Serie AStadio Olimpico Grande Torino, Torino21°30,6 mm7 km/h

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    TorinoTorinoLow block & direct
    vs
    AC MilanAC MilanBalanced & physical
    The model's lean: 2 · AC Milan (46%)Best value by the model: 1 · Torino @ 4.75 (+13 %)

    Torino – AC Milan · Serie A

    1 · Torino 24%X 30%46% AC Milan · 2

    Analysis: Torino – AC Milan

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

    3.1 goals per meeting on average. That number jumps off the page when considering Torino FC and AC Milan's recent clashes. Yet, the expected weather — a drenching 26.7 mm of rain — may put a dampener on proceedings, potentially suppressing goal numbers this time around. AC Milan might have the upper hand in this matchup, but the weather is an equalizer that can't be ignored.

    AC Milan, armed with a muscular and balanced approach, struts into the ring with a 46% win probability, a clear model lean in their favor. Their 1.56 expected goals suggest that the Rossoneri could slice through Torino's direct yet porous defense, which concedes 1.6 goals per game. AC Milan's form hasn't gone unnoticed either, with a solid total of 70 points compared to Torino's 45, and a tangible edge in xPoints and xGA per match.

    Torino, though, seems to relish their role as the underdog. Their historical record shows they've managed to scrape out three wins in their last ten meetings with AC Milan — a small sample, sure, but enough to make Milan wary. The odds are tantalizing for the braver punters out there, with Betsson, Nordicbet, and Betsafe all offering EV+ value at odds of 4.75 or 4.7 for a home win. The model's rating of 24% indicates a juicy 12-13% edge.

    Predicting a scoreline is never a science, but a 1-0 or 1-1 outcome feels plausible, given the weather's chilling effect on attacking play. With a 48% chance of over 2.5 goals, the lean is still slightly towards the under, especially with the rain factored in. Torino's ability to upset the odds, combined with a soggy pitch, might just keep things tighter than usual. Follow the numbers and take a punt on a low-scoring draw, but if you're feeling adventurous, those home win odds are hard to ignore.

    TorinoTorino
    Form DLWLD
    League ranking xG #9xGA #17xT #13xP/match #9Points #13
    Key players
    • Giovanni SimeoneFxG 0.31 · xT 0.01
    • Nikola VlašićCAMxG 0.24 · xT 0.10
    • Valentino LazaroLWBxG 0.03 · xT 0.15
    AC MilanAC Milan
    Form DLLWL
    League ranking xG #6xGA #7xT #4xP/match #5Points #5
    Key players
    • Alexis SaelemaekersRWxG 0.11 · xT 0.18
    • Christopher NkunkuFxG 0.47 · xT 0.06
    • Adrien RabiotCMxG 0.16 · xT 0.15

    Match prediction: Torino – AC Milan

    Predicted score matrix

    AC Milan →
    Torino →
    0
    1
    2
    3
    4+
    0
    0–07.9%
    0–111.5%
    0–29.3%
    0–34.8%
    0–4+2.7%
    1
    1–07.4%
    1–112.4%
    1–29.4%
    1–34.9%
    1–4+2.7%
    2
    2–03.9%
    2–16.1%
    2–24.8%
    2–32.5%
    2–4+1.4%
    3
    3–01.3%
    3–12.1%
    3–21.6%
    3–30.8%
    3–4+0.5%
    4+
    4+–00.4%
    4+–10.7%
    4+–20.5%
    4+–30.3%
    4+–4+0.1%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-112%
    2. 2.0-111%
    3. 3.1-29%
    4. 4.0-29%
    5. 5.0-08%
    Expected goals
    1,02–1,56
    Both teams to score
    51%

    Over/under goals

    Expected goals: 2,6
    Under 2,552%
    @1.89
    Over 2,548%
    @1.93

    Ready-made bet suggestions

    More combos & build your own →

    01 · 2 legs

    Safe

    • AC Milan to win46%
    • Under 3.5 goals74%

    Combined probability

    35%

    Fair odds

    2.86

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

    02 · 3 legs

    Balanced

    • AC Milan to win46%
    • Under 2.5 goals52%
    • Christopher Alan Nkunku to score28%

    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 score51%
    • Over 2.5 goals48%
    • Christopher Alan Nkunku to score28%
    • Davide Bartesaghi to be booked19%

    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 · Torino24% probability@4.75BetssonEV+13%reference odds
    • 1 · Torino24% probability@4.75NordicbetEV+13%reference odds
    • 1 · Torino24% probability@4.70BetsafeEV+12%reference odds
    Bookmaker1 · TorinoX2 · AC Milan
    Betsafe
    EV+ 12%
    4.70
    EV+ 4%
    3.50    		1.78
    Betsson
    EV+ 13%
    4.75
    EV+ 4%
    3.50    		1.80
    Nordicbet
    EV+ 13%
    4.75
    EV+ 4%
    3.50    		1.80

    Odds updated 18 Aug, 19:36

    Odds movement

    1+6 %
    23 %18 %

    4.50 → 4.75

    X-4 %
    29 %24 %

    3.65 → 3.50

    20 %
    55 %50 %

    1.80 → 1.80

    Over 2,50 %
    52 %47 %

    1.93 → 1.93

    Betsson · 3 recorded price levels · 18/08/2026 → 18/08/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    10 matches
    Torino 3Draw 2AC Milan 5
    Goals: 14–17 (⌀ 3,1)

    Head-to-head based on Serie A data since 2021.

    Key facts

    • A high-scoring fixture: 3.1 goals per meeting on average.
    xG & xGA per match — 3-game rolling average

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

    Torino
    AC Milan
    When goals are scored and conceded — 2025
    Torino (44–63)
    AC Milan (53–35)
    Pass networks

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

    Torino
    Enzo Ebosse: 263 passningar, xT 0.65EbosseSaúl Coco: 188 passningar, xT 0.43CocoNikola Vlašić: 177 passningar, xT -0.09VlašićRafael Obrador Burguera: 124 passningar, xT 0.13BurgueraAlberto Paleari: 123 passningar, xT 0.16PaleariLuca Marianucci: 114 passningar, xT 0.34MarianucciEmirhan Ilkhan: 112 passningar, xT 0.2IlkhanGvidas Gineitis: 99 passningar, xT 0.3GineitisMatteo Prati: 85 passningar, xT 0.2PratiArdian Ismajli: 75 passningar, xT 0.08IsmajliValentino Lazaro: 72 passningar, xT 0.49Lazaro
    AC Milan
    Strahinja Pavlović: 246 passningar, xT 0.27PavlovićMatteo Gabbia: 229 passningar, xT 0.09GabbiaAdrien Rabiot: 180 passningar, xT 1.07RabiotFikayo Tomori: 114 passningar, xT 0.28TomoriAlexis Saelemaekers: 111 passningar, xT 0.48SaelemaekersMike Maignan: 111 passningar, xT 0.1MaignanDavide Bartesaghi: 102 passningar, xT 0.38BartesaghiArdon Jashari: 91 passningar, xT 0.25JashariYoussouf Fofana: 77 passningar, xT -0.06FofanaSamuele Ricci: 76 passningar, xT 0.12RicciZachary Athekame: 72 passningar, xT 0.34Athekame
    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.

    Torino
    Enzo Ebosse: 263 passningar, xT 0.65EbosseSaúl Coco: 188 passningar, xT 0.43CocoNikola Vlašić: 177 passningar, xT -0.09VlašićRafael Obrador Burguera: 124 passningar, xT 0.13BurgueraAlberto Paleari: 123 passningar, xT 0.16PaleariLuca Marianucci: 114 passningar, xT 0.34MarianucciEmirhan Ilkhan: 112 passningar, xT 0.2IlkhanGvidas Gineitis: 99 passningar, xT 0.3GineitisMatteo Prati: 85 passningar, xT 0.2PratiArdian Ismajli: 75 passningar, xT 0.08IsmajliValentino Lazaro: 72 passningar, xT 0.49Lazaro
    AC Milan
    Strahinja Pavlović: 246 passningar, xT 0.27PavlovićMatteo Gabbia: 229 passningar, xT 0.09GabbiaAdrien Rabiot: 180 passningar, xT 1.07RabiotFikayo Tomori: 114 passningar, xT 0.28TomoriAlexis Saelemaekers: 111 passningar, xT 0.48SaelemaekersMike Maignan: 111 passningar, xT 0.1MaignanDavide Bartesaghi: 102 passningar, xT 0.38BartesaghiArdon Jashari: 91 passningar, xT 0.25JashariYoussouf Fofana: 77 passningar, xT -0.06FofanaSamuele Ricci: 76 passningar, xT 0.12RicciZachary Athekame: 72 passningar, xT 0.34Athekame

    The teams in numbers

    PerformanceTorinoAC Milan
    Points4570
    xPoints53.856.4
    xG per match1.31.6
    xGA per match1.61.3
    xG within 8s of winning the ball0.190.16
    xGA within 8s of losing the ball0.310.21
    Playing styleTorinoAC Milan
    Build-up efficiency0.330.33
    Field tilt0.40.52
    xT per match0.791.2
    xTA per match1.10.9
    Won balls, offensive half2423
    Pressing intensity0.230.23
    Pressing efficiency0.240.23
    Pressing efficiency, offensive half0.270.26
    Entries into the box per match1014
    Entries into the box against1311
    Pass completion %0.760.83
    Pass completion % under pressure0.710.79
    Passes per match316433
    Passes against per match427395
    Switches of play per match26.636.3
    Long balls per match3133
    Set piecesTorinoAC Milan
    xG from free kicks0.050.1
    Corners per match3.94.2
    Corners against per match4.74.3
    xG per corner0.060.07
    xGA per corner against0.060.05
    First touch, offensive corners %0.40.51
    First touch, defensive corners %0.510.61
    OtherTorinoAC Milan
    Throw-in control0.730.75
    The goalkeepersAlberto Paleari (Torino)Mike Maignan (AC Milan)
    Saves82109
    Save %66%76%
    xG prevented44%55%
    Claims0 (0%)0 (0%)

    Frequently asked questions

    Who wins Torino vs AC Milan according to our model?

    The model gives AC Milan a 46% win probability. Full 1X2 picture: Torino 24%, draw 30%, AC Milan 46%.

    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 48% and under at 52%.

    Will both teams score?

    The probability of both teams scoring is 51% 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.