3. LigaUpdated

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    HavelseHavelseLow block & direct
    vs
    The model's lean: 2 · VfB Stuttgart II (44%)
    VfB Stuttgart IIVfB Stuttgart IIPossession control

    HavelseVfB Stuttgart II · 3. Liga

    1 · Havelse 30%X 26%44% VfB Stuttgart II · 2
    HavelseHavelse
    Form LWLWL
    League ranking xG #18xGA #20xT #20xP/match #14Points #17
    Key players
    • Marko IlicFxG 0.11 · xT 0.15
    • John Xaver PosseltFxG 0.37 · xT 0.07
    • Arlind RexhepiFxG 0.08 · xT 0.12
    VfB Stuttgart IIVfB Stuttgart II
    Form DLWLL
    League ranking xG #9xGA #14xT #3xP/match #17Points #14
    Key players
    • Mansour Ouro-TagbaFxG 0.33 · xT 0.1
    • Noah Yanis DarvichRWxG 0.32 · xT 0.18
    • Leny MeyerLWBxG 0.09 · xT 0.17

    Match prediction: HavelseVfB Stuttgart II

    Predicted score matrix

    VfB Stuttgart II
    Havelse
    0
    1
    2
    3
    4+
    0
    0–03.6%
    0–16.2%
    0–26.4%
    0–34.2%
    0–4+3.3%
    1
    1–04.5%
    1–19.6%
    1–29.2%
    1–36.1%
    1–4+4.7%
    2
    2–03.4%
    2–16.7%
    2–26.7%
    2–34.4%
    2–4+3.4%
    3
    3–01.6%
    3–13.2%
    3–23.2%
    3–32.1%
    3–4+1.6%
    4+
    4+–00.8%
    4+–11.6%
    4+–21.6%
    4+–31.0%
    4+–4+0.8%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-110%
    2. 2.1-29%
    3. 3.2-17%
    4. 4.2-27%
    5. 5.0-26%
    Expected goals
    1,441,97
    Both teams to score
    66%

    Over/under goals

    Expected goals: 3,4
    Under 2,534%
    Over 2,566%

    Odds & value

    The model's value spots

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

    • X · Draw26% probability@4.12PinnacleEV+5%
    Bookmaker1 · HavelseX2 · VfB Stuttgart II
    Pinnacle3.19
    EV+ 5%
    4.12
    1.95

    Odds updated 4 Aug, 09:04

    Analysis: HavelseVfB Stuttgart II

    Marcus Johansson · · How the predictions work

    Twelve consecutive league matches with a goal for VfB Stuttgart II—it's a streak that speaks volumes about their offensive prowess. As they square off against Havelse, who lean heavily on a direct approach with a leaky backline, the numbers tip the balance towards the visitors. With the model putting VfB Stuttgart II's win probability at 44%, a clear tilt is evident, especially when contrasting it with Havelse’s 30% likelihood of prevailing.

    Havelse enters the fray with a distinct strategy: low defence combined with direct play. This isn't particularly comforting when facing a side like VfB Stuttgart II, who are adept at controlling possession and have a slight edge in xG per match—1.6 to Havelse's 1.3. Expectation doesn’t always match reality, though; Havelse has managed an xPoints tally of 48.6, outshining VfB Stuttgart II's 45.0. Yet, the real points tell a different story, where VfB Stuttgart II leads with 46 to Havelse’s 35. It's a classic case of potential versus execution.

    The most likely scorelines tell their own story: a 1-1 draw at 10% and a 1-2 away victory at 9%. Yet, there's a slightly intriguing lure for bettors here. At odds of 4.12 with Pinnacle, a draw offers value with a 5% edge according to the model's 26% probability. It’s a tempting proposition for those inclined toward a calculated risk.

    VfB Stuttgart II has consistently found the back of the net, and with an expected goals tally of 1.97 compared to Havelse’s 1.44, the over 2.5 goals market appears promising at 66%. The probability of both teams scoring mirrors this at 66%, making the match ripe for a game full of scoring chances. While a 1-2 scoreline aligns with the lean toward VfB Stuttgart II, considering the draw value could be the savviest punt for those looking to capitalize on market inefficiencies.

    Statistics

    Head-to-head

    2 matches
    Havelse 1Draw 0VfB Stuttgart II 1
    Goals: 44 (⌀ 4)

    Head-to-head based on 3. Liga data since 2024.

    Key facts

    • VfB Stuttgart II have scored in 12 consecutive league matches.
    xG & xGA per match — 3-game rolling average

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

    Havelse
    VfB Stuttgart II
    When goals are scored and conceded 2025
    Havelse (5789)
    VfB Stuttgart II (5769)
    Pass networks

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

    Havelse
    Julius Düker: 153 passningar, xT 0.32DükerJohann Berger: 136 passningar, xT 0.25BergerBesfort Leutrim Kolgeci: 130 passningar, xT 0.31KolgeciSemi Belkahia: 128 passningar, xT 0.12BelkahiaNorman Quindt: 113 passningar, xT 0.24QuindtMarko Ilic: 103 passningar, xT 0.81IlicNassim Boujellab: 93 passningar, xT 0.14BoujellabArlind Rexhepi: 88 passningar, xT 0.31RexhepiDennis Duah: 83 passningar, xT 0.06DuahLeon Sommer: 78 passningar, xT 1.02SommerEmre Aytun: 59 passningar, xT 0.25Aytun
    VfB Stuttgart II
    Christopher Olivier: 251 passningar, xT 1.02OlivierNicolas Sessa: 216 passningar, xT 0.26SessaLeny Meyer: 204 passningar, xT 0.93MeyerSamuele Di Benedetto: 189 passningar, xT 0.43BenedettoMaximilian Herwerth: 140 passningar, xT 0.16HerwerthNoah Yanis Darvich: 131 passningar, xT 1.71DarvichTim Kohler: 131 passningar, xT 0.4KohlerMirza Ćatović: 114 passningar, xT 0.23ĆatovićDominik Nothnagel: 91 passningar, xT 0.14NothnagelJustin Diehl: 84 passningar, xT 0.49DiehlJeremy Alberto Arévalo Mera: 69 passningar, xT 0.22Mera
    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.

    Havelse
    Julius Düker: 153 passningar, xT 0.32DükerJohann Berger: 136 passningar, xT 0.25BergerBesfort Leutrim Kolgeci: 130 passningar, xT 0.31KolgeciSemi Belkahia: 128 passningar, xT 0.12BelkahiaNorman Quindt: 113 passningar, xT 0.24QuindtMarko Ilic: 103 passningar, xT 0.81IlicNassim Boujellab: 93 passningar, xT 0.14BoujellabArlind Rexhepi: 88 passningar, xT 0.31RexhepiDennis Duah: 83 passningar, xT 0.06DuahLeon Sommer: 78 passningar, xT 1.02SommerEmre Aytun: 59 passningar, xT 0.25Aytun
    VfB Stuttgart II
    Christopher Olivier: 251 passningar, xT 1.02OlivierNicolas Sessa: 216 passningar, xT 0.26SessaLeny Meyer: 204 passningar, xT 0.93MeyerSamuele Di Benedetto: 189 passningar, xT 0.43BenedettoMaximilian Herwerth: 140 passningar, xT 0.16HerwerthNoah Yanis Darvich: 131 passningar, xT 1.71DarvichTim Kohler: 131 passningar, xT 0.4KohlerMirza Ćatović: 114 passningar, xT 0.23ĆatovićDominik Nothnagel: 91 passningar, xT 0.14NothnagelJustin Diehl: 84 passningar, xT 0.49DiehlJeremy Alberto Arévalo Mera: 69 passningar, xT 0.22Mera

    The teams in numbers

    PerformanceHavelseVfB Stuttgart II
    Points3546
    xPoints48.645
    xG per match1.31.6
    xGA per match21.7
    xG within 8s of winning the ball0.210.27
    xGA within 8s of losing the ball0.210.31
    Playing styleHavelseVfB Stuttgart II
    Build-up efficiency0.310.32
    Field tilt0.410.56
    xT per match0.831.2
    xTA per match1.41.1
    Won balls, offensive half2423
    Pressing intensity0.230.22
    Pressing efficiency0.290.33
    Pressing efficiency, offensive half0.340.39
    Entries into the box per match1013
    Entries into the box against1613
    Pass completion %0.70.78
    Pass completion % under pressure0.650.73
    Passes per match278393
    Passes against per match374300
    Switches of play per match11.922.5
    Long balls per match2531
    Set piecesHavelseVfB Stuttgart II
    xG from free kicks0.10.07
    Corners per match4.55.1
    Corners against per match6.35
    xG per corner0.060.04
    xGA per corner against0.060.07
    First touch, offensive corners %0.320.45
    First touch, defensive corners %0.590.6
    OtherHavelseVfB Stuttgart II
    Throw-in control0.670.72
    The goalkeepersTom Opitz (Havelse)Florian Pascal Hellstern (VfB Stuttgart II)
    Saves11696
    Save %68%69%
    xG prevented47%48%
    Claims0 (0%)0 (0%)

    Frequently asked questions

    Who wins Havelse vs VfB Stuttgart II according to our model?

    The model gives VfB Stuttgart II a 44% win probability. Full 1X2 picture: Havelse 30%, draw 26%, VfB Stuttgart II 44%.

    What is the most likely scoreline?

    The model's most likely final score is 1-1 at 10% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 66% and under at 34%.

    Will both teams score?

    The probability of both teams scoring is 66% 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.