EFL League OnePlough Lane, London16°0,6 mm18 km/h

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    WimbledonWimbledonCounter-attacks & crosses
    vs
    Milton Keynes DonsMilton Keynes DonsLow block & direct
    The model's lean: 1 · Wimbledon (38%)

    WimbledonMilton Keynes Dons · EFL League One

    1 · Wimbledon 38%X 30%32% Milton Keynes Dons · 2

    Analysis: WimbledonMilton Keynes Dons

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

    TEXT:

    In their recent matchups, Wimbledon and Milton Keynes Dons present a compelling contrast in styles. While the sample size from their head-to-head clashes is quite limited, the model leans toward a Wimbledon win at 38%, with a 30% likelihood of a draw and a 32% chance for MK Dons. The tilt in favor of Wimbledon aligns with their home advantage and the fact that they have accumulated more points so far this season, suggesting a slim edge for the hosts.

    Wimbledon's approach of counter attacks and crossing could exploit weaknesses in Milton Keynes' low defensive setup. Despite this tactical advantage, the statistics indicate a more nuanced picture. The visitors boast superior xG per match at 1.8 compared to Wimbledon's 1.0, suggesting MK Dons are more potent when pushing forward, albeit the hosts have a slightly better defensive record with an xGA of 1.2 against the visitors' 1.6. This defensive edge might help Wimbledon in stifling MK Dons' direct play.

    Given the expected goals, a tight contest is in the cards. The most likely scoreline is a 1-1 draw at 13%, closely followed by a 1-0 result for Wimbledon at 12%. Both teams to score is pegged at 47%, suggesting a balanced matchup with limited action. Additionally, the anticipated rain of 7.2 mm could dampen the attacking prowess of both sides, contributing to a lower goal expectation already reflected in the model's numbers.

    For those exploring betting opportunities, the under 2.5 goals market presents some value, with only a 41% chance of the total exceeding this line.

    WimbledonWimbledon
    Form LDWLW
    League ranking xG #20xGA #8xT #13xP/match #18Points #9
    Key players
    • Jayden Connor StockleyFxG 0.29 · xT 0.03
    • Steven Jeffrey SeddonLWxG 0.01 · xT 0.12
    • Isaac Ifeoluwa Foloronso Olushore OgundereCBxG 0.00 · xT 0.07
    Milton Keynes DonsMilton Keynes Dons
    Form DDDLD
    League ranking xG #6xGA #15xT #4xP/match #9Points #19
    Key players
    • Aaron Graham John CollinsFxG 0.51 · xT 0.24
    • Callum Thomas Owen PatersonLWxG 0.62 · xT 0.01
    • Daniel Tan BarlaserCMxG 0.02 · xT 0.16

    Match prediction: WimbledonMilton Keynes Dons

    Predicted score matrix

    Milton Keynes Dons
    Wimbledon
    0
    1
    2
    3
    4+
    0
    0–010.0%
    0–19.3%
    0–24.9%
    0–31.7%
    0–4+0.5%
    1
    1–012.4%
    1–113.3%
    1–26.5%
    1–32.2%
    1–4+0.7%
    2
    2–08.5%
    2–18.6%
    2–24.3%
    2–31.5%
    2–4+0.5%
    3
    3–03.8%
    3–13.8%
    3–21.9%
    3–30.6%
    3–4+0.2%
    4+
    4+–01.7%
    4+–11.7%
    4+–20.9%
    4+–30.3%
    4+–4+0.1%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-113%
    2. 2.1-012%
    3. 3.0-010%
    4. 4.0-19%
    5. 5.2-19%
    Expected goals
    1,331,01
    Both teams to score
    47%

    Over/under goals

    Expected goals: 2,3
    Under 2,559%
    Over 2,541%

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Double chance Wimbledon or draw (1X)72%
    • Under 3.5 goals79%

    Combined probability

    57%

    Fair odds

    1.76

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

    02 · 3 legs

    Balanced

    • Double chance Wimbledon or draw (1X)72%
    • Under 2.5 goals59%
    • Jayden Connor Stockley 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 score47%
    • Over 2.5 goals41%
    • Aaron Graham John Collins to score23%
    • Alistair Oluwashaun Smith 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

    No odds available yet.

    Statistics

    xG & xGA per match — 3-game rolling average

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

    Wimbledon
    Milton Keynes Dons
    When goals are scored and conceded 2026
    Wimbledon (47)
    Milton Keynes Dons (79)
    Pass networks

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

    Wimbledon
    Ryan Anthony Johnson: 163 passningar, xT 0.49JohnsonSteven Jeffrey Seddon: 157 passningar, xT 0.62SeddonDaniel Liam Sweeney: 138 passningar, xT 0.1SweeneyAlistair Oluwashaun Smith: 135 passningar, xT 0.07SmithIsaac Ifeoluwa Foloronso Olushore Ogundere: 126 passningar, xT 0.26OgundereJames Tilley: 113 passningar, xT 0.75TilleyMyles Elliot Zach Hippolyte: 86 passningar, xT 0.76HippolyteZack Nelson: 84 passningar, xT 0.02NelsonZeze Steven Sessegnon: 55 passningar, xT 0.3SessegnonJoseph Patrick McDonnell: 49 passningar, xT 0.31McDonnellAndrew Kyere Yiadom: 47 passningar, xT 0.14Yiadom
    Milton Keynes Dons
    Daniel Tan Barlaser: 147 passningar, xT 0.54BarlaserCraig Macgillivray: 127 passningar, xT 0.28MacgillivrayCurtis Alexander Nelson: 126 passningar, xT 0.33NelsonRyan Frank Wintle: 116 passningar, xT 0.33WintleMarvin Akpereogene Paul Edem Ekpiteta: 113 passningar, xT 0.14EkpitetaCohen Conrad Bramall: 101 passningar, xT 1.02BramallCharles James Goode: 101 passningar, xT 0.06GoodeGethin Wynne Jones: 72 passningar, xT 0.65JonesBenjamin Jack Wiles: 40 passningar, xT 0.13WilesRyan Barnett: 33 passningar, xT 0.83BarnettSamuel Tshiayima Nombe: 31 passningar, xT 0.34Nombe
    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.

    Wimbledon
    Ryan Anthony Johnson: 163 passningar, xT 0.49JohnsonSteven Jeffrey Seddon: 157 passningar, xT 0.62SeddonDaniel Liam Sweeney: 138 passningar, xT 0.1SweeneyAlistair Oluwashaun Smith: 135 passningar, xT 0.07SmithIsaac Ifeoluwa Foloronso Olushore Ogundere: 126 passningar, xT 0.26OgundereJames Tilley: 113 passningar, xT 0.75TilleyMyles Elliot Zach Hippolyte: 86 passningar, xT 0.76HippolyteZack Nelson: 84 passningar, xT 0.02NelsonZeze Steven Sessegnon: 55 passningar, xT 0.3SessegnonJoseph Patrick McDonnell: 49 passningar, xT 0.31McDonnellAndrew Kyere Yiadom: 47 passningar, xT 0.14Yiadom
    Milton Keynes Dons
    Daniel Tan Barlaser: 147 passningar, xT 0.54BarlaserCraig Macgillivray: 127 passningar, xT 0.28MacgillivrayCurtis Alexander Nelson: 126 passningar, xT 0.33NelsonRyan Frank Wintle: 116 passningar, xT 0.33WintleMarvin Akpereogene Paul Edem Ekpiteta: 113 passningar, xT 0.14EkpitetaCohen Conrad Bramall: 101 passningar, xT 1.02BramallCharles James Goode: 101 passningar, xT 0.06GoodeGethin Wynne Jones: 72 passningar, xT 0.65JonesBenjamin Jack Wiles: 40 passningar, xT 0.13WilesRyan Barnett: 33 passningar, xT 0.83BarnettSamuel Tshiayima Nombe: 31 passningar, xT 0.34Nombe

    The teams in numbers

    PerformanceWimbledonMilton Keynes Dons
    Points74
    xPoints5.67.6
    xG per match11.8
    xGA per match1.21.6
    xG within 8s of winning the ball0.180.32
    xGA within 8s of losing the ball0.10.41
    Playing styleWimbledonMilton Keynes Dons
    Build-up efficiency0.330.33
    Field tilt0.550.36
    xT per match0.961.3
    xTA per match11
    Won balls, offensive half3130
    Pressing intensity0.250.25
    Pressing efficiency0.360.28
    Pressing efficiency, offensive half0.320.26
    Entries into the box per match1212
    Entries into the box against1115
    Pass completion %0.670.65
    Pass completion % under pressure0.660.59
    Passes per match267230
    Passes against per match285351
    Switches of play per match15.623.8
    Long balls per match2738
    Set piecesWimbledonMilton Keynes Dons
    xG from free kicks0.080.11
    Corners per match5.65.3
    Corners against per match5.66.3
    xG per corner0.040.07
    xGA per corner against0.020.03
    First touch, offensive corners %0.290.35
    First touch, defensive corners %0.750.52
    OtherWimbledonMilton Keynes Dons
    Throw-in control0.720.68
    The goalkeepersJoseph Patrick McDonnell (Wimbledon)Craig Macgillivray (Milton Keynes Dons)
    Saves1121
    Save %79%70%
    xG prevented61%62%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Wimbledon vs Milton Keynes Dons according to our model?

    The model gives Wimbledon a 38% win probability. Full 1X2 picture: Wimbledon 38%, draw 30%, Milton Keynes Dons 32%.

    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 41% and under at 59%.

    Will both teams score?

    The probability of both teams scoring is 47% 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.