3. Liga17°0,1 mm23 km/h

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    Preussen MünsterPreussen MünsterCounter-attacks & crosses
    2–1
    HavelseHavelseCounter-attacks & crosses
    The model's lean: 1 · Preussen Münster (55%)Best value by the model: Under 0,5 @ 20.00 (+31 %)

    Preussen Münster – Havelse · 3. Liga

    1 · Preussen Münster 55%X 24%21% Havelse · 2

    Analysis: Preussen Münster – Havelse

    Erik Lindberg · · Written from the model's numbers · How the predictions work

    Preussen Münster's clash with Havelse presents a fascinating conundrum for those who appreciate a well-organized defense over flamboyance. With both teams favoring counter attacks and crosses, the evening is set to showcase tactical discipline rather than a flurry of goals. The hosts, Münster, statistically edge Havelse with a 55% probability of victory, a nod to their slightly stronger position in the league standings and potential home advantage.

    However, Havelse's recent form is a cause for concern, having suffered three consecutive losses. Such a streak could weigh on their mentality, even as their xG of 2.0 per match suggests they are capable of creating chances. Their defensive solidity, reflected in an xGA of just 0.6 per game, starkly contrasts Münster's more porous defense. Yet, it's Münster who are expected to edge the xG battle at 1.72 versus Havelse's 1.06, indicating that while Havelse can be defensively tight, they might struggle to convert opportunities.

    The model suggests a tight contest, with a 12% probability of a 1-1 draw and 10% for both a narrow 1-0 home win and a 2-1 result. This aligns with the over/under balance: the market slightly favors over 2.5 goals at 53%, but the numbers hint at a potential underperformance in front of goal. Here lies the betting value: under 2.5 goals at odds of 2.4 with Betsafe, Betsson, and Nordicbet, offering a significant 14% edge.

    Ultimately, while Münster might squeeze out a win, perhaps 1-0, the value bet lies in the game's goal tally remaining subdued. With such odds on the under, there's a sound argument to favor the cautious play.

    Preussen MünsterPreussen Münster
    Form WDL
    League ranking xG #14xGA #19xT #21xP/match #15Points #12
    Key players
    • Felix HiglFxG 0.21 · xT 0.01
    • Charalambos MakridisLWxG 0.05 · xT 0.03
    • Montell NdikomRWxG 0.90 · xT 0.09
    HavelseHavelse
    Form LWLLL
    League ranking xG #4xGA #1xT #12xP/match #1Points #13
    Key players
    • Jesse Edem TugbenyoFxG 0.24 · xT 0.01
    • Kwasi Okyere WriedtFxG 0.26 · xT -0.01
    • Kevin SchumacherLWxG 0.01 · xT 0.15
    Final score
    2 – 1
    The model called the outcome
    Predicted probabilities: Preussen Münster 55% · Draw 24% · Havelse 21%

    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 - TSV HavelseBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 12,42fair 17,76-30 %
    Miss
    Matchresultat - Preussen MunsterBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 4,11fair 6,85-40 %
    Miss

    Match prediction: Preussen Münster – Havelse

    Predicted score matrix

    Havelse →
    Preussen Münster →
    0
    1
    2
    3
    4+
    0
    0–06.5%
    0–16.3%
    0–23.5%
    0–31.2%
    0–4+0.4%
    1
    1–010.3%
    1–111.6%
    1–26.0%
    1–32.1%
    1–4+0.7%
    2
    2–09.2%
    2–19.7%
    2–25.2%
    2–31.8%
    2–4+0.6%
    3
    3–05.2%
    3–15.6%
    3–23.0%
    3–31.0%
    3–4+0.4%
    4+
    4+–03.3%
    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. 5.0-07%
    Expected goals
    1,72–1,06
    Both teams to score
    54%

    Over/under goals

    Expected goals: 2,8
    Under 2,547%
    @2.63EV+14%
    Over 2,553%
    @1.50

    Ready-made bet suggestions

    More combos & build your own →

    01 · 2 legs

    Safe

    • Preussen Münster to win55%
    • Over 1.5 goals77%

    Combined probability

    42%

    Fair odds

    2.38

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

    02 · 3 legs

    Balanced

    • Preussen Münster to win55%
    • Over 2.5 goals53%
    • Oliver Batista Meier to score27%

    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 score54%
    • Over 2.5 goals53%
    • Oliver Batista Meier to score27%
    • Marcel Benger to be booked21%

    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+).

    • Under 0.57% probability@20.00Paddy PowerEV+31%reference odds
    • Under 1.523% probability@5.50Paddy PowerEV+27%reference odds
    • Under 2.547% probability@2.63Paddy PowerEV+24%reference odds
    Bookmaker1 · Preussen MünsterX2 · Havelse
    Betsafe1.584.054.70
    Betsson1.584.054.70
    Nordicbet1.584.054.70
    Paddy Power1.57
    EV+ 2%
    4.20    		4.50
    Pinnacle1.63
    EV+ 4%
    4.30    		4.70

    Odds updated 5 Sept, 10:32

    Odds movement

    1+2 %
    61 %56 %

    1.59 → 1.63

    X+1 %
    24 %19 %

    4.27 → 4.30

    2+1 %
    22 %17 %

    4.64 → 4.70

    Pinnacle · 8 recorded price levels · 02/09/2026 → 05/09/2026 · fixed scale 5 percentage points

    Statistics

    Key facts

    • Havelse have lost 3 in a row.
    xG & xGA per match — 3-game rolling average

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

    Preussen Münster
    Havelse
    When goals are scored and conceded — 2026
    Preussen Münster (5–6)
    Havelse (2–4)
    Pass networks

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

    Preussen Münster
    Niko Koulis: 118 passningar, xT 0.1KoulisMorten Jens Behrens: 115 passningar, xT 0.21BehrensRico Preißinger: 89 passningar, xT 0.02PreißingerAntonio Tikvić: 62 passningar, xT 0.06TikvićTim-Justin Dietrich: 62 passningar, xT 0.14DietrichCharalambos Makridis: 52 passningar, xT 0.09MakridisWesley Adeh: 49 passningar, xT 0.04AdehLouis Philipp Kolbe: 47 passningar, xT 0.28KolbeRyan Johansson: 46 passningar, xT -0.04JohanssonLucas Christopher Zeller: 45 passningar, xT 0.02ZellerTorge Paetow: 35 passningar, xT 0.02Paetow
    Havelse
    Semi Belkahia: 74 passningar, xT 0.06BelkahiaDennis Duah: 62 passningar, xT 0.04DuahOmer Hanin: 55 passningar, xT 0.07HaninJohann Berger: 46 passningar, xT 0.04BergerKevin Schumacher: 45 passningar, xT 0.31SchumacherMax Lamby: 42 passningar, xT 0LambyLeon Sommer: 39 passningar, xT 0.16SommerJesse Edem Tugbenyo: 33 passningar, xT 0.01TugbenyoEric Voufack: 25 passningar, xT 0.11VoufackKwasi Okyere Wriedt: 16 passningar, xT -0.03WriedtNiklas Tauer: 13 passningar, xT 0.16Tauer
    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.

    Preussen Münster
    Niko Koulis: 118 passningar, xT 0.1KoulisMorten Jens Behrens: 115 passningar, xT 0.21BehrensRico Preißinger: 89 passningar, xT 0.02PreißingerAntonio Tikvić: 62 passningar, xT 0.06TikvićTim-Justin Dietrich: 62 passningar, xT 0.14DietrichCharalambos Makridis: 52 passningar, xT 0.09MakridisWesley Adeh: 49 passningar, xT 0.04AdehLouis Philipp Kolbe: 47 passningar, xT 0.28KolbeRyan Johansson: 46 passningar, xT -0.04JohanssonLucas Christopher Zeller: 45 passningar, xT 0.02ZellerTorge Paetow: 35 passningar, xT 0.02Paetow
    Havelse
    Semi Belkahia: 74 passningar, xT 0.06BelkahiaDennis Duah: 62 passningar, xT 0.04DuahOmer Hanin: 55 passningar, xT 0.07HaninJohann Berger: 46 passningar, xT 0.04BergerKevin Schumacher: 45 passningar, xT 0.31SchumacherMax Lamby: 42 passningar, xT 0LambyLeon Sommer: 39 passningar, xT 0.16SommerJesse Edem Tugbenyo: 33 passningar, xT 0.01TugbenyoEric Voufack: 25 passningar, xT 0.11VoufackKwasi Okyere Wriedt: 16 passningar, xT -0.03WriedtNiklas Tauer: 13 passningar, xT 0.16Tauer

    The teams in numbers

    PerformancePreussen MünsterHavelse
    Points43
    xPoints2.32.5
    xG per match1.32
    xGA per match20.6
    xG within 8s of winning the ball0.10.1
    xGA within 8s of losing the ball0.410.13
    Playing stylePreussen MünsterHavelse
    Build-up efficiency0.260.26
    Field tilt0.210.29
    xT per match0.411.1
    xTA per match1.10.88
    Won balls, offensive half1722
    Pressing intensity0.230.24
    Pressing efficiency0.330.3
    Pressing efficiency, offensive half0.260.17
    Entries into the box per match314
    Entries into the box against1510
    Pass completion %0.670.73
    Pass completion % under pressure0.720.66
    Passes per match253301
    Passes against per match352356
    Switches of play per match523
    Long balls per match2239
    Set piecesPreussen MünsterHavelse
    xG from free kicks00.06
    Corners per match35
    Corners against per match5.55
    xG per corner0.010
    xGA per corner against0.040.01
    First touch, offensive corners %0.670.2
    First touch, defensive corners %0.550.4
    OtherPreussen MünsterHavelse
    Throw-in control0.60.69
    The goalkeepersMorten Jens Behrens (Preussen Münster)Omer Hanin (Havelse)
    Saves712
    Save %54%75%
    xG prevented28%60%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Preussen Münster
    Fixtures, form & tips
    Havelse
    Fixtures, form & tips

    Frequently asked questions

    Who wins Preussen Münster vs Havelse according to our model?

    The model gives Preussen Münster a 55% win probability. Full 1X2 picture: Preussen Münster 55%, draw 24%, Havelse 21%.

    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 54% 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.