3. Liga8°1,0 mm7 km/h

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    Alemannia AachenAlemannia AachenLow block & direct
    vs
    Preussen MünsterPreussen MünsterPossession control
    The model's lean: 1 · Alemannia Aachen (54%)

    Alemannia Aachen vs Preussen Münster · 3. Liga

    1 · Alemannia Aachen 54%X 23%23% Preussen Münster · 2

    Prediction summary

    BetBuilders AI model prediction for Alemannia Aachen vs Preussen Münster (3. Liga, Sunday, 1 November 2026): Alemannia Aachen win 54%, draw 23%, Preussen Münster win 23%. Expected goals (xG): Alemannia Aachen 1.89, Preussen Münster 1.31. Most likely score: 1-1 (10%). Over 2.5 goals 62%, both teams to score 62%. Double chance: Alemannia Aachen or draw 77%, Preussen Münster or draw 46%. Prediction updated Friday, 23 October 2026.

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    Analysis: Alemannia Aachen – Preussen Münster

    Sofia Andersson · · The model's read on the match · How the predictions work

    TEXT: With Alemannia Aachen poised to meet Preussen Münster, the numbers reveal a clash of contrasting styles. Aachen's tendency for low defensive setups coupled with direct attacks will test Münster's possession-heavy approach. The model sees Aachen as favourites with a 54% chance of victory, and it's easy to see why. Their edge in both points and expected points underscores a more consistent season so far.

    The likelihood of a tight affair is reflected in the most probable scorelines, with 1-1 and 2-1 both sitting at 10%. However, Aachen's expected goals (1.89) suggest they might edge past Münster's 1.31 xG. This leans towards a 2-1 win for the hosts, especially considering their ability to convert chances. The 62% probability for over 2.5 goals aligns with an open game, though Münster's ball control might temper this unless Aachen can break effectively.

    Aachen's slight superiority in xG per match (1.6 vs. Münster's 1.2) and marginally better xGA (1.5 vs. 1.6) suggest a nuanced advantage. Their direct play could exploit gaps if Münster overcommits to possession. With both teams likely to find the net (62% probability), the balance may tip in Aachen's favour if their directness proves effective while Münster holds the ball.

    For bettors, the value lies in backing Aachen's win at odds of 54% implied, which might not be fully reflected in bookmaker prices. Coupling this with an over 2.5 goals bet seems the sharpest angle, given the expected dynamics. The numbers hint at a 2-1 result for Aachen, positioning their directness as the potential match-winner.

    Alemannia AachenAlemannia Aachen
    Form LWLLW
    League ranking xG #10xGA #10xT #12xP/match #6Points #8
    Key players
    • Lukas ScepanikRWxG 0.23 · xT 0.11
    • Matti WagnerLWBxG 0.03 · xT 0.21
    • Mehdi LouneCAMxG 0.16 · xT 0.13
    Preussen MünsterPreussen Münster
    Form DLDLL
    League ranking xG #16xGA #13xT #20xP/match #16Points #12
    Key players
    • Torge PaetowCBxG 0.04 · xT 0.08
    • Ryan JohanssonFxG 0.11 · xT 0.03
    • Felix HiglFxG 0.28 · xT 0.07

    Match prediction: Alemannia Aachen – Preussen Münster

    Predicted score matrix

    Preussen Münster →
    Alemannia Aachen →
    0
    1
    2
    3
    4+
    0
    0–04.4%
    0–15.1%
    0–23.5%
    0–31.5%
    0–4+0.7%
    1
    1–07.4%
    1–110.4%
    1–26.6%
    1–32.9%
    1–4+1.3%
    2
    2–07.3%
    2–19.5%
    2–26.2%
    2–32.7%
    2–4+1.2%
    3
    3–04.6%
    3–16.0%
    3–23.9%
    3–31.7%
    3–4+0.7%
    4+
    4+–03.3%
    4+–14.3%
    4+–22.9%
    4+–31.2%
    4+–4+0.5%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-110%
    2. 2.2-110%
    3. 3.1-07%
    4. 4.2-07%
    5. 5.1-27%
    Expected goals
    1,89–1,31
    Both teams to score
    62%

    Over/under goals

    Expected goals: 3,2
    Under 2,538%
    –
    Over 2,562%
    –

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    01 · 2 legs

    Safe

    • Alemannia Aachen to win54%
    • Over 1.5 goals83%

    Combined probability

    43%

    Fair odds

    2.32

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

    02 · 3 legs

    Balanced

    • Alemannia Aachen to win54%
    • Over 2.5 goals62%
    • Georg Ermolaev to score19%

    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 score62%
    • Over 2.5 goals62%
    • Marvin Schulz to score22%
    • Danilo Wiebe 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

    No odds available yet.

    Statistics

    xG & xGA per match — 3-game rolling average

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

    Alemannia Aachen
    Preussen Münster
    When goals are scored and conceded — 2026
    Alemannia Aachen (15–16)
    Preussen Münster (18–21)
    Pass networks

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

    Alemannia Aachen
    Joel Miguel da Silva Kiala: 214 passningar, xT 0.44KialaPetros Bagalianis: 187 passningar, xT 0.2BagalianisMehdi Loune: 153 passningar, xT 0.4LouneDylan Leonard: 151 passningar, xT 0.25LeonardMatti Wagner: 131 passningar, xT 0.97WagnerManuel Riemann-Lorenzen: 122 passningar, xT 0.22Riemann-LorenzenDanilo Wiebe: 93 passningar, xT 0.22WiebeLukas Scepanik: 75 passningar, xT 0.46ScepanikGeorg Ermolaev: 58 passningar, xT 0.18ErmolaevKacper Kościerski: 50 passningar, xT 0.08KościerskiMika Schroers: 44 passningar, xT 0.13Schroers
    Preussen Münster
    Torge Paetow: 198 passningar, xT 0.59PaetowLucas Christopher Zeller: 177 passningar, xT 0.23ZellerAntonio Tikvić: 174 passningar, xT 0.23TikvićNiklas Varelmann: 157 passningar, xT 0.18VarelmannMorten Jens Behrens: 147 passningar, xT 0.15BehrensPhilipp Maier: 70 passningar, xT 0.06MaierLouis Philipp Kolbe: 60 passningar, xT 0.47KolbeCharalambos Makridis: 59 passningar, xT 0.63MakridisMontell Ndikom: 51 passningar, xT 0.29NdikomFelix Higl: 49 passningar, xT 0.28HiglSamuel Moise Althaus: 48 passningar, xT -0.03Althaus
    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.

    Alemannia Aachen
    Joel Miguel da Silva Kiala: 214 passningar, xT 0.44KialaPetros Bagalianis: 187 passningar, xT 0.2BagalianisMehdi Loune: 153 passningar, xT 0.4LouneDylan Leonard: 151 passningar, xT 0.25LeonardMatti Wagner: 131 passningar, xT 0.97WagnerManuel Riemann-Lorenzen: 122 passningar, xT 0.22Riemann-LorenzenDanilo Wiebe: 93 passningar, xT 0.22WiebeLukas Scepanik: 75 passningar, xT 0.46ScepanikGeorg Ermolaev: 58 passningar, xT 0.18ErmolaevKacper Kościerski: 50 passningar, xT 0.08KościerskiMika Schroers: 44 passningar, xT 0.13Schroers
    Preussen Münster
    Torge Paetow: 198 passningar, xT 0.59PaetowLucas Christopher Zeller: 177 passningar, xT 0.23ZellerAntonio Tikvić: 174 passningar, xT 0.23TikvićNiklas Varelmann: 157 passningar, xT 0.18VarelmannMorten Jens Behrens: 147 passningar, xT 0.15BehrensPhilipp Maier: 70 passningar, xT 0.06MaierLouis Philipp Kolbe: 60 passningar, xT 0.47KolbeCharalambos Makridis: 59 passningar, xT 0.63MakridisMontell Ndikom: 51 passningar, xT 0.29NdikomFelix Higl: 49 passningar, xT 0.28HiglSamuel Moise Althaus: 48 passningar, xT -0.03Althaus

    The teams in numbers

    PerformanceAlemannia AachenPreussen Münster
    Points1412
    xPoints15.112.5
    xG per match1.61.2
    xGA per match1.51.6
    xG within 8s of winning the ball0.310.23
    xGA within 8s of losing the ball0.280.22
    Playing styleAlemannia AachenPreussen Münster
    Build-up efficiency0.310.26
    Field tilt0.570.39
    xT per match10.65
    xTA per match1.11.1
    Won balls, offensive half2426
    Pressing intensity0.220.22
    Pressing efficiency0.340.28
    Pressing efficiency, offensive half0.30.24
    Entries into the box per match1110
    Entries into the box against1311
    Pass completion %0.720.7
    Pass completion % under pressure0.680.68
    Passes per match322290
    Passes against per match324368
    Switches of play per match16.917
    Long balls per match2631
    Set piecesAlemannia AachenPreussen Münster
    xG from free kicks0.10.05
    Corners per match4.83.6
    Corners against per match3.44.7
    xG per corner0.030.02
    xGA per corner against0.030.03
    First touch, offensive corners %0.540.36
    First touch, defensive corners %0.590.66
    OtherAlemannia AachenPreussen Münster
    Throw-in control0.740.74
    The goalkeepersStefan Bajić (Alemannia Aachen)Morten Jens Behrens (Preussen Münster)
    Saves1621
    Save %67%50%
    xG prevented64%24%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Alemannia Aachen vs Preussen Münster according to our model?

    The model gives Alemannia Aachen a 54% win probability. Full 1X2 picture: Alemannia Aachen 54%, draw 23%, Preussen Münster 23%.

    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 62% and under at 38%.

    Will both teams score?

    The probability of both teams scoring is 62% according to the model.

    How many goals are expected in Alemannia Aachen vs Preussen Münster?

    The model expects 1.89 goals (xG) for Alemannia Aachen and 1.31 for Preussen Münster, 3.20 in total.

    What does the model say about double chance?

    Alemannia Aachen or draw (1X) 77%, Preussen Münster or draw (X2) 46% and no draw (12) 77%.

    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.