Swiss Super LeagueStockhorn Arena, Thun11°4,6 mm22 km/h

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    ThunThunLow block & direct
    vs
    LuganoLuganoPossession control
    The model's lean: 2 · Lugano (56%)Best value by the model: Under 3,5 @ 1.89 (+12 %)

    Thun vs Lugano · Swiss Super League

    1 · Thun 21%X 24%56% Lugano · 2

    Prediction summary

    BetBuilders AI model prediction for Thun vs Lugano (Swiss Super League, Sunday, 25 October 2026): Thun win 21%, draw 24%, Lugano win 56%. Expected goals (xG): Thun 1.15, Lugano 2.10. Most likely score: 1-2 (10%). Over 2.5 goals 63%, both teams to score 60%. Double chance: Thun or draw 44%, Lugano or draw 79%. Prediction updated Friday, 16 October 2026.

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    Analysis: Thun – Lugano

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

    The TEXT contains a factual error in the final paragraph: it states "A 2-1 or 2-0 victory for the visitors seems on the cards," but the model's most likely scorelines are 1-2 and 0-2 (Lugano winning), not 2-1 or 2-0. Here is the corrected text:

    Thun's struggles are evident against Lugano's robust form, and the probabilities paint a clear picture: the visitors are favorites with a 56% chance to secure a win. Lugano's current momentum is undeniable, coming off three consecutive victories and having scored in 21 straight league matches. Meanwhile, Thun's direct style faces the challenge of Lugano's possession-focused approach, making it difficult for the hosts to control the game flow.

    The model indicates Lugano's attacking prowess, estimating them at 2.10 expected goals compared to Thun's 1.15. This aligns with the most likely scorelines of 1-2 and 0-2, which collectively suggest Lugano's edge. A small head-to-head sample since 2023 supports this, with Thun winning just once in four encounters, emphasizing the visitors' upper hand. Lugano's defense, conceding an average of just 1.2 xGA per match, will likely stifle Thun's forward thrusts, which are already limited by a higher xGA figure of 2.2 per match.

    The forecasted rain of 10.1 mm could suppress scoring slightly, yet the numbers still lean towards over 2.5 goals at 63%. Both teams are expected to score (60%), but Lugano's structured play and Thun's defensive vulnerabilities might skew the outcome further in favor of the visitors. This environmental factor is already accounted for in the model's projections.

    Betting markets provide an enticing opportunity. Lugano's win odds at 1.909 on LeoVegas and 1.9 on both Betsafe and Nordicbet offer value, with the model identifying a 5-6% edge. Given the probabilities and Lugano's form, backing an away win holds the sharpest angle. A 1-2 or 0-2 victory for the visitors seems on the cards, steering the narrative towards a profitable evening for those siding with Lugano.

    ThunThun
    Form LLLWL
    League ranking xG #9xGA #12xT #9xP/match #11Points #9
    Key players
    • Brighton LabeauFxG 0.26 · xT 0.17
    • Nicolas Sandro BürgyCBxG 0.15 · xT 0.13
    • Fabio FehrRWBxG 0.14 · xT 0.26
    LuganoLugano
    Form WDWWW
    League ranking xG #6xGA #1xT #2xP/match #2Points #1
    Key players
    • Uran BislimiCMxG 0.08 · xT 0.24
    • Yanis CimignaniLWBxG 0.19 · xT 0.28
    • Anto GrgicCDMxG 0.04 · xT 0.16

    Match prediction: Thun – Lugano

    Predicted score matrix

    Lugano →
    Thun →
    0
    1
    2
    3
    4+
    0
    0–04.1%
    0–17.9%
    0–28.6%
    0–36.0%
    0–4+5.1%
    1
    1–04.2%
    1–19.6%
    1–29.8%
    1–36.9%
    1–4+5.9%
    2
    2–02.6%
    2–15.4%
    2–25.6%
    2–34.0%
    2–4+3.4%
    3
    3–01.0%
    3–12.1%
    3–22.2%
    3–31.5%
    3–4+1.3%
    4+
    4+–00.4%
    4+–10.8%
    4+–20.8%
    4+–30.6%
    4+–4+0.5%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-210%
    2. 2.1-110%
    3. 3.0-29%
    4. 4.0-18%
    5. 5.1-37%
    Expected goals
    1,15–2,10
    Both teams to score
    60%

    Over/under goals

    Expected goals: 3,3
    Under 2,537%
    @2.95EV+6%
    Over 2,563%
    @1.40

    Ready-made bet suggestions

    More combos & build your own →

    01 · 2 legs

    Safe

    • Lugano to win56%
    • Over 1.5 goals84%

    Combined probability

    51%

    Fair odds

    1.96

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

    02 · 3 legs

    Balanced

    • Lugano to win56%
    • Over 2.5 goals63%
    • Dereck Alessandro Moncada Arguijo to score38%

    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 goals63%
    • Dereck Alessandro Moncada Arguijo to score38%
    • Mattia Zanotti to be booked23%

    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+).

    • Under 3.559% probability@1.89PinnacleEV+12%reference odds
    • Under 3.559% probability@1.85LeoVegasEV+9%reference odds
    • Under 2.537% probability@2.95LeoVegasEV+9%reference odds
    Bookmaker1 · ThunX2 · Lugano
    Bet3654.334.101.61
    Betsafe3.653.951.78
    LeoVegas3.654.001.80
    Nordicbet3.653.951.78
    Pinnacle3.76
    EV+ 7%
    4.49
    EV+ 1%
    1.81

    Odds updated 25 Oct, 10:35

    Odds movement

    1+8 %
    29 %24 %

    3.48 → 3.76

    X+6 %
    24 %19 %

    4.22 → 4.49

    2-3 %
    54 %49 %

    1.88 → 1.81

    Pinnacle · 9 recorded price levels · 23/10/2026 → 25/10/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    4 matches
    Thun 1Draw 0Lugano 3
    Goals: 2–4 (⌀ 1,5)

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

    Key facts

    • FC Lugano come into this round on 3 straight wins.
    • FC Lugano have scored in 21 consecutive league matches.
    xG & xGA per match — 3-game rolling average

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

    Thun
    Lugano
    When goals are scored and conceded — 2026
    Thun (17–27)
    Lugano (31–7)
    Pass networks

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

    Thun
    Jan Bamert: 197 passningar, xT 0.48BamertNassim-Othmane Zoukit: 166 passningar, xT 0.47ZoukitJustin Roth: 160 passningar, xT 0.14RothFabio Fehr: 140 passningar, xT 1.68FehrNiklas Steffen: 114 passningar, xT 0.2SteffenTom Henning Strannegård: 97 passningar, xT 0.52StrannegårdNicolas Sandro Bürgy: 76 passningar, xT 0.35BürgyMarco Burki: 76 passningar, xT 0.18BurkiFabio Saiz Pennarossa: 66 passningar, xT 0.08PennarossaMattias Kait: 61 passningar, xT -0.04KaitNils Reichmuth: 59 passningar, xT 0.98Reichmuth
    Lugano
    Anto Grgic: 330 passningar, xT 0.65GrgicHannes Piterson Delcroix: 291 passningar, xT 0.27DelcroixUran Bislimi: 280 passningar, xT 0.39BislimiLukas Mai: 268 passningar, xT 0.45MaiAntonios Papadopoulos: 227 passningar, xT 0.64PapadopoulosYanis Cimignani: 175 passningar, xT 1.16CimignaniDaniel Dos Santos: 167 passningar, xT 0.31SantosDavid Von Ballmoos: 116 passningar, xT 0.06BallmoosBehruzjon Karimov: 115 passningar, xT 0.41KarimovMattia Zanotti: 93 passningar, xT 0.3ZanottiRenato Steffen: 70 passningar, xT 0.1Steffen
    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
    Jan Bamert: 197 passningar, xT 0.48BamertNassim-Othmane Zoukit: 166 passningar, xT 0.47ZoukitJustin Roth: 160 passningar, xT 0.14RothFabio Fehr: 140 passningar, xT 1.68FehrNiklas Steffen: 114 passningar, xT 0.2SteffenTom Henning Strannegård: 97 passningar, xT 0.52StrannegårdNicolas Sandro Bürgy: 76 passningar, xT 0.35BürgyMarco Burki: 76 passningar, xT 0.18BurkiFabio Saiz Pennarossa: 66 passningar, xT 0.08PennarossaMattias Kait: 61 passningar, xT -0.04KaitNils Reichmuth: 59 passningar, xT 0.98Reichmuth
    Lugano
    Anto Grgic: 330 passningar, xT 0.65GrgicHannes Piterson Delcroix: 291 passningar, xT 0.27DelcroixUran Bislimi: 280 passningar, xT 0.39BislimiLukas Mai: 268 passningar, xT 0.45MaiAntonios Papadopoulos: 227 passningar, xT 0.64PapadopoulosYanis Cimignani: 175 passningar, xT 1.16CimignaniDaniel Dos Santos: 167 passningar, xT 0.31SantosDavid Von Ballmoos: 116 passningar, xT 0.06BallmoosBehruzjon Karimov: 115 passningar, xT 0.41KarimovMattia Zanotti: 93 passningar, xT 0.3ZanottiRenato Steffen: 70 passningar, xT 0.1Steffen

    The teams in numbers

    PerformanceThunLugano
    Points1028
    xPoints10.615.7
    xG per match1.51.8
    xGA per match2.21.2
    xG within 8s of winning the ball0.30.18
    xGA within 8s of losing the ball0.40.24
    Playing styleThunLugano
    Build-up efficiency0.330.31
    Field tilt0.460.58
    xT per match1.11.6
    xTA per match1.41
    Won balls, offensive half2825
    Pressing intensity0.240.23
    Pressing efficiency0.330.28
    Pressing efficiency, offensive half0.290.25
    Entries into the box per match1515
    Entries into the box against1412
    Pass completion %0.70.82
    Pass completion % under pressure0.630.79
    Passes per match275478
    Passes against per match314334
    Switches of play per match24.834
    Long balls per match3740
    Set piecesThunLugano
    xG from free kicks0.090.12
    Corners per match5.56
    Corners against per match5.54
    xG per corner0.030.04
    xGA per corner against0.060.02
    First touch, offensive corners %0.410.55
    First touch, defensive corners %0.490.57
    OtherThunLugano
    Throw-in control0.690.77
    The goalkeepersNiklas Steffen (Thun)David Von Ballmoos (Lugano)
    Saves3224
    Save %54%80%
    xG prevented29%49%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Thun vs Lugano according to our model?

    The model gives Lugano a 56% win probability. Full 1X2 picture: Thun 21%, draw 24%, Lugano 56%.

    What is the most likely scoreline?

    The model's most likely final score is 1-2 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 60% according to the model.

    How many goals are expected in Thun vs Lugano?

    The model expects 1.15 goals (xG) for Thun and 2.10 for Lugano, 3.25 in total.

    What does the model say about double chance?

    Thun or draw (1X) 44%, Lugano or draw (X2) 79% and no draw (12) 76%.

    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.