Serie BStadio Druso, Bolzano18°9,3 mm4 km/h

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    SüdtirolSüdtirolCounter-attacks & crosses
    vs
    AscoliAscoliPossession & high press
    The model's lean: 2 · Ascoli (42%)

    Südtirol vs Ascoli · Serie B

    1 · Südtirol 30%X 28%42% Ascoli · 2

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    Analysis: Südtirol – Ascoli

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

    The numbers tell a compelling story when Südtirol faces Ascoli, despite the hosts' unbeaten streak of eight league matches. The model gives Ascoli a clear edge with a 42% win probability, suggesting that the visitors' possession and high-press style might unsettle Südtirol, who prefer counterattacks and crossing. With both teams showing different strengths and weaknesses, the game's outcome hangs in a delicate balance.

    Südtirol may have collected more points, but Ascoli edges them in expected metrics. The hosts' xPoints of 6.9 are overshadowed by their visitors' 7.3, despite the actual points tally favoring Südtirol. The expected goals (xG) figures further tilt the scales; Ascoli's 1.7 xG per match points to a sharper attack compared to Südtirol's 0.85. However, Südtirol's slightly superior defense, with an xGA of 1.2 against Ascoli's 1.4, could keep them in the game, especially in adverse weather conditions, which usually dampen scoring.

    Considering the likelihood of goals, the model leans towards a high-scoring affair. There's a 54% chance of hitting over 2.5 goals, and a 57% probability that both sides will find the net. This inclination towards goals, coupled with the wet conditions, suggests a cautious approach might be prudent.

    The sharpest angle here is the value on Ascoli's win at odds of 2.85 with LeoVegas, presenting a notable 20% edge according to the model. Despite Südtirol's unbeaten run, the model's most likely scoreline is a 1-1 draw (12%), though a 1-2 or 0-1 win for the visitors are close alternatives (9% each). For those seeking a more conservative play, backing over 2.5 goals at 1.88 is another angle, albeit with a smaller margin. Both positions leverage the numbers effectively, offering a calculated approach to this Serie B clash.

    SüdtirolSüdtirol
    Form WDWDW
    League ranking xG #18xGA #10xT #20xP/match #8Points #3
    Key players
    • Aljosa VasicFxG 0.15 · xT 0.04
    • Alvin Obinna Obinna OkoroFxG 0.42 · xT -0.01
    • Silvio MerkajFxG 0.11 · xT 0.06
    AscoliAscoli
    Form WDWLW
    League ranking xG #3xGA #18xT #5xP/match #6Points #5
    Key players
    • Andrea SilipoRWxG 0.23 · xT 0.18
    • Matteo Luigi BrunoriFxG 0.97 · xT 0.10
    • Abdoul Razack GuiébréLWBxG 0.08 · xT 0.06

    Match prediction: Südtirol – Ascoli

    Predicted score matrix

    Ascoli →
    Südtirol →
    0
    1
    2
    3
    4+
    0
    0–06.2%
    0–18.6%
    0–26.8%
    0–33.4%
    0–4+1.8%
    1
    1–07.4%
    1–112.1%
    1–28.9%
    1–34.5%
    1–4+2.4%
    2
    2–05.1%
    2–17.7%
    2–25.9%
    2–33.0%
    2–4+1.6%
    3
    3–02.2%
    3–13.4%
    3–22.6%
    3–31.3%
    3–4+0.7%
    4+
    4+–01.0%
    4+–11.5%
    4+–21.1%
    4+–30.6%
    4+–4+0.3%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-112%
    2. 2.1-29%
    3. 3.0-19%
    4. 4.2-18%
    5. 5.1-07%
    Expected goals
    1,31–1,52
    Both teams to score
    57%

    Over/under goals

    Expected goals: 2,8
    Under 2,546%
    @1.75
    Over 2,554%
    @1.95EV+5%

    Ready-made bet suggestions

    More combos & build your own →

    01 · 2 legs

    Safe

    • Double chance Ascoli or draw (X2)68%
    • Over 1.5 goals78%

    Combined probability

    53%

    Fair odds

    1.90

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

    02 · 3 legs

    Balanced

    • Double chance Ascoli or draw (X2)68%
    • Over 2.5 goals54%
    • Don Bolsius to score21%

    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 score57%
    • Over 2.5 goals54%
    • Don Bolsius to score21%
    • Samuele Damiani to be booked22%

    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+).

    • 2 · Ascoli42% probability@2.90BetsafeEV+22%reference odds
    • 2 · Ascoli42% probability@2.90NordicbetEV+22%reference odds
    • 2 · Ascoli42% probability@2.85LeoVegasEV+20%reference odds
    Bookmaker1 · SüdtirolX2 · Ascoli
    Betsafe2.353.10
    EV+ 22%
    2.90
    LeoVegas2.383.05
    EV+ 20%
    2.85
    Nordicbet2.353.10
    EV+ 22%
    2.90

    Odds updated 2 Oct, 07:36

    Statistics

    Key facts

    • Sudtirol are unbeaten in their last 8 league matches.
    xG & xGA per match — 3-game rolling average

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

    Südtirol
    Ascoli
    When goals are scored and conceded — 2026
    Südtirol (9–3)
    Ascoli (7–4)
    Pass networks

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

    Südtirol
    Andrea Giorgini: 305 passningar, xT 0.29GiorginiRiccardo Stivanello: 247 passningar, xT 0.32StivanelloFabio Rispoli: 217 passningar, xT 0.2RispoliSimone Tronchin: 215 passningar, xT 0.02TronchinSalvatore Molina: 193 passningar, xT 0.57MolinaAlessandro Plizzari: 186 passningar, xT 0.07PlizzariGiacomo Stabile: 125 passningar, xT 0.17StabileBjarki Steinn Bjarkason: 92 passningar, xT 0.55BjarkasonDavide Veroli: 86 passningar, xT 0.08VeroliVasco Rafael Fortes Lopes: 85 passningar, xT 0.06LopesAljosa Vasic: 53 passningar, xT 0.11Vasic
    Ascoli
    Marcos Curado: 315 passningar, xT 1.12CuradoNicholas Rizzo: 286 passningar, xT 0.65RizzoSamuele Damiani: 246 passningar, xT 0.32DamianiTommaso Milanese: 205 passningar, xT 0.21MilaneseAbdoul Razack Guiébré: 176 passningar, xT 0.09GuiébréGiovanni Corradini: 175 passningar, xT 0.81CorradiniSamuele Vitale: 139 passningar, xT 0.02VitaleSimone D'Uffizi: 116 passningar, xT 0.85D'UffiziAndrea Silipo: 94 passningar, xT 0.57SilipoDon Bolsius: 54 passningar, xT -0.03BolsiusSergiu Perciun: 49 passningar, xT -0.03Perciun
    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: 305 passningar, xT 0.29GiorginiRiccardo Stivanello: 247 passningar, xT 0.32StivanelloFabio Rispoli: 217 passningar, xT 0.2RispoliSimone Tronchin: 215 passningar, xT 0.02TronchinSalvatore Molina: 193 passningar, xT 0.57MolinaAlessandro Plizzari: 186 passningar, xT 0.07PlizzariGiacomo Stabile: 125 passningar, xT 0.17StabileBjarki Steinn Bjarkason: 92 passningar, xT 0.55BjarkasonDavide Veroli: 86 passningar, xT 0.08VeroliVasco Rafael Fortes Lopes: 85 passningar, xT 0.06LopesAljosa Vasic: 53 passningar, xT 0.11Vasic
    Ascoli
    Marcos Curado: 315 passningar, xT 1.12CuradoNicholas Rizzo: 286 passningar, xT 0.65RizzoSamuele Damiani: 246 passningar, xT 0.32DamianiTommaso Milanese: 205 passningar, xT 0.21MilaneseAbdoul Razack Guiébré: 176 passningar, xT 0.09GuiébréGiovanni Corradini: 175 passningar, xT 0.81CorradiniSamuele Vitale: 139 passningar, xT 0.02VitaleSimone D'Uffizi: 116 passningar, xT 0.85D'UffiziAndrea Silipo: 94 passningar, xT 0.57SilipoDon Bolsius: 54 passningar, xT -0.03BolsiusSergiu Perciun: 49 passningar, xT -0.03Perciun

    The teams in numbers

    PerformanceSüdtirolAscoli
    Points1110
    xPoints6.97.3
    xG per match0.851.7
    xGA per match1.21.4
    xG within 8s of winning the ball0.180.44
    xGA within 8s of losing the ball0.260.32
    Playing styleSüdtirolAscoli
    Build-up efficiency0.330.3
    Field tilt0.360.68
    xT per match0.521.1
    xTA per match1.10.94
    Won balls, offensive half1326
    Pressing intensity0.240.22
    Pressing efficiency0.270.35
    Pressing efficiency, offensive half0.250.37
    Entries into the box per match514
    Entries into the box against1411
    Pass completion %0.820.81
    Pass completion % under pressure0.750.78
    Passes per match383411
    Passes against per match370225
    Switches of play per match17.624.7
    Long balls per match2328
    Set piecesSüdtirolAscoli
    xG from free kicks00.05
    Corners per match2.46.6
    Corners against per match7.54.4
    xG per corner0.020.03
    xGA per corner against0.010.07
    First touch, offensive corners %0.330.33
    First touch, defensive corners %0.630.68
    OtherSüdtirolAscoli
    Throw-in control0.680.7
    The goalkeepersAlessandro Plizzari (Südtirol)Samuele Vitale (Ascoli)
    Saves1713
    Save %85%77%
    xG prevented51%60%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Südtirol vs Ascoli according to our model?

    The model gives Ascoli a 42% win probability. Full 1X2 picture: Südtirol 30%, draw 28%, Ascoli 42%.

    What is the most likely scoreline?

    The model's most likely final score is 1-1 at 12% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 54% and under at 46%.

    Will both teams score?

    The probability of both teams scoring is 57% 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.