BundesligaSignal Iduna Park, Dortmund19°1,5 mm22 km/h

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    Borussia DortmundBorussia DortmundPossession & high press
    20
    Hamburger SVHamburger SVLow block & direct
    The model's lean: 1 · Borussia Dortmund (78%)

    Borussia DortmundHamburger SV · Bundesliga

    1 · Borussia Dortmund 78%X 14%9% Hamburger SV · 2

    Analysis: Borussia DortmundHamburger SV

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

    TEXT: Borussia Dortmund's dominance at home jumps out immediately: a 71% win rate across their 34 all-time home matches speaks to formidable consistency. This weekend, they face Hamburger SV, a side sitting well below them on both the points and expected goals tables. The numbers clearly favor the hosts, with the model giving them a substantial 78% chance of victory. Dortmund’s playing style, marked by possession and a high press, contrasts sharply with Hamburg’s more defensive, direct approach—an imbalance that often leads to home success.

    Despite the small head-to-head sample, Dortmund edges it with one win and one draw in their recent encounters. This historical advantage, coupled with their superior xG and xGA figures, suggests they're equipped to control the game. Dortmund's xG per match stands at 1.8, comfortably higher than Hamburg's 1.3, while their defensive metrics also show a tighter ship with xGA at 1.2 compared to Hamburg's 1.8.

    The model's most likely scorelines—2-0, 1-0, and 3-0—also underscore the home team's superiority. However, the over/under 2.5 goals market presents an intriguing opportunity. While the over 2.5 goals is favored at 61%, there’s value in the under. At odds of 2.61 with Betsafe, Betsson, and Nordicbet, the under 2.5 goals shows a 3% edge according to the model's 39% rating. This positions the under bet as an enticing proposition, especially given Dortmund's strong defense and potential to control the match tempo.

    In sum, expect Dortmund to assert their dominance, likely securing a win with a clean sheet. While the hosts are heavily backed to win, the under 2.5 goals market at the provided odds reveals a shrewd play for value seekers, framing the match as one where disciplined defense could suppress the scoreline.

    Borussia DortmundBorussia Dortmund
    Form LWLWW
    League ranking xG #4xGA #2xT #3xP/match #6Points #2
    Key players
    • Serhou GuirassyFxG 0.60 · xT 0.01
    • Julian BrandtLWxG 0.21 · xT 0.18
    • Julian RyersonRWxG 0.04 · xT 0.23
    Hamburger SVHamburger SV
    Form LLWWD
    League ranking xG #16xGA #16xT #16xP/match #14Points #13
    Key players
    • Miro MuheimLWxG 0.05 · xT 0.14
    • Jean Luc DompeLWxG 0.20 · xT 0.28
    • Rayan PhilippeFxG 0.33 · xT 0.09
    Final score
    20
    The model called the outcome
    Predicted probabilities: Borussia Dortmund 78% · Draw 14% · Hamburger SV 9%

    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 - Borussia DortmundBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 3,66fair 4,63-21 %
    Miss
    Matchresultat - Hamburger SVBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 22,14fair 42,23-48 %
    Miss

    Match prediction: Borussia DortmundHamburger SV

    Predicted score matrix

    Hamburger SV
    Borussia Dortmund
    0
    1
    2
    3
    4+
    0
    0–04.6%
    0–13.2%
    0–21.3%
    0–30.3%
    0–4+0.1%
    1
    1–010.0%
    1–18.2%
    1–23.1%
    1–30.8%
    1–4+0.2%
    2
    2–012.0%
    2–19.4%
    2–23.7%
    2–31.0%
    2–4+0.2%
    3
    3–09.4%
    3–17.4%
    3–22.9%
    3–30.8%
    3–4+0.2%
    4+
    4+–09.7%
    4+–17.6%
    4+–23.0%
    4+–30.8%
    4+–4+0.2%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.2-012%
    2. 2.1-010%
    3. 3.3-09%
    4. 4.2-19%
    5. 5.1-18%
    Expected goals
    2,350,78
    Both teams to score
    49%

    Over/under goals

    Expected goals: 3,1
    Under 2,539%
    @2.61EV+3%
    Over 2,561%
    @1.51

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Borussia Dortmund to win78%
    • Over 1.5 goals82%

    Combined probability

    62%

    Fair odds

    1.61

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

    02 · 3 legs

    Balanced

    • Borussia Dortmund to win78%
    • Over 2.5 goals61%
    • Serhou Yadaly Guirassy to score29%

    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 score49%
    • Over 2.5 goals61%
    • Serhou Yadaly Guirassy to score29%
    • Jordan Torunarigha 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+).

    • 1 · Borussia Dortmund78% probability@1.38PinnacleEV+7%reference odds
    • 1 · Borussia Dortmund78% probability@1.35BetsafeEV+5%reference odds
    • 1 · Borussia Dortmund78% probability@1.35BetssonEV+5%reference odds
    Bookmaker1 · Borussia DortmundX2 · Hamburger SV
    Betsafe
    EV+ 5%
    1.35
    5.157.60
    Betsson
    EV+ 5%
    1.35
    5.157.60
    Nordicbet
    EV+ 5%
    1.35
    5.157.60
    Pinnacle
    EV+ 7%
    1.38
    5.447.75

    Odds updated 29 Aug, 11:37

    Odds movement

    1+5 %
    74 %69 %

    1.321.38

    X-1 %
    20 %15 %

    5.485.44

    2-5 %
    14 %9 %

    8.167.75

    Pinnacle · 9 recorded price levels · 23/08/2026 → 29/08/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    2 matches
    Borussia Dortmund 1Draw 1Hamburger SV 0
    Goals: 43 (⌀ 3,5)

    Head-to-head based on Bundesliga data since 2022.

    Key facts

    • Borussia Dortmund win 71% of their home matches all-time (34 played).
    xG & xGA per match — 3-game rolling average

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

    Borussia Dortmund
    Hamburger SV
    When goals are scored and conceded 2025
    Borussia Dortmund (7034)
    Hamburger SV (4054)
    Pass networks

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

    Borussia Dortmund
    Waldemar Anton: 329 passningar, xT 0.32AntonNico Schlotterbeck: 315 passningar, xT 1.27SchlotterbeckJobe Bellingham: 207 passningar, xT -0.03BellinghamLuca Reggiani: 179 passningar, xT 0.19ReggianiJulian Ryerson: 172 passningar, xT 1.06RyersonGregor Kobel: 153 passningar, xT 0.2KobelMarcel Sabitzer: 138 passningar, xT 0.42SabitzerJulian Brandt: 123 passningar, xT 0.92BrandtMaximilian Beier: 107 passningar, xT 0.49BeierRamy Bensebaini: 96 passningar, xT 0.19BensebainiSamuele Inácio Piá: 94 passningar, xT 0.21Piá
    Hamburger SV
    Nicolai Remberg: 202 passningar, xT 0.31RembergWarmed Omari: 172 passningar, xT 0.24OmariDaniel Heuer Fernandes: 144 passningar, xT 0.4FernandesFabio Vieira: 131 passningar, xT 0.27VieiraAlbert Sambi Lokonga: 110 passningar, xT 0.23LokongaNicolas Capaldo: 110 passningar, xT 0.87CapaldoJordan Torunarigha: 103 passningar, xT 0.1TorunarighaAlbert Grønbæk Erlykke: 94 passningar, xT 0.72ErlykkeLuka Vuskovic: 82 passningar, xT 0.23VuskovicBakery Jatta: 58 passningar, xT -0.06JattaRansford Königsdörffer: 41 passningar, xT 0.24Königsdörffer
    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.

    Borussia Dortmund
    Waldemar Anton: 329 passningar, xT 0.32AntonNico Schlotterbeck: 315 passningar, xT 1.27SchlotterbeckJobe Bellingham: 207 passningar, xT -0.03BellinghamLuca Reggiani: 179 passningar, xT 0.19ReggianiJulian Ryerson: 172 passningar, xT 1.06RyersonGregor Kobel: 153 passningar, xT 0.2KobelMarcel Sabitzer: 138 passningar, xT 0.42SabitzerJulian Brandt: 123 passningar, xT 0.92BrandtMaximilian Beier: 107 passningar, xT 0.49BeierRamy Bensebaini: 96 passningar, xT 0.19BensebainiSamuele Inácio Piá: 94 passningar, xT 0.21Piá
    Hamburger SV
    Nicolai Remberg: 202 passningar, xT 0.31RembergWarmed Omari: 172 passningar, xT 0.24OmariDaniel Heuer Fernandes: 144 passningar, xT 0.4FernandesFabio Vieira: 131 passningar, xT 0.27VieiraAlbert Sambi Lokonga: 110 passningar, xT 0.23LokongaNicolas Capaldo: 110 passningar, xT 0.87CapaldoJordan Torunarigha: 103 passningar, xT 0.1TorunarighaAlbert Grønbæk Erlykke: 94 passningar, xT 0.72ErlykkeLuka Vuskovic: 82 passningar, xT 0.23VuskovicBakery Jatta: 58 passningar, xT -0.06JattaRansford Königsdörffer: 41 passningar, xT 0.24Königsdörffer

    The teams in numbers

    PerformanceBorussia DortmundHamburger SV
    Points7338
    xPoints52.441.4
    xG per match1.81.3
    xGA per match1.21.8
    xG within 8s of winning the ball0.240.16
    xGA within 8s of losing the ball0.150.24
    Playing styleBorussia DortmundHamburger SV
    Build-up efficiency0.310.31
    Field tilt0.610.34
    xT per match1.30.88
    xTA per match0.861.3
    Won balls, offensive half2821
    Pressing intensity0.240.23
    Pressing efficiency0.260.26
    Pressing efficiency, offensive half0.30.29
    Entries into the box per match1510
    Entries into the box against1115
    Pass completion %0.80.77
    Pass completion % under pressure0.750.72
    Passes per match429322
    Passes against per match368401
    Switches of play per match26.323
    Long balls per match3031
    Set piecesBorussia DortmundHamburger SV
    xG from free kicks0.070.06
    Corners per match5.33.6
    Corners against per match4.25.8
    xG per corner0.060.04
    xGA per corner against0.040.06
    First touch, offensive corners %0.40.39
    First touch, defensive corners %0.480.56
    OtherBorussia DortmundHamburger SV
    Throw-in control0.730.76
    The goalkeepersGregor Kobel (Borussia Dortmund)Daniel Heuer Fernandes (Hamburger SV)
    Saves90107
    Save %73%67%
    xG prevented43%42%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Borussia Dortmund vs Hamburger SV according to our model?

    The model gives Borussia Dortmund a 78% win probability. Full 1X2 picture: Borussia Dortmund 78%, draw 14%, Hamburger SV 9%.

    What is the most likely scoreline?

    The model's most likely final score is 2-0 at 12% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 61% and under at 39%.

    Will both teams score?

    The probability of both teams scoring is 49% 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.