3. Liga23°11 km/h

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    Viktoria KölnViktoria KölnPossession control
    25
    Jahn RegensburgJahn RegensburgPossession control
    The model's lean: 1 · Viktoria Köln (44%)

    Viktoria Köln vs Jahn Regensburg · 3. Liga

    1 · Viktoria Köln 44%X 25%32% Jahn Regensburg · 2

    Analysis: Viktoria KölnJahn Regensburg

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

    Two matches, one win and a draw. That's the entirety of the head-to-head record between Viktoria Koln and Jahn Regensburg since 2024. Yet, don't be misled by the small sample size. Viktoria Koln's slight statistical edges across various metrics—points, xPoints, and expected goals against—suggest they have the upper hand heading into this 3. Liga encounter. With both teams favoring possession control, we can expect a tactical battle, though Viktoria Koln's knack for converting their 1.57 expected goals per match signals a potential advantage in breaking down Jahn Regensburg's slightly leakier defense.

    Viktoria Koln holds a slim lead in both actual and expected points, making their home advantage even more significant. Jahn Regensburg, however, edges them in expected goals per match at 1.7, indicating that they can create scoring opportunities and might trouble the Viktoria Koln defense, which concedes an average of 1.4 xGA per game. Given these dynamics, the most probable outcomes—1-1, 2-1, or 1-0—are indeed reflective of a match that could sway in favor of the home side, especially with the market offering a slight value edge.

    The forecasted 55% chance of over 2.5 goals and 58% for both teams to score suggest that goals could be on the menu, despite both teams' shared possession-heavy approach. Weather conditions aren't a factor here, leaving tactics and execution to dictate terms. Viktoria Koln's systematic build-up might find the right cracks in Jahn Regensburg's defense, which statistically allows more chances than its opponent.

    Viktoria Koln presents a viable betting angle with Pinnacle offering odds of 2.3, slightly above the model's 44% win probability. This 1% edge hints at value, though not gold-plated certainty. The most likely scoreline, a 1-0 or 2-1 victory for Viktoria Koln, encapsulates the game’s predictive contours. With the over/under leaning slightly over 2.5 goals, this fixture promises to exceed its subdued head-to-head history.

    Viktoria KölnViktoria Köln
    Form LLWLD
    League ranking xG #8xGA #5xT #13xP/match #4Points #11
    Key players
    • David OttoFxG 0.26 · xT 0.13
    • Lex Tyger LobingerFxG 0.78 · xT 0.04
    • Benjamin Merlin ZankFxG 0.27 · xT 0.04
    Jahn RegensburgJahn Regensburg
    Form LWWLL
    League ranking xG #6xGA #9xT #4xP/match #7Points #13
    Key players
    • Christian KühlwetterFxG 0.28 · xT 0.11
    • Eric HottmannFxG 0.37 · xT 0.09
    • Adrian FeinCAMxG 0.04 · xT 0.16
    Final score
    25
    The model missed the outcome
    Predicted probabilities: Viktoria Köln 44% · Draw 25% · Jahn Regensburg 32%

    Match prediction: Viktoria KölnJahn Regensburg

    Predicted score matrix

    Jahn Regensburg
    Viktoria Köln
    0
    1
    2
    3
    4+
    0
    0–06.0%
    0–17.1%
    0–24.8%
    0–32.1%
    0–4+0.9%
    1
    1–08.6%
    1–111.9%
    1–27.6%
    1–33.3%
    1–4+1.4%
    2
    2–06.9%
    2–19.1%
    2–25.9%
    2–32.6%
    2–4+1.1%
    3
    3–03.6%
    3–14.7%
    3–23.1%
    3–31.3%
    3–4+0.6%
    4+
    4+–02.0%
    4+–12.6%
    4+–21.7%
    4+–30.7%
    4+–4+0.3%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-112%
    2. 2.2-19%
    3. 3.1-09%
    4. 4.1-28%
    5. 5.0-17%
    Expected goals
    1,571,30
    Both teams to score
    58%

    Over/under goals

    Expected goals: 2,9
    Under 2,545%
    Over 2,555%

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Double chance Viktoria Köln or draw (1X)69%
    • Over 1.5 goals78%

    Combined probability

    54%

    Fair odds

    1.85

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

    02 · 3 legs

    Balanced

    • Double chance Viktoria Köln or draw (1X)69%
    • Over 2.5 goals55%
    • Jakob Sachse to score22%

    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 score58%
    • Over 2.5 goals55%
    • Jakob Sachse to score22%
    • Tobias Eisenhuth 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+).

    • 1 · Viktoria Köln44% probability@2.30PinnacleEV+1%reference odds
    Bookmaker1 · Viktoria KölnX2 · Jahn Regensburg
    Pinnacle
    EV+ 1%
    2.30
    3.622.92

    Odds updated 8 Aug, 10:09

    Odds movement

    1-4 %
    43 %38 %

    2.392.30

    X-3 %
    28 %23 %

    3.733.62

    2+11 %
    36 %31 %

    2.642.92

    Pinnacle · 11 recorded price levels · 04/08/2026 → 08/08/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    2 matches
    Viktoria Köln 1Draw 1Jahn Regensburg 0
    Goals: 10 (⌀ 0,5)

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

    xG & xGA per match — 3-game rolling average

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

    Viktoria Köln
    Jahn Regensburg
    When goals are scored and conceded 2025
    Viktoria Köln (5153)
    Jahn Regensburg (5458)
    Pass networks

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

    Viktoria Köln
    Tobias Eisenhuth: 196 passningar, xT 0.25EisenhuthLars Dietz: 180 passningar, xT 0.48DietzVerthomy Schilo Boboy: 172 passningar, xT 0.18BoboyTaylan Duman: 120 passningar, xT 0.1DumanSimon Handle: 120 passningar, xT 1.36HandleArne Schulz: 115 passningar, xT 0.17SchulzLeonhard Munst: 110 passningar, xT 0.13MunstLucas Wolf: 108 passningar, xT 0.38WolfDavid Otto: 97 passningar, xT 0.1OttoJoel Agyekum: 95 passningar, xT 0.12AgyekumRobin Velasco: 79 passningar, xT 0.75Velasco
    Jahn Regensburg
    Adrian Fein: 247 passningar, xT 1.29FeinLeopold Wurm: 191 passningar, xT 0.32WurmFelix Strauß: 167 passningar, xT 0.53StraußNicolas-Bernd Oliveira Kisilowski: 130 passningar, xT 0.87KisilowskiBenedikt Saller: 108 passningar, xT 0.23SallerNoel Eichinger: 107 passningar, xT 0.86EichingerNick Seidel: 106 passningar, xT 0.56SeidelFelix Karl-Ernst Gebhardt: 99 passningar, xT 0.04GebhardtOscar Schönfelder: 84 passningar, xT 0.86SchönfelderBenedikt Bauer: 73 passningar, xT 0.47BauerRobin Ziegele: 49 passningar, xT 0.24Ziegele
    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.

    Viktoria Köln
    Tobias Eisenhuth: 196 passningar, xT 0.25EisenhuthLars Dietz: 180 passningar, xT 0.48DietzVerthomy Schilo Boboy: 172 passningar, xT 0.18BoboyTaylan Duman: 120 passningar, xT 0.1DumanSimon Handle: 120 passningar, xT 1.36HandleArne Schulz: 115 passningar, xT 0.17SchulzLeonhard Munst: 110 passningar, xT 0.13MunstLucas Wolf: 108 passningar, xT 0.38WolfDavid Otto: 97 passningar, xT 0.1OttoJoel Agyekum: 95 passningar, xT 0.12AgyekumRobin Velasco: 79 passningar, xT 0.75Velasco
    Jahn Regensburg
    Adrian Fein: 247 passningar, xT 1.29FeinLeopold Wurm: 191 passningar, xT 0.32WurmFelix Strauß: 167 passningar, xT 0.53StraußNicolas-Bernd Oliveira Kisilowski: 130 passningar, xT 0.87KisilowskiBenedikt Saller: 108 passningar, xT 0.23SallerNoel Eichinger: 107 passningar, xT 0.86EichingerNick Seidel: 106 passningar, xT 0.56SeidelFelix Karl-Ernst Gebhardt: 99 passningar, xT 0.04GebhardtOscar Schönfelder: 84 passningar, xT 0.86SchönfelderBenedikt Bauer: 73 passningar, xT 0.47BauerRobin Ziegele: 49 passningar, xT 0.24Ziegele

    The teams in numbers

    PerformanceViktoria KölnJahn Regensburg
    Points5149
    xPoints56.755.3
    xG per match1.61.7
    xGA per match1.41.5
    xG within 8s of winning the ball0.210.32
    xGA within 8s of losing the ball0.240.31
    Playing styleViktoria KölnJahn Regensburg
    Build-up efficiency0.30.3
    Field tilt0.470.46
    xT per match11.1
    xTA per match11.1
    Won balls, offensive half2728
    Pressing intensity0.220.21
    Pressing efficiency0.280.31
    Pressing efficiency, offensive half0.310.36
    Entries into the box per match1214
    Entries into the box against1213
    Pass completion %0.780.71
    Pass completion % under pressure0.740.63
    Passes per match383296
    Passes against per match355354
    Switches of play per match16.816.5
    Long balls per match2829
    Set piecesViktoria KölnJahn Regensburg
    xG from free kicks0.130.12
    Corners per match4.85.5
    Corners against per match4.55.3
    xG per corner0.070.07
    xGA per corner against0.050.06
    First touch, offensive corners %0.460.42
    First touch, defensive corners %0.620.52
    OtherViktoria KölnJahn Regensburg
    Throw-in control0.740.69
    The goalkeepersEduardo dos Santos Haesler (Viktoria Köln)Felix Karl-Ernst Gebhardt (Jahn Regensburg)
    Saves64103
    Save %73%66%
    xG prevented46%47%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Viktoria Köln vs Jahn Regensburg according to our model?

    The model gives Viktoria Köln a 44% win probability. Full 1X2 picture: Viktoria Köln 44%, draw 25%, Jahn Regensburg 32%.

    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 55% and under at 45%.

    Will both teams score?

    The probability of both teams scoring is 58% 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.