Premier LeagueVilla Park, Birmingham10°14 km/h

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    Aston VillaAston VillaLow block & direct
    vs
    FulhamFulhamPossession control
    The model's lean: 1 · Aston Villa (49%)Best value by the model: Under 2,5 @ 2.11 (+0 %)

    Aston Villa vs Fulham · Premier League

    1 · Aston Villa 49%X 26%25% Fulham · 2

    Prediction summary

    BetBuilders AI model prediction for Aston Villa vs Fulham (Premier League, Saturday, 31 October 2026): Aston Villa win 49%, draw 26%, Fulham win 25%. Expected goals (xG): Aston Villa 1.59, Fulham 1.18. Most likely score: 1-1 (12%). Over 2.5 goals 53%, both teams to score 56%. Double chance: Aston Villa or draw 75%, Fulham or draw 51%. Prediction updated Friday, 23 October 2026.

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    Analysis: Aston Villa – Fulham

    Anna Karlsson · · A data-driven preview · How the predictions work

    Aston Villa's home edge at 49% probability stands out as the key factor. Set against Fulham's 25% chance, it underscores a tilt towards the hosts. Villa's record of winning 55% of their home matches is a strong historical marker, albeit with a small head-to-head sample since 2022, where Villa lead 3-1 in wins. The odds offered by LeoVegas at 2.08 for a Villa win suggest a valuable opportunity with a 2% edge.

    Despite Villa's edge in points, Fulham's underlying statistics show efficiency. They lead in expected points and xG per match, suggesting they can make possession count. However, Villa's direct style, especially at home, might disrupt Fulham's control strategy, despite the latter's better defensive numbers. The expected goals lean towards a narrow Villa advantage at 1.59 to 1.18. The most likely scorelines of 1-1 and 1-0 reflect a likely tight contest.

    Weather plays a subtle role, with the forecasted rain potentially dampening goal expectancy. Despite a 53% chance for over 2.5 goals, the conditions might suppress scoring opportunities. The model's preference for Villa at odds of 2.08 with LeoVegas remains the sharpest angle, hinting at a likely 1-0 or 2-1 win for the hosts.

    Aston VillaAston Villa
    Form DLWDW
    League ranking xG #14xGA #15xT #20xP/match #14Points #11
    Key players
    • Nicolas JacksonFxG 0.31 · xT 0.12
    • Johan ManzambiCAMxG 0.56 · xT 0.10
    • John McGinnRWxG 0.15 · xT 0.07
    FulhamFulham
    Form LDDLW
    League ranking xG #8xGA #4xT #4xP/match #7Points #18
    Key players
    • Alex IwobiLWxG 0.12 · xT 0.38
    • Antonee RobinsonLWBxG 0.05 · xT 0.09
    • Joachim AndersenCBxG 0.00 · xT 0.06

    Match prediction: Aston Villa – Fulham

    Predicted score matrix

    Fulham →
    Aston Villa →
    0
    1
    2
    3
    4+
    0
    0–06.6%
    0–17.0%
    0–24.4%
    0–31.7%
    0–4+0.7%
    1
    1–09.6%
    1–112.1%
    1–26.9%
    1–32.7%
    1–4+1.0%
    2
    2–07.9%
    2–19.4%
    2–25.5%
    2–32.2%
    2–4+0.8%
    3
    3–04.2%
    3–15.0%
    3–22.9%
    3–31.2%
    3–4+0.4%
    4+
    4+–02.4%
    4+–12.8%
    4+–21.7%
    4+–30.7%
    4+–4+0.3%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-112%
    2. 2.1-010%
    3. 3.2-19%
    4. 4.2-08%
    5. 5.0-17%
    Expected goals
    1,59–1,18
    Both teams to score
    56%

    Over/under goals

    Expected goals: 2,8
    Under 2,547%
    @2.11EV+0%
    Over 2,553%
    @1.74

    Ready-made bet suggestions

    More combos & build your own →

    01 · 2 legs

    Safe

    • Aston Villa to win49%
    • Over 1.5 goals77%

    Combined probability

    37%

    Fair odds

    2.71

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

    02 · 3 legs

    Balanced

    • Aston Villa to win49%
    • Over 2.5 goals53%
    • Johan Manzambi to score23%

    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 score56%
    • Over 2.5 goals53%
    • Gonzalo García Torres to score23%
    • Shea Emmanuel Charles to be booked25%

    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 2.547% probability@2.11BetsafeEV+0%reference odds
    • Under 2.547% probability@2.11NordicbetEV+0%reference odds
    Bookmaker1 · Aston VillaX2 · Fulham
    Betsafe1.883.753.80
    LeoVegas1.953.703.60
    Nordicbet1.903.753.85

    Odds updated 25 Oct, 08:36

    Odds movement

    1-6 %
    49 %44 %

    2.08 → 1.95

    X+3 %
    29 %24 %

    3.60 → 3.70

    2+7 %
    30 %25 %

    3.35 → 3.60

    Over 2,50 %
    57 %52 %

    1.70 → 1.70

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

    Statistics

    Head-to-head

    4 matches
    Aston Villa 3Draw 0Fulham 1
    Goals: 7–3 (⌀ 2,5)

    Head-to-head based on Premier League data since 2022.

    Key facts

    • Aston Villa win 55% of their home matches all-time (42 played).
    xG & xGA per match — 3-game rolling average

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

    Aston Villa
    Fulham
    When goals are scored and conceded — 2026
    Aston Villa (7–11)
    Fulham (7–10)
    Pass networks

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

    Aston Villa
    Victor Lindelöf: 272 passningar, xT 0.47LindelöfBoubacar Kamara: 216 passningar, xT 0.3KamaraTyrone Mings: 201 passningar, xT 0.08MingsZion Suzuki: 154 passningar, xT 0.12SuzukiRoss Barkley: 142 passningar, xT 0.05BarkleyMatty Cash: 138 passningar, xT 0.04CashEmiliano Buendia: 107 passningar, xT 0.07BuendiaAaron Wan-Bissaka: 106 passningar, xT 0.2Wan-BissakaJohn McGinn: 94 passningar, xT 0.36McGinnJoao Gomes: 86 passningar, xT 0.45GomesIan Maatsen: 70 passningar, xT 0.29Maatsen
    Fulham
    Calvin Bassey: 286 passningar, xT 0.43BasseySander Berge: 255 passningar, xT 0.12BergeDavid Affengruber: 249 passningar, xT 0.16AffengruberAlex Iwobi: 228 passningar, xT 1.98IwobiShea Charles: 225 passningar, xT 0.19CharlesTimothy Castagne: 218 passningar, xT 0.53CastagneBernd Leno: 177 passningar, xT -0.06LenoAntonee Robinson: 160 passningar, xT 0.45RobinsonJosh King: 138 passningar, xT 0.57KingOscar Bobb: 99 passningar, xT 0.42BobbJoachim Andersen: 91 passningar, xT 0.07Andersen
    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.

    Aston Villa
    Victor Lindelöf: 272 passningar, xT 0.47LindelöfBoubacar Kamara: 216 passningar, xT 0.3KamaraTyrone Mings: 201 passningar, xT 0.08MingsZion Suzuki: 154 passningar, xT 0.12SuzukiRoss Barkley: 142 passningar, xT 0.05BarkleyMatty Cash: 138 passningar, xT 0.04CashEmiliano Buendia: 107 passningar, xT 0.07BuendiaAaron Wan-Bissaka: 106 passningar, xT 0.2Wan-BissakaJohn McGinn: 94 passningar, xT 0.36McGinnJoao Gomes: 86 passningar, xT 0.45GomesIan Maatsen: 70 passningar, xT 0.29Maatsen
    Fulham
    Calvin Bassey: 286 passningar, xT 0.43BasseySander Berge: 255 passningar, xT 0.12BergeDavid Affengruber: 249 passningar, xT 0.16AffengruberAlex Iwobi: 228 passningar, xT 1.98IwobiShea Charles: 225 passningar, xT 0.19CharlesTimothy Castagne: 218 passningar, xT 0.53CastagneBernd Leno: 177 passningar, xT -0.06LenoAntonee Robinson: 160 passningar, xT 0.45RobinsonJosh King: 138 passningar, xT 0.57KingOscar Bobb: 99 passningar, xT 0.42BobbJoachim Andersen: 91 passningar, xT 0.07Andersen

    The teams in numbers

    PerformanceAston VillaFulham
    Points85
    xPoints910.6
    xG per match1.21.6
    xGA per match1.61.1
    xG within 8s of winning the ball0.290.35
    xGA within 8s of losing the ball0.40.17
    Playing styleAston VillaFulham
    Build-up efficiency0.30.33
    Field tilt0.440.54
    xT per match0.591.2
    xTA per match1.21.1
    Won balls, offensive half1820
    Pressing intensity0.240.26
    Pressing efficiency0.260.28
    Pressing efficiency, offensive half0.220.26
    Entries into the box per match1116
    Entries into the box against1313
    Pass completion %0.760.81
    Pass completion % under pressure0.720.76
    Passes per match328498
    Passes against per match375361
    Switches of play per match16.431.3
    Long balls per match2229
    Set piecesAston VillaFulham
    xG from free kicks0.020
    Corners per match3.16.3
    Corners against per match4.24.4
    xG per corner0.010.01
    xGA per corner against0.020.04
    First touch, offensive corners %0.450.4
    First touch, defensive corners %0.630.5
    OtherAston VillaFulham
    Throw-in control0.680.76
    The goalkeepersZion Suzuki (Aston Villa)Bernd Leno (Fulham)
    Saves1920
    Save %73%67%
    xG prevented53%51%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Aston Villa vs Fulham according to our model?

    The model gives Aston Villa a 49% win probability. Full 1X2 picture: Aston Villa 49%, draw 26%, Fulham 25%.

    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 53% and under at 47%.

    Will both teams score?

    The probability of both teams scoring is 56% according to the model.

    How many goals are expected in Aston Villa vs Fulham?

    The model expects 1.59 goals (xG) for Aston Villa and 1.18 for Fulham, 2.78 in total.

    What does the model say about double chance?

    Aston Villa or draw (1X) 75%, Fulham or draw (X2) 51% and no draw (12) 74%.

    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.