Swiss Super LeagueRheinpark Stadion, Vaduz17°8 km/h

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    VaduzVaduzCounter-attacks & crosses
    vs
    ThunThunCounter-attacks & crosses
    The model's lean: 1 · Vaduz (48%)

    Vaduz vs Thun · Swiss Super League

    1 · Vaduz 48%X 26%26% Thun · 2

    Analysis: VaduzThun

    Erik Lindberg · · Written from the model's numbers · How the predictions work

    Vaduz enters this matchup with a subtle but clear edge, underscored by a model probability of 48% in their favor. The hosts have managed to score in eight consecutive league matches, reflecting a consistency that Thun has struggled to match. Despite Thun's slight lead in the actual points tally — 7 to Vaduz's 6 — the expected data paints a different picture. Vaduz's expected points (xPoints) of 10.8 suggest they've been unfortunate, compared to Thun's 6.6. This clash of form versus potential sets the stage for a tightly contested affair.

    The expected goals (xG) metric further backs the home side, pegging Vaduz at 1.8 xG per match against Thun’s 1.5. Defensively, the visitors appear more vulnerable, with an alarming 2.4 expected goals against (xGA) per match. In contrast, Vaduz's xGA is a more respectable 1.8, indicating that while they are not impervious, they are less porous than their opponents. This defensive fragility of Thun could be a critical factor, especially given the hosts' current scoring streak.

    While head-to-head records can sometimes skew perceptions in football, our current sample size is too small to outweigh the more telling, data-driven insights. Both sides align stylistically, relying on counterattacks and crosses, which may balance the tactical scales. However, the home pitch advantage and a more favorable xG forecast lean towards Vaduz.

    The betting market offers value on this home tilt, with odds of 2.32 available through Betsafe, Betsson, and Nordicbet. With the model's 48% rating, there's a tangible 10% edge here for the calculated bettor. The most likely scorelines of 1-1 and 2-1 suggest a close contest, but the edge tips towards a 2-1 home victory, aligning with both teams' goal probabilities over 2.5 at 65%.

    For those who prioritize data over drama, Vaduz at 2.32 presents a shrewd play.

    VaduzVaduz
    Form LWLWL
    League ranking xG #5xGA #10xT #11xP/match #7Points #10
    Key players
    • Lutfi DalipiFxG 0.18 · xT 0.20
    • Nicolas HaslerRBxG 0.03 · xT 0.16
    • Marcel MonsbergerFxG 0.48 · xT -0.04
    ThunThun
    Form LWDLL
    League ranking xG #9xGA #12xT #9xP/match #12Points #9
    Key players
    • Brighton LabeauFxG 0.33 · xT 0.16
    • Dorian DerbaciFxG 0.03 · xT 0.08
    • Lucien DahlerRWBxG 0.10 · xT 0.19

    Match prediction: VaduzThun

    Predicted score matrix

    Thun
    Vaduz
    0
    1
    2
    3
    4+
    0
    0–03.7%
    0–14.6%
    0–23.4%
    0–31.6%
    0–4+0.8%
    1
    1–06.5%
    1–19.8%
    1–26.6%
    1–33.1%
    1–4+1.5%
    2
    2–06.7%
    2–19.3%
    2–26.5%
    2–33.0%
    2–4+1.4%
    3
    3–04.4%
    3–16.1%
    3–24.3%
    3–32.0%
    3–4+0.9%
    4+
    4+–03.4%
    4+–14.7%
    4+–23.3%
    4+–31.5%
    4+–4+0.7%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-110%
    2. 2.2-19%
    3. 3.2-07%
    4. 4.1-27%
    5. 5.2-27%
    Expected goals
    1,971,40
    Both teams to score
    65%

    Over/under goals

    Expected goals: 3,4
    Under 2,535%
    @2.95EV+2%
    Over 2,565%
    @1.35

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Vaduz to win48%
    • Over 1.5 goals85%

    Combined probability

    44%

    Fair odds

    2.29

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

    02 · 3 legs

    Balanced

    • Vaduz to win48%
    • Over 2.5 goals65%
    • Marcel Michael Monsberger to score26%

    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 goals65%
    • Marcel Michael Monsberger to score26%
    • Luca Maurice Mack 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 · Vaduz48% probability@2.38PinnacleEV+13%reference odds
    • 1 · Vaduz48% probability@2.35BetsafeEV+12%reference odds
    • 1 · Vaduz48% probability@2.35BetssonEV+12%reference odds
    Bookmaker1 · VaduzX2 · Thun
    Betfair Exchange1.311.891.84
    Betsafe
    EV+ 12%
    2.35
    EV+ 0%
    3.85
    2.45
    Betsson
    EV+ 12%
    2.35
    EV+ 0%
    3.85
    2.45
    Nordicbet
    EV+ 12%
    2.35
    EV+ 0%
    3.85
    2.45
    Pinnacle
    EV+ 13%
    2.38
    EV+ 8%
    4.16
    2.54

    Odds updated 17 Sept, 06:36

    Statistics

    Key facts

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

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

    Vaduz
    Thun
    When goals are scored and conceded 2026
    Vaduz (1719)
    Thun (1118)
    Pass networks

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

    Vaduz
    Denis Simani: 317 passningar, xT 0.45SimaniLiridon Berisha: 314 passningar, xT 0.69BerishaLuca Mack: 286 passningar, xT 0.33MackNicolas Hasler: 227 passningar, xT 0.75HaslerJulian Stark: 194 passningar, xT 0.26StarkDominik Schwizer: 172 passningar, xT 0.49SchwizerLeon Schaffran: 136 passningar, xT 0.07SchaffranLutfi Dalipi: 132 passningar, xT 0.77DalipiJuan Ignacio Cabrera: 125 passningar, xT 0.58CabreraMiloš Ćoćić: 92 passningar, xT -0.01ĆoćićMalik Sawadogo: 55 passningar, xT 0.36Sawadogo
    Thun
    Jan Bamert: 231 passningar, xT 0.72BamertNassim-Othmane Zoukit: 175 passningar, xT 0.63ZoukitNiklas Steffen: 142 passningar, xT 0.28SteffenNicolas Sandro Bürgy: 134 passningar, xT 0.35BürgyJustin Roth: 133 passningar, xT 0.04RothFabio Fehr: 122 passningar, xT 0.31FehrMarco Burki: 95 passningar, xT 0.23BurkiFabio Saiz Pennarossa: 90 passningar, xT 0.15PennarossaLucien Dahler: 83 passningar, xT 0.46DahlerNils Reichmuth: 63 passningar, xT -0.09ReichmuthTom Henning Strannegård: 61 passningar, xT 0.24Strannegård
    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.

    Vaduz
    Denis Simani: 317 passningar, xT 0.45SimaniLiridon Berisha: 314 passningar, xT 0.69BerishaLuca Mack: 286 passningar, xT 0.33MackNicolas Hasler: 227 passningar, xT 0.75HaslerJulian Stark: 194 passningar, xT 0.26StarkDominik Schwizer: 172 passningar, xT 0.49SchwizerLeon Schaffran: 136 passningar, xT 0.07SchaffranLutfi Dalipi: 132 passningar, xT 0.77DalipiJuan Ignacio Cabrera: 125 passningar, xT 0.58CabreraMiloš Ćoćić: 92 passningar, xT -0.01ĆoćićMalik Sawadogo: 55 passningar, xT 0.36Sawadogo
    Thun
    Jan Bamert: 231 passningar, xT 0.72BamertNassim-Othmane Zoukit: 175 passningar, xT 0.63ZoukitNiklas Steffen: 142 passningar, xT 0.28SteffenNicolas Sandro Bürgy: 134 passningar, xT 0.35BürgyJustin Roth: 133 passningar, xT 0.04RothFabio Fehr: 122 passningar, xT 0.31FehrMarco Burki: 95 passningar, xT 0.23BurkiFabio Saiz Pennarossa: 90 passningar, xT 0.15PennarossaLucien Dahler: 83 passningar, xT 0.46DahlerNils Reichmuth: 63 passningar, xT -0.09ReichmuthTom Henning Strannegård: 61 passningar, xT 0.24Strannegård

    The teams in numbers

    PerformanceVaduzThun
    Points67
    xPoints10.86.6
    xG per match1.81.5
    xGA per match1.82.4
    xG within 8s of winning the ball0.270.29
    xGA within 8s of losing the ball0.380.41
    Playing styleVaduzThun
    Build-up efficiency0.290.33
    Field tilt0.470.47
    xT per match0.851
    xTA per match1.41.4
    Won balls, offensive half2726
    Pressing intensity0.280.24
    Pressing efficiency0.340.35
    Pressing efficiency, offensive half0.30.32
    Entries into the box per match1416
    Entries into the box against1715
    Pass completion %0.770.71
    Pass completion % under pressure0.710.65
    Passes per match418288
    Passes against per match304304
    Switches of play per match24.426.1
    Long balls per match3639
    Set piecesVaduzThun
    xG from free kicks0.040.13
    Corners per match4.25.1
    Corners against per match6.86
    xG per corner0.020.02
    xGA per corner against0.050.07
    First touch, offensive corners %0.440.47
    First touch, defensive corners %0.520.52
    OtherVaduzThun
    Throw-in control0.720.7
    The goalkeepersLeon Schaffran (Vaduz)Niklas Steffen (Thun)
    Saves2329
    Save %62%62%
    xG prevented47%31%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Vaduz vs Thun according to our model?

    The model gives Vaduz a 48% win probability. Full 1X2 picture: Vaduz 48%, draw 26%, Thun 26%.

    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 65% and under at 35%.

    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.