3. Liga22°7 km/hUpdated

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

    Viktoria KölnJahn Regensburg · 3. Liga

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

    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%

    Odds & value

    The model's value spots

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

    • 1 · Viktoria Köln44% probability@2.39PinnacleEV+5%
    Bookmaker1 · Viktoria KölnX2 · Jahn Regensburg
    Pinnacle
    EV+ 5%
    2.39
    3.732.64

    Odds updated 4 Aug, 09:04

    Analysis: Viktoria KölnJahn Regensburg

    Sofia Andersson · · How the predictions work

    A 44% chance for Viktoria Koln to claim victory speaks volumes in a tightly contested 3. Liga clash where every point is precious. They're riding slightly ahead in the points tally with 51, just a hair above Jahn Regensburg's 49. When the teams last met, Viktoria Koln emerged unbeaten, notching a win and a draw. It's a small sample size, but it suggests an edge in this head-to-head. Viktoria Koln’s home odds of 2.39 with Pinnacle present a tantalising 5% edge, making it a value bet you might not want to overlook.

    Viktoria Koln's expected goals (xG) of 1.57 against Jahn Regensburg's 1.30 suggests a slight lean towards the home side. Yet Jahn Regensburg's marginally superior xG per match at 1.7 points to their ability to carve out chances. Both teams share a similar affinity for possession control, hinting at a tactical tussle where seizing the moment could prove decisive. In a game where subtle differences matter, Viktoria’s lower expected goals against (xGA) of 1.4 compared to Jahn Regensburg’s 1.5 suggests a more robust defensive core.

    Jahn Regensburg's 32% chance of winning doesn’t spark much confidence, especially considering their past struggles against this opponent. The expected goals narrative here sets the stage for an intriguing 1-1 draw, the most likely score per the model. Yet, with Viktoria Koln's probability of registering a 2-1 or 1-0 win each at 9%, that edge in the model’s favour skews the picture towards a home win.

    With the odds favouring an over 2.5 goals scenario at 55%, and both teams to score pegged at 58%, goal action seems more probable than not. However, it's Viktoria Koln’s home value at 2.39 with Pinnacle that stands out as the sharpest betting angle. If you're looking for a punt that aligns with both numbers and narrative, backing Viktoria Koln to edge past Jahn Regensburg seems the most sensible play.

    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 0.18BoboySimon Handle: 120 passningar, xT 1.36HandleTaylan Duman: 120 passningar, xT 0.1DumanArne 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 0.18BoboySimon Handle: 120 passningar, xT 1.36HandleTaylan Duman: 120 passningar, xT 0.1DumanArne 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%)

    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.