsburg
    Points44
    xPoints3.53.5
    xG per match1.31.6
    xGA per match0.720.72
    xG within 8s of winning the ball0.30.23
    xGA within 8s of losing the ball0.090.13
    Playing styleKarlsruheWolfsburg
    Build-up efficiency0.30.3
    Field tilt0.590.6
    xT per match0.731.3
    xTA per match0.830.96
    Won balls, offensive half2927
    Pressing intensity0.250.23
    Pressing efficiency0.380.28
    Pressing efficiency, offensive half0.30.27
    Entries into the box per match1611
    Entries into the box against1014
    Pass completion %0.750.77
    Pass completion % under pressure0.740.73
    Passes per match329422
    Passes against per match287325
    Switches of play per match14.217.1
    Long balls per match2630
    Set piecesKarlsruheWolfsburg
    xG from free kicks0.030.02
    Corners per match8.37.5
    Corners against per match4.95
    xG per corner0.020.02
    xGA per corner against0.030
    First touch, offensive corners %0.350.14
    First touch, defensive corners %0.30.4
    OtherKarlsruheWolfsburg
    Throw-in control0.820.76
    The goalkeepersHans Christian Bernat (Karlsruhe)Jakub Zieliński (Wolfsburg)
    Saves65
    Save %86%100%
    xG prevented81%100%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Karlsruhe vs Wolfsburg according to our model?

    The model gives Karlsruhe a 39% win probability. Full 1X2 picture: Karlsruhe 39%, draw 26%, Wolfsburg 35%.

    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 60% and under at 40%.

    Will both teams score?

    The probability of both teams scoring is 62% 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.