2. BundesligaVonovia Ruhrstadion, Bochum21°15,2 mm22 km/h

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    BochumBochumPossession control
    01
    OsnabrückOsnabrückPossession control
    The model's lean: 1 · Bochum (37%)Best value by the model: 2 · Osnabrück @ 5.50 (+95 %)

    BochumOsnabrück · 2. Bundesliga

    1 · Bochum 37%X 27%35% Osnabrück · 2

    Analysis: BochumOsnabrück

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

    Possession control will dictate the tempo when Bochum hosts Osnabrück, as both teams favor a style centered around maintaining the ball. Despite a slight market lean towards Bochum, this match promises to be tight. The model pegs Bochum at a 37% chance of winning, with Osnabrück not far behind at 35%. A draw sits at 27% likelihood, suggesting a finely balanced contest.

    The expected goals are nearly even: 1.35 for the hosts and 1.21 for the visitors. While Bochum edges ahead in xPoints (3.0 to 2.5), Osnabrück must address their defensive frailties, conceding double the expected goals per match (2.0 xGA) compared to Bochum’s 0.98. Rain might suppress scoring, though it's already considered in the model's lean towards under 2.5 goals at 53%.

    With both sides yet to demonstrate dominance, the most probable outcomes are a 1-1 draw (13%) or a narrow 1-0 win for Bochum (10%). Yet, Osnabrück's away proposition at 5.3 odds with Betsafe, Betsson, and Nordicbet presents a striking 88% value edge, defying traditional odds.

    Considering the rain and controlled possession styles, this contest could very well edge towards a low-scoring affair. Still, the real action might be on the sidelines, where savvy punters will find significant value in backing Osnabrück at those generous odds, despite them being slight underdogs on paper.

    BochumBochum
    Form DDWLW
    League ranking xG #10xGA #4xT #9xP/match #8Points #9
    Key players
    • Philipp HofmannFxG 0.31 · xT 0.08
    • Berkan TazCAMxG 0.14 · xT 0.45
    • Maximilian WittekLWBxG 0.10 · xT 0.21
    OsnabrückOsnabrück
    Form LL
    League ranking xG #11xGA #16xT #7xP/match #12Points #18
    Key players
    • Ismail BadjieFxG 0.15 · xT 0.03
    • David KopaczCAMxG 0.09 · xT 0.00
    • Konrad Johannes Karl FaberFxG 0.00 · xT 0.13
    Final score
    01
    The model missed the outcome
    Predicted probabilities: Bochum 37% · Draw 27% · Osnabrück 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 - VfL 1899 OsnabruckBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 17,31fair 13,35+30 %
    Miss

    Match prediction: BochumOsnabrück

    Predicted score matrix

    Osnabrück
    Bochum
    0
    1
    2
    3
    4+
    0
    0–08.1%
    0–19.0%
    0–25.6%
    0–32.3%
    0–4+0.9%
    1
    1–010.1%
    1–113.0%
    1–27.6%
    1–33.1%
    1–4+1.2%
    2
    2–07.1%
    2–18.5%
    2–25.1%
    2–32.1%
    2–4+0.8%
    3
    3–03.2%
    3–13.8%
    3–22.3%
    3–30.9%
    3–4+0.4%
    4+
    4+–01.4%
    4+–11.7%
    4+–21.0%
    4+–30.4%
    4+–4+0.2%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-113%
    2. 2.1-010%
    3. 3.0-19%
    4. 4.2-19%
    5. 5.0-08%
    Expected goals
    1,351,21
    Both teams to score
    52%

    Over/under goals

    Expected goals: 2,6
    Under 2,553%
    @2.35EV+25%
    Over 2,547%
    @1.70

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Double chance Bochum or draw (1X)67%
    • Under 3.5 goals75%

    Combined probability

    50%

    Fair odds

    2.00

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

    02 · 3 legs

    Balanced

    • Double chance Bochum or draw (1X)67%
    • Under 2.5 goals53%
    • Mats Henry Pannewig to score14%

    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 score52%
    • Over 2.5 goals47%
    • Robin Maximilian Meißner to score22%
    • Cajetan Lenz to be booked25%

    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+).

    • 2 · Osnabrück35% probability@5.50Bet365EV+95%reference odds
    • 2 · Osnabrück35% probability@5.30BetsafeEV+88%reference odds
    • 2 · Osnabrück35% probability@5.30BetssonEV+88%reference odds
    Bookmaker1 · BochumX2 · Osnabrück
    Bet3651.50
    EV+ 15%
    4.20
    EV+ 95%
    5.50
    Betsafe1.50
    EV+ 14%
    4.15
    EV+ 88%
    5.30
    Betsson1.50
    EV+ 14%
    4.15
    EV+ 88%
    5.30
    Nordicbet1.50
    EV+ 14%
    4.15
    EV+ 88%
    5.30
    Pinnacle1.80
    EV+ 10%
    4.00
    EV+ 55%
    4.38

    Odds updated 28 Aug, 10:29

    Odds movement

    Market signal

    The market has moved clearly towards an Osnabrück win since 22 August — the odds have shortened from 4.92 to 4.38 (−11%).

    1+9 %
    58 %53 %

    1.651.80

    X-3 %
    26 %21 %

    4.114.00

    2-11 %
    23 %18 %

    4.924.38

    Over 2,5-1 %
    58 %53 %

    1.721.70

    Pinnacle · 11 recorded price levels · 22/08/2026 → 28/08/2026 · fixed scale 5 percentage points

    Statistics

    xG & xGA per match — 3-game rolling average

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

    Bochum
    Osnabrück
    When goals are scored and conceded 2026
    Bochum (11)
    Osnabrück (37)
    Pass networks

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

    Bochum
    Michael Steinwender: 104 passningar, xT 0.14SteinwenderMaximilian Wittek: 84 passningar, xT 0.37WittekEnis Çokaj: 83 passningar, xT -0.11ÇokajKarol Mets: 70 passningar, xT 0.08MetsTimo Phil Horn: 54 passningar, xT 0.07HornMats Pannewig: 45 passningar, xT 0.04PannewigOliver Olsen: 44 passningar, xT 0.02OlsenBerkan Taz: 39 passningar, xT 0.55TazKōji Miyoshi: 25 passningar, xT -0.04MiyoshiJean-Manuel Mbom: 23 passningar, xT 0.01MbomGerrit Holtmann: 22 passningar, xT 0.21Holtmann
    Osnabrück
    Robin Fabinski: 77 passningar, xT 0.22FabinskiJannik Muller: 73 passningar, xT 0.15MullerFridolin Wagner: 65 passningar, xT 0.17WagnerKonrad Johannes Karl Faber: 54 passningar, xT 0.16FaberPatrick Kammerbauer: 50 passningar, xT 0.55KammerbauerBjarke Jacobsen: 50 passningar, xT 0.11JacobsenNiklas Wiemann: 47 passningar, xT 0.09WiemannJonas Krumrey: 36 passningar, xT 0.08KrumreyRobin Meissner: 34 passningar, xT 0.12MeissnerLeonhard Luis Münst: 25 passningar, xT 0.1MünstDavid Kopacz: 21 passningar, xT -0.01Kopacz
    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: 104 passningar, xT 0.14SteinwenderMaximilian Wittek: 84 passningar, xT 0.37WittekEnis Çokaj: 83 passningar, xT -0.11ÇokajKarol Mets: 70 passningar, xT 0.08MetsTimo Phil Horn: 54 passningar, xT 0.07HornMats Pannewig: 45 passningar, xT 0.04PannewigOliver Olsen: 44 passningar, xT 0.02OlsenBerkan Taz: 39 passningar, xT 0.55TazKōji Miyoshi: 25 passningar, xT -0.04MiyoshiJean-Manuel Mbom: 23 passningar, xT 0.01MbomGerrit Holtmann: 22 passningar, xT 0.21Holtmann
    Osnabrück
    Robin Fabinski: 77 passningar, xT 0.22FabinskiJannik Muller: 73 passningar, xT 0.15MullerFridolin Wagner: 65 passningar, xT 0.17WagnerKonrad Johannes Karl Faber: 54 passningar, xT 0.16FaberPatrick Kammerbauer: 50 passningar, xT 0.55KammerbauerBjarke Jacobsen: 50 passningar, xT 0.11JacobsenNiklas Wiemann: 47 passningar, xT 0.09WiemannJonas Krumrey: 36 passningar, xT 0.08KrumreyRobin Meissner: 34 passningar, xT 0.12MeissnerLeonhard Luis Münst: 25 passningar, xT 0.1MünstDavid Kopacz: 21 passningar, xT -0.01Kopacz

    The teams in numbers

    PerformanceBochumOsnabrück
    Points30
    xPoints32.5
    xG per match1.41.4
    xGA per match0.982
    xG within 8s of winning the ball0.080.1
    xGA within 8s of losing the ball0.280.4
    Playing styleBochumOsnabrück
    Build-up efficiency0.320.32
    Field tilt0.440.45
    xT per match0.971.1
    xTA per match0.581.1
    Won balls, offensive half2829
    Pressing intensity0.240.24
    Pressing efficiency0.270.29
    Pressing efficiency, offensive half0.250.22
    Entries into the box per match913
    Entries into the box against1017
    Pass completion %0.710.69
    Pass completion % under pressure0.680.65
    Passes per match334293
    Passes against per match342435
    Switches of play per match24.613.2
    Long balls per match3631
    Set piecesBochumOsnabrück
    xG from free kicks0.010.02
    Corners per match5.54.5
    Corners against per match3.57.1
    xG per corner0.050.02
    xGA per corner against0.060.03
    First touch, offensive corners %0.180.56
    First touch, defensive corners %0.860.43
    OtherBochumOsnabrück
    Throw-in control0.770.74
    The goalkeepersTimo Phil Horn (Bochum)Jonas Krumrey (Osnabrück)
    Saves45
    Save %80%42%
    xG prevented75%18%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Bochum vs Osnabrück according to our model?

    The model gives Bochum a 37% win probability. Full 1X2 picture: Bochum 37%, draw 27%, Osnabrück 35%.

    What is the most likely scoreline?

    The model's most likely final score is 1-1 at 13% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 47% and under at 53%.

    Will both teams score?

    The probability of both teams scoring is 52% 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.