Swiss Super LeagueStockhorn Arena, Thun19°14 km/h

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    ThunThunLow block & direct
    00
    Lausanne SportLausanne SportPossession control
    The model's lean: 1 · Thun (46%)

    ThunLausanne Sport · Swiss Super League

    1 · Thun 46%X 27%27% Lausanne Sport · 2

    Analysis: ThunLausanne Sport

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

    TEXT: Thun holds a slight edge in their recent head-to-head encounters with Lausanne Sport, securing two victories in the three matches since 2023. While it's a limited sample, these results might suggest a slight psychological advantage for the hosts. However, this matchup is not just about past meetings; it's about contrasting styles and current form.

    Thun, playing at home, tends to rely on a low defensive block and direct play. This could challenge Lausanne Sport's possession-oriented approach, especially as Thun boasts a 60% home win rate. Yet, the expected goals tell a more nuanced story. For this match, Thun's expected goals stand at 1.67, while Lausanne Sport's are 1.35. Although this leans slightly in favor of the home side, their defensive frailties are exposed with a worrying 2.5 xGA per game, compared to Lausanne Sport's more robust 1.2 xGA.

    Despite their defensive vulnerabilities, the model still favors Thun with a 46% probability of winning. The most likely scorelines, such as 1-1 and 2-1, reflect the balance but slight edge for the hosts. However, with a model-predicted 58% chance of over 2.5 goals and 60% for both teams to score, this could easily swing either way if defenses falter.

    The sharper betting angle lies in the value on the under 3.5 goals market. The model gives a 64% likelihood for this outcome, offering a 6% edge at odds of 1.65 with bookmakers like Betsafe, Betsson, and Nordicbet. This suggests a slightly less chaotic affair than the goal probabilities imply, making it a strategic pick for those evaluating the match from a value perspective.

    ThunThun
    Form DWLLW
    League ranking xG #11xGA #12xT #12xP/match #12Points #6
    Key players
    • Marc GutbubFxG 0.47 · xT 0.00
    • Brighton LabeauLWxG 0.31 · xT 0.10
    • Lucien DahlerRWBxG 0.10 · xT 0.12
    Lausanne SportLausanne Sport
    Form DWDLL
    League ranking xG #12xGA #3xT #10xP/match #11Points #8
    Key players
    • Beyatt LekoueiryRWxG 0.00 · xT 0.34
    • Kevin MouangaCBxG 0.03 · xT 0.04
    • Jamie RocheCMxG 0.03 · xT -0.01
    Final score
    00
    The model missed the outcome
    Predicted probabilities: Thun 46% · Draw 27% · Lausanne Sport 27%

    How the bookmaker bet builders went

    The verdict on the pre-built bet builders for this match, priced against the model’s score matrix before kickoff. Graded on the 90-minute result.

    Matchresultat - LausanneBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 8,20fair 10,46-22 %
    Miss
    Matchresultat - ThunBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 5,16fair 6,84-25 %
    Miss

    Match prediction: ThunLausanne Sport

    Predicted score matrix

    Lausanne Sport
    Thun
    0
    1
    2
    3
    4+
    0
    0–05.2%
    0–16.3%
    0–24.5%
    0–32.0%
    0–4+0.9%
    1
    1–07.9%
    1–111.4%
    1–27.4%
    1–33.3%
    1–4+1.5%
    2
    2–06.8%
    2–19.2%
    2–26.2%
    2–32.8%
    2–4+1.3%
    3
    3–03.8%
    3–15.1%
    3–23.4%
    3–31.5%
    3–4+0.7%
    4+
    4+–02.3%
    4+–13.1%
    4+–22.1%
    4+–30.9%
    4+–4+0.4%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-111%
    2. 2.2-19%
    3. 3.1-08%
    4. 4.1-27%
    5. 5.2-07%
    Expected goals
    1,671,35
    Both teams to score
    60%

    Over/under goals

    Expected goals: 3,0
    Under 2,542%
    @2.22
    Over 2,558%
    @1.58

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Thun to win46%
    • Over 1.5 goals81%

    Combined probability

    37%

    Fair odds

    2.72

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

    02 · 3 legs

    Balanced

    • Thun to win46%
    • Over 2.5 goals58%
    • Brighton Andy Labeau Melchior 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 score60%
    • Over 2.5 goals58%
    • Brighton Andy Labeau Melchior to score26%
    • Jamie John Roche to be booked24%

    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

    Bookmaker1 · ThunX2 · Lausanne Sport
    Betsafe2.023.403.25
    Betsson2.023.403.25
    Nordicbet2.023.403.25
    Pinnacle2.093.513.65

    Odds updated 2 Sept, 10:36

    Odds movement

    1-5 %
    48 %43 %

    2.192.09

    X+4 %
    30 %25 %

    3.373.51

    2+10 %
    30 %25 %

    3.333.65

    Pinnacle · 18 recorded price levels · 31/08/2026 → 02/09/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    3 matches
    Thun 2Draw 0Lausanne Sport 1
    Goals: 84 (⌀ 4)

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

    Key facts

    • Thun win 60% of their home matches all-time (20 played).
    xG & xGA per match — 3-game rolling average

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

    Thun
    Lausanne Sport
    When goals are scored and conceded 2026
    Thun (914)
    Lausanne Sport (67)
    Pass networks

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

    Thun
    Nicolas Sandro Bürgy: 157 passningar, xT 0.32BürgyJan Bamert: 135 passningar, xT 0.26BamertNiklas Steffen: 102 passningar, xT 0.14SteffenFabio Saiz Pennarossa: 95 passningar, xT 0.17PennarossaLucien Dahler: 79 passningar, xT 0.36DahlerNassim-Othmane Zoukit: 70 passningar, xT 0.14ZoukitJustin Roth: 62 passningar, xT 0RothNico Maier: 41 passningar, xT 0.41MaierFabio Fehr: 34 passningar, xT -0.29FehrDorian Derbaci: 33 passningar, xT 0.21DerbaciMichael Heule: 33 passningar, xT 0.28Heule
    Lausanne Sport
    Abdou Karim Sow: 247 passningar, xT 0.28SowOlivier da Costa Custodio: 183 passningar, xT 0.05CustodioBrandon Soppy: 173 passningar, xT 0.28SoppyJamie Roche: 166 passningar, xT -0.04RocheMorgan Poaty: 164 passningar, xT 0.29PoatyKevin Mouanga: 152 passningar, xT 0.12MouangaFlorent Mollet: 127 passningar, xT -0.05MolletMelvin Feyçal Mastil: 105 passningar, xT 0.16MastilSékou Koné: 75 passningar, xT 0.29KonéNathan Jerome Chatoyer Butler-Oyedeji: 68 passningar, xT 0.04Butler-OyedejiTyler Fredricson: 62 passningar, xT 0.08Fredricson
    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.

    Thun
    Nicolas Sandro Bürgy: 157 passningar, xT 0.32BürgyJan Bamert: 135 passningar, xT 0.26BamertNiklas Steffen: 102 passningar, xT 0.14SteffenFabio Saiz Pennarossa: 95 passningar, xT 0.17PennarossaLucien Dahler: 79 passningar, xT 0.36DahlerNassim-Othmane Zoukit: 70 passningar, xT 0.14ZoukitJustin Roth: 62 passningar, xT 0RothNico Maier: 41 passningar, xT 0.41MaierFabio Fehr: 34 passningar, xT -0.29FehrDorian Derbaci: 33 passningar, xT 0.21DerbaciMichael Heule: 33 passningar, xT 0.28Heule
    Lausanne Sport
    Abdou Karim Sow: 247 passningar, xT 0.28SowOlivier da Costa Custodio: 183 passningar, xT 0.05CustodioBrandon Soppy: 173 passningar, xT 0.28SoppyJamie Roche: 166 passningar, xT -0.04RocheMorgan Poaty: 164 passningar, xT 0.29PoatyKevin Mouanga: 152 passningar, xT 0.12MouangaFlorent Mollet: 127 passningar, xT -0.05MolletMelvin Feyçal Mastil: 105 passningar, xT 0.16MastilSékou Koné: 75 passningar, xT 0.29KonéNathan Jerome Chatoyer Butler-Oyedeji: 68 passningar, xT 0.04Butler-OyedejiTyler Fredricson: 62 passningar, xT 0.08Fredricson

    The teams in numbers

    PerformanceThunLausanne Sport
    Points65
    xPoints3.95.1
    xG per match1.20.71
    xGA per match2.51.2
    xG within 8s of winning the ball0.410.14
    xGA within 8s of losing the ball0.420.34
    Playing styleThunLausanne Sport
    Build-up efficiency0.320.33
    Field tilt0.340.56
    xT per match0.670.75
    xTA per match1.70.95
    Won balls, offensive half2322
    Pressing intensity0.250.24
    Pressing efficiency0.340.37
    Pressing efficiency, offensive half0.30.3
    Entries into the box per match128
    Entries into the box against1812
    Pass completion %0.690.74
    Pass completion % under pressure0.60.69
    Passes per match246352
    Passes against per match346304
    Switches of play per match19.836.9
    Long balls per match3038
    Set piecesThunLausanne Sport
    xG from free kicks0.130.05
    Corners per match43.9
    Corners against per match5.94.7
    xG per corner0.010.03
    xGA per corner against0.020.04
    First touch, offensive corners %0.380.5
    First touch, defensive corners %0.50.43
    OtherThunLausanne Sport
    Throw-in control0.670.74
    The goalkeepersNiklas Steffen (Thun)Melvin Feyçal Mastil (Lausanne Sport)
    Saves1916
    Save %58%70%
    xG prevented34%48%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Thun vs Lausanne Sport according to our model?

    The model gives Thun a 46% win probability. Full 1X2 picture: Thun 46%, draw 27%, Lausanne Sport 27%.

    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 58% and under at 42%.

    Will both teams score?

    The probability of both teams scoring is 60% 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.