2. BundesligaVonovia Ruhrstadion, Bochum19°0,2 mm13 km/h

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    BochumBochumPossession control
    vs
    Greuther FürthGreuther FürthCounter-attacks & crosses
    The model's lean: 1 · Bochum (52%)

    BochumGreuther Fürth · 2. Bundesliga

    1 · Bochum 52%X 26%22% Greuther Fürth · 2

    Analysis: BochumGreuther Fürth

    Oscar Nilsson · · Model-assisted analysis, fact-checked · How the predictions work

    TEXT:

    Bochum enters this match with market backing as favorites at a 52% win probability, but the numbers suggest a more nuanced story. While the hosts have the edge in points and a perfect record in their two recent head-to-heads, the sample size is too small to be decisive. Instead, digging deeper into expected numbers reveals a different narrative: Fürth edges it with 1.6 xG per match compared to Bochum's 1.4, yet they also concede more, allowing 1.6 xGA to Bochum's 1.1. This contradiction in attacking promise and defensive vulnerability for Fürth adds layers to the market's oversimplified picture.

    The model leans towards Bochum, favoring them for their possession-based control that typically stifles opponents. Yet, Fürth's counter-attacking style, enhanced by effective crosses, might exploit Bochum's need to dominate possession. Expected goals further complicate matters: Bochum has a slight edge at 1.71 versus Fürth's 1.08, but the 1-1 scoreline as the most likely outcome (12%) hints at defensive frailties for both.

    With a 53% chance of over 2.5 goals and a 55% probability for both teams to score, the game leans towards an open encounter. Bochum's defensive stability doesn't fully eclipse their opponents' adventurous attacking play, suggesting goals on both ends. Despite these indicators, Bochum's 1-0 and 2-1 scorelines, each at 10%, align with their tactical approach and market position.

    For bettors pinpointing value, Fürth's 22% win probability implied by the model may be worth exploring as an away win option. Considering Fürth's superior xG and the volatility of their counter-attacking dynamic, this presents an intriguing opportunity. While not a certainty, the potential for disruption is significant, especially if Bochum fails to convert possession into goals.

    BochumBochum
    Form WLWLW
    League ranking xG #14xGA #2xT #7xP/match #11Points #6
    Key players
    • Maximilian WittekLBxG 0.08 · xT 0.24
    • Philipp HofmannFxG 0.22 · xT 0.01
    • Mats PannewigCMxG 0.15 · xT 0.01
    Greuther FürthGreuther Fürth
    Form WDLWL
    League ranking xG #11xGA #10xT #14xP/match #5Points #10
    Key players
    • Felix KlausFxG 1.01 · xT 0.13
    • Luca ItterLWBxG 0.02 · xT 0.11
    • Dennis SrbenyFxG 0.11 · xT 0.00

    Match prediction: BochumGreuther Fürth

    Predicted score matrix

    Greuther Fürth
    Bochum
    0
    1
    2
    3
    4+
    0
    0–06.4%
    0–16.3%
    0–23.6%
    0–31.3%
    0–4+0.4%
    1
    1–010.1%
    1–111.7%
    1–26.1%
    1–32.2%
    1–4+0.8%
    2
    2–09.0%
    2–19.7%
    2–25.3%
    2–31.9%
    2–4+0.6%
    3
    3–05.1%
    3–15.5%
    3–23.0%
    3–31.1%
    3–4+0.4%
    4+
    4+–03.2%
    4+–13.5%
    4+–21.9%
    4+–30.7%
    4+–4+0.2%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-112%
    2. 2.1-010%
    3. 3.2-110%
    4. 4.2-09%
    5. 5.0-06%
    Expected goals
    1,711,08
    Both teams to score
    55%

    Over/under goals

    Expected goals: 2,8
    Under 2,547%
    Over 2,553%

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Bochum to win52%
    • Over 1.5 goals77%

    Combined probability

    42%

    Fair odds

    2.40

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

    02 · 3 legs

    Balanced

    • Bochum to win52%
    • Over 2.5 goals53%
    • Philipp Hofmann to score30%

    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 goals53%
    • Philipp Hofmann to score30%
    • Philipp Ziereis 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

    The model's value spots

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

    • 1 · Bochum52% probability@1.96PinnacleEV+2%reference odds
    Bookmaker1 · BochumX2 · Greuther Fürth
    Pinnacle
    EV+ 2%
    1.96
    3.873.68

    Odds updated 11 Sept, 12:24

    Odds movement

    1+5 %
    52 %47 %

    1.871.96

    X0 %
    27 %22 %

    3.873.87

    2-5 %
    28 %23 %

    3.873.68

    Pinnacle · 9 recorded price levels · 06/09/2026 → 11/09/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    2 matches
    Bochum 2Draw 0Greuther Fürth 0
    Goals: 51 (⌀ 3)

    Head-to-head based on 2. Bundesliga data since 2023.

    xG & xGA per match — 3-game rolling average

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

    Bochum
    Greuther Fürth
    When goals are scored and conceded 2026
    Bochum (33)
    Greuther Fürth (79)
    Pass networks

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

    Bochum
    Michael Steinwender: 268 passningar, xT 0.36SteinwenderKarol Mets: 228 passningar, xT 0.17MetsMaximilian Wittek: 222 passningar, xT 0.87WittekMats Pannewig: 148 passningar, xT -0.02PannewigOliver Olsen: 121 passningar, xT 0.06OlsenTimo Phil Horn: 111 passningar, xT 0.15HornEnis Çokaj: 95 passningar, xT 0.02ÇokajKōji Miyoshi: 75 passningar, xT 0.05MiyoshiGerrit Holtmann: 57 passningar, xT 0.44HoltmannBerkan Taz: 56 passningar, xT 0.55TazPhilipp Hofmann: 49 passningar, xT -0.1Hofmann
    Greuther Fürth
    Jannis Heuer: 168 passningar, xT 0.28HeuerPaul Will: 159 passningar, xT 0.17WillKrisztián Keresztes: 154 passningar, xT 0.25KeresztesFlorian Pascal Hellstern: 146 passningar, xT 0.21HellsternLuca Itter: 136 passningar, xT 0.41ItterJannik Dehm: 118 passningar, xT 0.52DehmFelix Klaus: 100 passningar, xT 0.21KlausSacha Banse: 97 passningar, xT 0.16BanseOlé Pohlmann: 90 passningar, xT -0.01PohlmannShinta Karl Appelkamp: 76 passningar, xT 0.09AppelkampDennis Srbeny: 47 passningar, xT 0.07Srbeny
    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.

    Bochum
    Michael Steinwender: 268 passningar, xT 0.36SteinwenderKarol Mets: 228 passningar, xT 0.17MetsMaximilian Wittek: 222 passningar, xT 0.87WittekMats Pannewig: 148 passningar, xT -0.02PannewigOliver Olsen: 121 passningar, xT 0.06OlsenTimo Phil Horn: 111 passningar, xT 0.15HornEnis Çokaj: 95 passningar, xT 0.02ÇokajKōji Miyoshi: 75 passningar, xT 0.05MiyoshiGerrit Holtmann: 57 passningar, xT 0.44HoltmannBerkan Taz: 56 passningar, xT 0.55TazPhilipp Hofmann: 49 passningar, xT -0.1Hofmann
    Greuther Fürth
    Jannis Heuer: 168 passningar, xT 0.28HeuerPaul Will: 159 passningar, xT 0.17WillKrisztián Keresztes: 154 passningar, xT 0.25KeresztesFlorian Pascal Hellstern: 146 passningar, xT 0.21HellsternLuca Itter: 136 passningar, xT 0.41ItterJannik Dehm: 118 passningar, xT 0.52DehmFelix Klaus: 100 passningar, xT 0.21KlausSacha Banse: 97 passningar, xT 0.16BanseOlé Pohlmann: 90 passningar, xT -0.01PohlmannShinta Karl Appelkamp: 76 passningar, xT 0.09AppelkampDennis Srbeny: 47 passningar, xT 0.07Srbeny

    The teams in numbers

    PerformanceBochumGreuther Fürth
    Points64
    xPoints5.76.3
    xG per match1.41.6
    xGA per match1.11.6
    xG within 8s of winning the ball0.230.27
    xGA within 8s of losing the ball0.180.18
    Playing styleBochumGreuther Fürth
    Build-up efficiency0.320.32
    Field tilt0.540.42
    xT per match0.980.79
    xTA per match0.51.4
    Won balls, offensive half3121
    Pressing intensity0.230.24
    Pressing efficiency0.330.27
    Pressing efficiency, offensive half0.320.24
    Entries into the box per match1111
    Entries into the box against1015
    Pass completion %0.750.77
    Pass completion % under pressure0.690.73
    Passes per match411348
    Passes against per match333353
    Switches of play per match2928.9
    Long balls per match4035
    Set piecesBochumGreuther Fürth
    xG from free kicks0.010.03
    Corners per match5.34.9
    Corners against per match45.9
    xG per corner0.060.01
    xGA per corner against0.120.05
    First touch, offensive corners %0.240.35
    First touch, defensive corners %0.810.46
    OtherBochumGreuther Fürth
    Throw-in control0.730.68
    The goalkeepersTimo Phil Horn (Bochum)Florian Pascal Hellstern (Greuther Fürth)
    Saves918
    Save %75%67%
    xG prevented81%61%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Bochum vs Greuther Fürth according to our model?

    The model gives Bochum a 52% win probability. Full 1X2 picture: Bochum 52%, draw 26%, Greuther Fürth 22%.

    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 53% and under at 47%.

    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.