Swiss Super LeagueSwissporarena, Luzern18°1,5 mm7 km/h

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    LuzernLuzernCounter-attacks & crosses
    vs
    BaselBaselBalanced & physical
    The model's lean: 1 · Luzern (37%)Soft drawBest value by the model: X · Draw @ 4.02 (+14 %)

    LuzernBasel · Swiss Super League

    1 · Luzern 37%X 28%34% Basel · 2

    Analysis: LuzernBasel

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

    The clash between Luzern and Basel promises an intriguing dynamic as the hosts lean on their counter-attacking prowess, while the visitors bring a balanced physicality to the pitch. With model probabilities giving Luzern a slight edge at 37% to Basel's 34%, the game is finely poised, reflective of the expected goals (xG) tally where Luzern narrowly trails Basel 1.62 to 1.65. The high-scoring nature, averaging 3.1 goals per meeting, suggests a lively encounter on the cards.

    Luzern's recent form adds another layer to the narrative, going unbeaten in their last five league outings. They’ve shown resilience, yet the head-to-head record against Basel since 2023 is deadlocked at three wins, one draw, and three losses each. This tight historical context, while informative, carries less weight than current form and expected goals when predicting outcomes. Interestingly, Luzern’s superior xG per match (1.6) compared to Basel’s (1.1) highlights their attacking edge, though their defensive frailties are evident, conceding 2.1 xGA per match against Basel's 1.3.

    The model's most probable scorelines—1-1, 1-2, or 2-1—underscore the likelihood of both sides finding the net, supported by a 65% probability for both teams to score. With an over 2.5 goals chance standing at 63%, the matchup leans towards a high-scoring affair. The balance Luzern and Basel strike between attack and defense makes the draw scenario highly plausible, especially as the odds offered by bookmakers like Betsafe, Betsson, and Nordicbet present value at 3.8. With such an 8% edge for the draw, the analytics point to a 1-1 outcome as the most viable bet.

    LuzernLuzern
    Form DWDWD
    League ranking xG #7xGA #11xT #4xP/match #9Points #6
    Key players
    • Matteo Di GiustoLWxG 0.30 · xT 0.15
    • Daniel MikołajewskiFxG 0.28 · xT 0.26
    • Tyron OwusuRWxG 0.04 · xT 0.14
    BaselBasel
    Form WWDLL
    League ranking xG #11xGA #2xT #10xP/match #10Points #5
    Key players
    • Keigo TsunemotoRBxG 0.01 · xT 0.19
    • Žan CelarFxG 0.35 · xT -0.01
    • Flavius David DaniliucCBxG 0.06 · xT 0.08

    Match prediction: LuzernBasel

    Predicted score matrix

    Basel
    Luzern
    0
    1
    2
    3
    4+
    0
    0–04.1%
    0–16.0%
    0–25.2%
    0–32.9%
    0–4+1.7%
    1
    1–05.8%
    1–110.4%
    1–28.4%
    1–34.6%
    1–4+2.8%
    2
    2–05.0%
    2–18.2%
    2–26.8%
    2–33.7%
    2–4+2.2%
    3
    3–02.7%
    3–14.4%
    3–23.7%
    3–32.0%
    3–4+1.2%
    4+
    4+–01.6%
    4+–12.6%
    4+–22.1%
    4+–31.2%
    4+–4+0.7%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-110%
    2. 2.1-28%
    3. 3.2-18%
    4. 4.2-27%
    5. 5.0-16%
    Expected goals
    1,621,65
    Both teams to score
    65%

    Over/under goals

    Expected goals: 3,3
    Under 2,537%
    @2.72
    Over 2,563%
    @1.40

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Double chance Luzern or draw (1X)61%
    • Over 1.5 goals84%

    Combined probability

    51%

    Fair odds

    1.95

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

    02 · 3 legs

    Balanced

    • Double chance Luzern or draw (1X)61%
    • Over 2.5 goals63%
    • Daniel Mikołajewski to score16%

    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 score65%
    • Over 2.5 goals63%
    • Žan Celar to score23%
    • Leonardo Fabrizio Bertone 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+).

    • X · Draw28% probability@4.02PinnacleEV+14%reference odds
    • Under 3.559% probability@1.77PinnacleEV+4%reference odds
    • 2 · Basel34% probability@3.02PinnacleEV+4%reference odds
    Bookmaker1 · LuzernX2 · Basel
    Betsafe2.08
    EV+ 3%
    3.65
    EV+ 1%
    2.95
    Betsson2.08
    EV+ 3%
    3.65
    EV+ 1%
    2.95
    Nordicbet2.08
    EV+ 3%
    3.65
    EV+ 1%
    2.95
    Pinnacle2.11
    EV+ 14%
    4.02
    EV+ 4%
    3.02

    Odds updated 11 Sept, 04:38

    Odds movement

    1+3 %
    48 %43 %

    2.052.11

    X-2 %
    26 %21 %

    4.114.02

    2-2 %
    34 %29 %

    3.073.02

    Pinnacle · 5 recorded price levels · 07/09/2026 → 09/09/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    7 matches
    Luzern 3Draw 1Basel 3
    Goals: 1012 (⌀ 3,1)

    Head-to-head based on Swiss Super League data since 2023.

    Key facts

    • A high-scoring fixture: 3.1 goals per meeting on average.
    • Luzern are unbeaten in their last 5 league matches.
    xG & xGA per match — 3-game rolling average

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

    Luzern
    Basel
    When goals are scored and conceded 2026
    Luzern (1013)
    Basel (1212)
    Pass networks

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

    Luzern
    Bung Meng Freimann: 159 passningar, xT 0.34FreimannAndrejs Ciganiks: 156 passningar, xT 0.98CiganiksLeonardo Bertone: 136 passningar, xT 0.4BertoneBung Hua Freimann: 127 passningar, xT 0.16FreimannMatteo Di Giusto: 96 passningar, xT 0.64GiustoRuben Dantas Fernandes: 95 passningar, xT 0.36FernandesMio Zimmermann: 92 passningar, xT 0.17ZimmermannKarlo Letica: 83 passningar, xT 0.15LeticaPius Dorn: 83 passningar, xT 0.26DornTyron Owusu: 69 passningar, xT 0.37OwusuDaniel Mikołajewski: 46 passningar, xT 0.7Mikołajewski
    Basel
    Flavius David Daniliuc: 290 passningar, xT 0.37DaniliucKeigo Tsunemoto: 279 passningar, xT 0.82TsunemotoAkpe Victory Maduabuchukwu: 261 passningar, xT 0.41MaduabuchukwuBećir Omeragić: 174 passningar, xT 0.01OmeragićMoussa Cissé: 138 passningar, xT 0.52CisséMirko Salvi: 114 passningar, xT 0.07SalviAsane Sow: 113 passningar, xT 0.37SowAbemly Silu Metinho: 103 passningar, xT -0.09MetinhoXherdan Shaqiri: 100 passningar, xT 0.26ShaqiriKazeem Aderemi Olaigbe: 75 passningar, xT 0.47OlaigbeLudwig Simon Małachowski Thorell: 67 passningar, xT -0.02Thorell
    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.

    Luzern
    Bung Meng Freimann: 159 passningar, xT 0.34FreimannAndrejs Ciganiks: 156 passningar, xT 0.98CiganiksLeonardo Bertone: 136 passningar, xT 0.4BertoneBung Hua Freimann: 127 passningar, xT 0.16FreimannMatteo Di Giusto: 96 passningar, xT 0.64GiustoRuben Dantas Fernandes: 95 passningar, xT 0.36FernandesMio Zimmermann: 92 passningar, xT 0.17ZimmermannKarlo Letica: 83 passningar, xT 0.15LeticaPius Dorn: 83 passningar, xT 0.26DornTyron Owusu: 69 passningar, xT 0.37OwusuDaniel Mikołajewski: 46 passningar, xT 0.7Mikołajewski
    Basel
    Flavius David Daniliuc: 290 passningar, xT 0.37DaniliucKeigo Tsunemoto: 279 passningar, xT 0.82TsunemotoAkpe Victory Maduabuchukwu: 261 passningar, xT 0.41MaduabuchukwuBećir Omeragić: 174 passningar, xT 0.01OmeragićMoussa Cissé: 138 passningar, xT 0.52CisséMirko Salvi: 114 passningar, xT 0.07SalviAsane Sow: 113 passningar, xT 0.37SowAbemly Silu Metinho: 103 passningar, xT -0.09MetinhoXherdan Shaqiri: 100 passningar, xT 0.26ShaqiriKazeem Aderemi Olaigbe: 75 passningar, xT 0.47OlaigbeLudwig Simon Małachowski Thorell: 67 passningar, xT -0.02Thorell

    The teams in numbers

    PerformanceLuzernBasel
    Points910
    xPoints8.98.1
    xG per match1.61.1
    xGA per match2.11.3
    xG within 8s of winning the ball0.140.25
    xGA within 8s of losing the ball0.350.19
    Playing styleLuzernBasel
    Build-up efficiency0.340.32
    Field tilt0.410.46
    xT per match1.30.91
    xTA per match1.41.2
    Won balls, offensive half2121
    Pressing intensity0.250.24
    Pressing efficiency0.310.27
    Pressing efficiency, offensive half0.250.21
    Entries into the box per match1312
    Entries into the box against1818
    Pass completion %0.710.78
    Pass completion % under pressure0.60.72
    Passes per match268362
    Passes against per match366381
    Switches of play per match23.131.3
    Long balls per match3332
    Set piecesLuzernBasel
    xG from free kicks0.120.03
    Corners per match5.13.8
    Corners against per match5.96.7
    xG per corner0.030.02
    xGA per corner against0.030.01
    First touch, offensive corners %0.330.63
    First touch, defensive corners %0.440.43
    OtherLuzernBasel
    Throw-in control0.730.66
    The goalkeepersSimon Simoni (Luzern)Mirko Salvi (Basel)
    Saves1618
    Save %67%62%
    xG prevented37%38%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Luzern vs Basel according to our model?

    The model gives Luzern a 37% win probability. Full 1X2 picture: Luzern 37%, draw 28%, Basel 34%.

    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 63% and under at 37%.

    Will both teams score?

    The probability of both teams scoring is 65% 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.