3. Liga18°11 km/h

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    SaarbrückenSaarbrückenPossession control
    vs
    IngolstadtIngolstadtPossession control
    The model's lean: 1 · Saarbrücken (44%)Best value by the model: X · Draw @ 4.01 (+2 %)

    SaarbrückenIngolstadt · 3. Liga

    1 · Saarbrücken 44%X 25%30% Ingolstadt · 2

    Analysis: SaarbrückenIngolstadt

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

    TEXT: Saarbrücken's attack, a consistent producer with goals in their last eight league outings, faces a familiar opponent in Ingolstadt. While the hosts hold an edge with nine points compared to Ingolstadt's five, their previous encounters with Ingolstadt tell a different story: just one victory in four meetings since 2024. This small head-to-head sample, however, weighs less than the current form and expected goals, where Saarbrücken holds the upper hand.

    The clash is intriguing tactically as both sides favor a possession-based approach. This setup could lead to a tightly contested midfield battle, likely affecting the rhythm and flow of the game. Despite both teams' preference for controlling play, the model projects a 60% chance for over 2.5 goals and a 62% probability of both teams finding the net, indicating a potentially open affair.

    Ingolstadt's defense, with an average of 1.3 expected goals against per match, edges out Saarbrücken's more porous backline, which concedes 1.6 xGA on average. Yet, it's Saarbrücken's superior offensive output—averaging 2.2 expected goals per match—that could tip the scales in their favor.

    The most likely scorelines suggest a narrow outcome, with a 2-1 victory for Saarbrücken at 9% probability standing just behind the evenly matched 1-1 draw at 11%. Despite Ingolstadt's resilience in past head-to-heads, current dynamics favor the home side.

    For bettors, there's value to be found in backing Saarbrücken, whose 44% win probability leads the model's projections for this fixture. This matchup's narrative leans toward a narrow Saarbrücken victory, with the home side seizing control of the 3. Liga fixture.

    SaarbrückenSaarbrücken
    Form LWWLW
    League ranking xG #1xGA #11xT #6xP/match #2Points #2
    Key players
    • Florian PickRWxG 0.31 · xT 0.36
    • Kai BrunkerFxG 0.53 · xT 0.16
    • Christian KühlwetterCAMxG 0.57 · xT 0.07
    IngolstadtIngolstadt
    Form WDDWL
    League ranking xG #13xGA #10xT #16xP/match #8Points #13
    Key players
    • Obed Chidindu UgonduFxG 0.74 · xT 0.01
    • Keanan BennettsLWBxG 0.01 · xT 0.16
    • Davide-Danilo SekulovicRWBxG 0.12 · xT 0.19

    Match prediction: SaarbrückenIngolstadt

    Predicted score matrix

    Ingolstadt
    Saarbrücken
    0
    1
    2
    3
    4+
    0
    0–04.9%
    0–16.1%
    0–24.5%
    0–32.1%
    0–4+1.0%
    1
    1–07.3%
    1–111.1%
    1–27.6%
    1–33.5%
    1–4+1.7%
    2
    2–06.5%
    2–19.1%
    2–26.4%
    2–33.0%
    2–4+1.4%
    3
    3–03.6%
    3–15.1%
    3–23.6%
    3–31.7%
    3–4+0.8%
    4+
    4+–02.2%
    4+–13.1%
    4+–22.2%
    4+–31.0%
    4+–4+0.5%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-111%
    2. 2.2-19%
    3. 3.1-28%
    4. 4.1-07%
    5. 5.2-06%
    Expected goals
    1,691,41
    Both teams to score
    62%

    Over/under goals

    Expected goals: 3,1
    Under 2,540%
    @2.28
    Over 2,560%
    @1.55

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Double chance Saarbrücken or draw (1X)68%
    • Over 1.5 goals82%

    Combined probability

    56%

    Fair odds

    1.78

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

    02 · 3 legs

    Balanced

    • Double chance Saarbrücken or draw (1X)68%
    • Over 2.5 goals60%
    • Florian Pick to score25%

    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 goals60%
    • Florian Pick to score25%
    • Elijah Akwasi Krahn to be booked23%

    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+).

    • X · Draw25% probability@4.01PinnacleEV+2%reference odds
    Bookmaker1 · SaarbrückenX2 · Ingolstadt
    Betsafe2.153.552.85
    Betsson2.153.552.85
    Nordicbet2.153.552.85
    Pinnacle2.18
    EV+ 2%
    4.01
    2.84

    Odds updated 11 Sept, 16:31

    Odds movement

    Market signal

    The market has moved clearly towards a Saarbrücken win since 5 September — the odds have shortened from 2.42 to 2.18 (−10%).

    1-10 %
    43 %38 %

    2.422.18

    X+6 %
    27 %22 %

    3.794.01

    2+12 %
    38 %33 %

    2.542.84

    Pinnacle · 12 recorded price levels · 05/09/2026 → 11/09/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    4 matches
    Saarbrücken 1Draw 0Ingolstadt 3
    Goals: 46 (⌀ 2,5)

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

    Key facts

    • Saarbrucken have scored in 8 consecutive league matches.
    xG & xGA per match — 3-game rolling average

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

    Saarbrücken
    Ingolstadt
    When goals are scored and conceded 2026
    Saarbrücken (147)
    Ingolstadt (56)
    Pass networks

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

    Saarbrücken
    Siemen Voet: 198 passningar, xT 0.28VoetMladen Cvjetinovic: 179 passningar, xT 0.27CvjetinovicPatrick Sontheimer: 143 passningar, xT 0.27SontheimerNiko Bretschneider: 140 passningar, xT 0.4BretschneiderDaniel Gleiber: 132 passningar, xT 0.08GleiberPhilip Fahrner: 131 passningar, xT 0.29FahrnerMatteo Bignetti: 128 passningar, xT 0.06BignettiFlorian Pick: 93 passningar, xT 1.41PickChristian Kühlwetter: 45 passningar, xT 0.25KühlwetterAlexander Staff: 42 passningar, xT 0.48StaffKai Brunker: 28 passningar, xT 0.19Brunker
    Ingolstadt
    Simon Lorenz: 130 passningar, xT 0.09LorenzDavid Klein: 121 passningar, xT 0.18KleinGeorgios Antzoulas: 119 passningar, xT 0.36AntzoulasJonas Scholz: 116 passningar, xT 0.35ScholzVinko Sapina: 104 passningar, xT 0.16SapinaDavide-Danilo Sekulovic: 72 passningar, xT 0.38SekulovicKeanan Bennetts: 70 passningar, xT 0.43BennettsFredrik Carlsen: 61 passningar, xT 0.01CarlsenEmre Gul: 42 passningar, xT 0.84GulLars Lokotsch: 41 passningar, xT 0LokotschYannick Deichmann: 36 passningar, xT 0.22Deichmann
    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.

    Saarbrücken
    Siemen Voet: 198 passningar, xT 0.28VoetMladen Cvjetinovic: 179 passningar, xT 0.27CvjetinovicPatrick Sontheimer: 143 passningar, xT 0.27SontheimerNiko Bretschneider: 140 passningar, xT 0.4BretschneiderDaniel Gleiber: 132 passningar, xT 0.08GleiberPhilip Fahrner: 131 passningar, xT 0.29FahrnerMatteo Bignetti: 128 passningar, xT 0.06BignettiFlorian Pick: 93 passningar, xT 1.41PickChristian Kühlwetter: 45 passningar, xT 0.25KühlwetterAlexander Staff: 42 passningar, xT 0.48StaffKai Brunker: 28 passningar, xT 0.19Brunker
    Ingolstadt
    Simon Lorenz: 130 passningar, xT 0.09LorenzDavid Klein: 121 passningar, xT 0.18KleinGeorgios Antzoulas: 119 passningar, xT 0.36AntzoulasJonas Scholz: 116 passningar, xT 0.35ScholzVinko Sapina: 104 passningar, xT 0.16SapinaDavide-Danilo Sekulovic: 72 passningar, xT 0.38SekulovicKeanan Bennetts: 70 passningar, xT 0.43BennettsFredrik Carlsen: 61 passningar, xT 0.01CarlsenEmre Gul: 42 passningar, xT 0.84GulLars Lokotsch: 41 passningar, xT 0LokotschYannick Deichmann: 36 passningar, xT 0.22Deichmann

    The teams in numbers

    PerformanceSaarbrückenIngolstadt
    Points95
    xPoints7.16.1
    xG per match2.21.3
    xGA per match1.61.3
    xG within 8s of winning the ball0.290.37
    xGA within 8s of losing the ball0.110.21
    Playing styleSaarbrückenIngolstadt
    Build-up efficiency0.320.31
    Field tilt0.590.26
    xT per match1.20.84
    xTA per match1.11.3
    Won balls, offensive half1626
    Pressing intensity0.210.22
    Pressing efficiency0.270.28
    Pressing efficiency, offensive half0.210.26
    Entries into the box per match1410
    Entries into the box against1417
    Pass completion %0.770.68
    Pass completion % under pressure0.720.68
    Passes per match338256
    Passes against per match325402
    Switches of play per match3318.7
    Long balls per match4035
    Set piecesSaarbrückenIngolstadt
    xG from free kicks0.150.03
    Corners per match6.22.8
    Corners against per match57.1
    xG per corner0.050.03
    xGA per corner against0.040.02
    First touch, offensive corners %0.420.27
    First touch, defensive corners %0.550.57
    OtherSaarbrückenIngolstadt
    Throw-in control0.750.65
    The goalkeepersMatteo Bignetti (Saarbrücken)David Klein (Ingolstadt)
    Saves1515
    Save %68%71%
    xG prevented38%47%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Saarbrücken vs Ingolstadt according to our model?

    The model gives Saarbrücken a 44% win probability. Full 1X2 picture: Saarbrücken 44%, draw 25%, Ingolstadt 30%.

    What is the most likely scoreline?

    The model's most likely final score is 1-1 at 11% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 60% and under at 40%.

    Will both teams score?

    The probability of both teams scoring is 62% 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.