Serie BStadio Druso, Bolzano20°9 km/h

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    SüdtirolSüdtirolCounter-attacks & crosses
    vs
    ModenaModenaBalanced & physical
    The model's lean: 2 · Modena (38%)Best value by the model: 1 · Südtirol @ 3.45 (+13 %)

    SüdtirolModena · Serie B

    1 · Südtirol 33%X 29%38% Modena · 2

    Analysis: SüdtirolModena

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

    Modena's physicality and balanced approach pose a significant challenge for Südtirol, who rely heavily on counter-attacks and crosses. With Modena's superior xG per match at 1.5 compared to Südtirol's 0.6, the visitors are likely to create more quality chances in front of goal. Despite sitting a point behind in the standings, Modena's underlying numbers suggest they have been the more robust side, both in terms of expected goals and expected goals against.

    Südtirol, however, are riding a wave of confidence, having remained unbeaten in their last six league matches. Their resilience has been exemplified in recent head-to-head encounters, albeit in a small sample size of four matches since 2023, where they've secured one win and three draws against Modena. Yet, this historical record is perhaps misleading given the disparity in the quality of chances created and conceded by each team this season. Modena's strong defense, with an xGA of 0.63 per match, further underscores their capability to stifle Südtirol's attacking threats.

    The model slightly favors Modena with a 38% win probability compared to Südtirol's 33%, hinting at a narrow away victory. The most likely scorelines suggest a low-scoring affair, with a 1-1 draw sitting at 13% and a 0-1 win for Modena at 12%. The over 2.5 goals probability stands at just 43%, reinforcing the expectation of a tight contest dominated by tactical discipline rather than free-flowing play.

    For bettors seeking value, the home win priced at odds of 3.1 offers a marginal edge with Betsafe, Betsson, and Nordicbet, as the model pegs Südtirol's chances at 33%, indicating a 1% value edge. However, given the expected dynamics on the pitch, betting on the favored Modena to edge out a win or a draw seems the strategically sound play. Expect a low-scoring match, with the final result likely tilting in Modena’s favor, perhaps settling at a narrow 0-1 victory.

    SüdtirolSüdtirol
    Form DDWDW
    League ranking xG #20xGA #12xT #20xP/match #12Points #3
    Key players
    • Aljosa VasicFxG 0.18 · xT -0.01
    • Silvio MerkajFxG 0.12 · xT 0.06
    • Fabio RispoliCMxG 0.03 · xT 0.08
    ModenaModena
    Form LLWWL
    League ranking xG #6xGA #1xT #8xP/match #4Points #6
    Key players
    • Giuseppe AmbrosinoFxG 0.30 · xT 0.00
    • Giacomo OlzerRWxG 0.13 · xT -0.19
    • Simone SantoroCMxG 0.16 · xT 0.06

    Match prediction: SüdtirolModena

    Predicted score matrix

    Modena
    Südtirol
    0
    1
    2
    3
    4+
    0
    0–09.4%
    0–111.7%
    0–28.1%
    0–33.6%
    0–4+1.6%
    1
    1–09.2%
    1–113.2%
    1–28.6%
    1–33.9%
    1–4+1.7%
    2
    2–05.1%
    2–16.9%
    2–24.6%
    2–32.1%
    2–4+0.9%
    3
    3–01.8%
    3–12.4%
    3–21.6%
    3–30.7%
    3–4+0.3%
    4+
    4+–00.6%
    4+–10.8%
    4+–20.6%
    4+–30.2%
    4+–4+0.1%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-113%
    2. 2.0-112%
    3. 3.0-09%
    4. 4.1-09%
    5. 5.1-29%
    Expected goals
    1,071,34
    Both teams to score
    49%

    Over/under goals

    Expected goals: 2,4
    Under 2,557%
    @1.61
    Over 2,543%
    @2.39EV+4%

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Double chance Modena or draw (X2)71%
    • Under 3.5 goals78%

    Combined probability

    55%

    Fair odds

    1.83

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

    02 · 3 legs

    Balanced

    • Double chance Modena or draw (X2)71%
    • Under 2.5 goals57%
    • Ettore Gliozzi to score20%

    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 score49%
    • Over 2.5 goals43%
    • Silvio Merkaj to score27%
    • Simone Santoro 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 · Südtirol33% probability@3.45PinnacleEV+13%reference odds
    • Over 2.543% probability@2.39PinnacleEV+4%reference odds
    • 1 · Südtirol33% probability@3.10BetsafeEV+1%reference odds
    Bookmaker1 · SüdtirolX2 · Modena
    Betsafe
    EV+ 1%
    3.10
    2.852.38
    Betsson
    EV+ 1%
    3.10
    2.852.38
    Nordicbet
    EV+ 1%
    3.10
    2.852.38
    Pinnacle
    EV+ 13%
    3.45
    2.862.50

    Odds updated 11 Sept, 16:32

    Odds movement

    1+14 %
    32 %27 %

    3.033.45

    X-1 %
    36 %31 %

    2.892.86

    2-6 %
    40 %35 %

    2.652.50

    Over 2,5+4 %
    43 %38 %

    2.302.39

    Pinnacle · 10 recorded price levels · 06/09/2026 → 11/09/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    4 matches
    Südtirol 1Draw 3Modena 0
    Goals: 32 (⌀ 1,2)

    Head-to-head based on Serie B data since 2023.

    Key facts

    • Sudtirol are unbeaten in their last 6 league matches.
    xG & xGA per match — 3-game rolling average

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

    Südtirol
    Modena
    When goals are scored and conceded 2026
    Südtirol (41)
    Modena (52)
    Pass networks

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

    Südtirol
    Andrea Giorgini: 175 passningar, xT 0.14GiorginiSimone Tronchin: 120 passningar, xT 0TronchinRiccardo Stivanello: 119 passningar, xT 0.22StivanelloFabio Rispoli: 110 passningar, xT 0.19RispoliAlessandro Plizzari: 101 passningar, xT 0.07PlizzariSalvatore Molina: 100 passningar, xT 0.15MolinaDavide Veroli: 78 passningar, xT 0.07VeroliBjarki Steinn Bjarkason: 49 passningar, xT 0.13BjarkasonAljosa Vasic: 46 passningar, xT -0.01VasicVasco Rafael Fortes Lopes: 44 passningar, xT -0.02LopesGiacomo Stabile: 34 passningar, xT 0.06Stabile
    Modena
    Folly Nador: 162 passningar, xT 0.21NadorGastón Brugman Duarte: 159 passningar, xT 0.15DuarteBryant Nieling: 158 passningar, xT 0.32NielingAlessandro Bianco: 152 passningar, xT 0.22BiancoDaniel Tonoli: 102 passningar, xT 0.26TonoliSimone Santoro: 100 passningar, xT 0.05SantoroLeandro Chichizola: 86 passningar, xT 0.12ChichizolaFrancesco Filippo Zampano: 78 passningar, xT 0.01ZampanoGiuseppe Caso: 53 passningar, xT 0.96CasoGiuseppe Ambrosino: 44 passningar, xT 0AmbrosinoPaulo Azzi: 42 passningar, xT 0Azzi
    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.

    Südtirol
    Andrea Giorgini: 175 passningar, xT 0.14GiorginiSimone Tronchin: 120 passningar, xT 0TronchinRiccardo Stivanello: 119 passningar, xT 0.22StivanelloFabio Rispoli: 110 passningar, xT 0.19RispoliAlessandro Plizzari: 101 passningar, xT 0.07PlizzariSalvatore Molina: 100 passningar, xT 0.15MolinaDavide Veroli: 78 passningar, xT 0.07VeroliBjarki Steinn Bjarkason: 49 passningar, xT 0.13BjarkasonAljosa Vasic: 46 passningar, xT -0.01VasicVasco Rafael Fortes Lopes: 44 passningar, xT -0.02LopesGiacomo Stabile: 34 passningar, xT 0.06Stabile
    Modena
    Folly Nador: 162 passningar, xT 0.21NadorGastón Brugman Duarte: 159 passningar, xT 0.15DuarteBryant Nieling: 158 passningar, xT 0.32NielingAlessandro Bianco: 152 passningar, xT 0.22BiancoDaniel Tonoli: 102 passningar, xT 0.26TonoliSimone Santoro: 100 passningar, xT 0.05SantoroLeandro Chichizola: 86 passningar, xT 0.12ChichizolaFrancesco Filippo Zampano: 78 passningar, xT 0.01ZampanoGiuseppe Caso: 53 passningar, xT 0.96CasoGiuseppe Ambrosino: 44 passningar, xT 0AmbrosinoPaulo Azzi: 42 passningar, xT 0Azzi

    The teams in numbers

    PerformanceSüdtirolModena
    Points76
    xPoints3.75.5
    xG per match0.61.5
    xGA per match1.20.63
    xG within 8s of winning the ball0.110.29
    xGA within 8s of losing the ball0.330.07
    Playing styleSüdtirolModena
    Build-up efficiency0.330.33
    Field tilt0.350.57
    xT per match0.390.94
    xTA per match10.79
    Won balls, offensive half1227
    Pressing intensity0.240.21
    Pressing efficiency0.310.24
    Pressing efficiency, offensive half0.280.21
    Entries into the box per match514
    Entries into the box against1210
    Pass completion %0.790.82
    Pass completion % under pressure0.750.77
    Passes per match343410
    Passes against per match379343
    Switches of play per match18.732.6
    Long balls per match2536
    Set piecesSüdtirolModena
    xG from free kicks00
    Corners per match1.66
    Corners against per match6.96
    xG per corner0.010.05
    xGA per corner against0.010.01
    First touch, offensive corners %0.40.67
    First touch, defensive corners %0.710.61
    OtherSüdtirolModena
    Throw-in control0.680.8
    The goalkeepersAlessandro Plizzari (Südtirol)Leandro Chichizola (Modena)
    Saves87
    Save %89%78%
    xG prevented35%74%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Südtirol vs Modena according to our model?

    The model gives Modena a 38% win probability. Full 1X2 picture: Südtirol 33%, draw 29%, Modena 38%.

    What is the most likely scoreline?

    The model's most likely final score is 1-1 at 13% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 43% and under at 57%.

    Will both teams score?

    The probability of both teams scoring is 49% 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.