EFL ChampionshipCardiff City Stadium, Cardiff16°4,9 mm21 km/h

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    Cardiff CityCardiff CityPossession control
    vs
    Stoke CityStoke CityPossession control
    The model's lean: 1 · Cardiff City (64%)

    Cardiff CityStoke City · EFL Championship

    1 · Cardiff City 64%X 20%16% Stoke City · 2

    Analysis: Cardiff CityStoke City

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

    Cardiff City face Stoke City with both teams tending towards possession control, suggesting a tactical battle over who dictates the pace. The hosts are favored, with a 64% model probability pointing towards a likely Cardiff City victory. This shapes up as a match where Cardiff will look to assert their home advantage — perhaps through patient build-up play — while Stoke might opt for compactness and quick transitions, hoping to exploit any spaces left by Cardiff's forward forays.

    The numbers underscore Cardiff's potential dominance in this encounter. Their expected goals stand at 2.09 compared to Stoke's 0.97, indicating a higher likelihood of converting chances. Despite having fewer points than Stoke this season, Cardiff's xPoints show they have been slightly unfortunate, hinting at underperformance relative to their chances. The odds offered by Betsafe, Betsson, and Nordicbet at 2.12 provide a significant edge, aligning with the model's estimation of a 64% home win probability.

    The head-to-head record here is limited, with just two matches since 2023, which saw Stoke coming out slightly better with one win and one draw. However, such a small sample weighs less heavily than Cardiff's current form and goal expectancy. The forecast of 4.9 mm of rain may dampen the tempo, often a recipe for fewer goals. Yet, the model still leans towards over 2.5 goals at 59%, suggesting the weather impact is already factored into the projection.

    Ultimately, the sharpest angle lies in backing Cardiff at odds of 2.12, with an attractive 36% edge. While the most likely scorelines — 2-0, 2-1, and 1-1 — all feature Cardiff scoring, the balance tips in favor of them achieving a solid home win, possibly with a clean sheet.

    Cardiff CityCardiff City
    Form DDDLL
    League ranking xG #10xGA #20xT #4xP/match #21Points #22
    Key players
    • Cian Ty AshfordLWxG 0.32 · xT 0.02
    • Yousef SalechFxG 0.43 · xT -0.02
    • Joel Matthew BaganCBxG 0.04 · xT 0.15
    Stoke CityStoke City
    Form LLLWW
    League ranking xG #21xGA #16xT #6xP/match #19Points #15
    Key players
    • Sam GallagherFxG 0.08 · xT 0.09
    • George David Eric HirstFxG 0.23 · xT 0.13
    • Jun Ho BaeRWxG 0.04 · xT 0.18

    Match prediction: Cardiff CityStoke City

    Predicted score matrix

    Stoke City
    Cardiff City
    0
    1
    2
    3
    4+
    0
    0–05.0%
    0–14.3%
    0–22.2%
    0–30.7%
    0–4+0.2%
    1
    1–09.6%
    1–19.8%
    1–24.6%
    1–31.5%
    1–4+0.4%
    2
    2–010.3%
    2–19.9%
    2–24.8%
    2–31.5%
    2–4+0.5%
    3
    3–07.2%
    3–16.9%
    3–23.3%
    3–31.1%
    3–4+0.3%
    4+
    4+–06.0%
    4+–15.8%
    4+–22.8%
    4+–30.9%
    4+–4+0.3%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.2-010%
    2. 2.2-110%
    3. 3.1-110%
    4. 4.1-010%
    5. 5.3-07%
    Expected goals
    2,090,97
    Both teams to score
    54%

    Over/under goals

    Expected goals: 3,1
    Under 2,541%
    @2.35
    Over 2,559%
    @1.60

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    01 · 2 legs

    Safe

    • Cardiff City to win64%
    • Over 1.5 goals81%

    Combined probability

    53%

    Fair odds

    1.88

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

    02 · 3 legs

    Balanced

    • Cardiff City to win64%
    • Over 2.5 goals59%
    • Yousef Salech to score38%

    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 score54%
    • Over 2.5 goals59%
    • Yousef Salech to score38%
    • Ethan Stuart William Galbraith 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+).

    • 1 · Cardiff City64% probability@2.16PinnacleEV+38%reference odds
    • 1 · Cardiff City64% probability@2.12BetsafeEV+36%reference odds
    • 1 · Cardiff City64% probability@2.12BetssonEV+36%reference odds
    Bookmaker1 · Cardiff CityX2 · Stoke City
    Betsafe
    EV+ 36%
    2.12
    3.603.20
    Betsson
    EV+ 36%
    2.12
    3.603.20
    Nordicbet
    EV+ 36%
    2.12
    3.603.20
    Pinnacle
    EV+ 38%
    2.16
    3.723.10

    Odds updated 6 Sept, 18:31

    Odds movement

    1+9 %
    48 %43 %

    1.992.16

    X+1 %
    28 %23 %

    3.703.72

    2-9 %
    32 %27 %

    3.393.10

    Pinnacle · 3 recorded price levels · 06/09/2026 → 06/09/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    2 matches
    Cardiff City 0Draw 1Stoke City 1
    Goals: 23 (⌀ 2,5)

    Head-to-head based on Championship data since 2023.

    xG & xGA per match — 3-game rolling average

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

    Cardiff City
    Stoke City
    When goals are scored and conceded 2026
    Cardiff City (69)
    Stoke City (89)
    Pass networks

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

    Cardiff City
    Joel Matthew Bagan: 348 passningar, xT 0.65BaganAlexander Sean Pablo Robertson: 315 passningar, xT 0.27RobertsonPerry Tian Hee Ng: 275 passningar, xT 0.7NgGabriel Jeremiah Adedayo Osho: 260 passningar, xT 0.54OshoKrystian Bielik: 165 passningar, xT 0.37BielikNathan Wallace Newman Trott: 162 passningar, xT 0.19TrottCalum Alexander Scanlon: 121 passningar, xT 0.38ScanlonRubin James Colwill: 112 passningar, xT -0.29ColwillOllie Anthony Tanner: 84 passningar, xT 1.2TannerJack Moylan: 77 passningar, xT 0.69MoylanCian Ty Ashford: 75 passningar, xT -0.04Ashford
    Stoke City
    Ben Wilmot: 194 passningar, xT 0.23WilmotEthan Stuart William Galbraith: 158 passningar, xT 0.25GalbraithEric Junior Bocat: 143 passningar, xT 0.38BocatEl Hadji Djibril Soumaré: 134 passningar, xT 0.14SoumaréLuke Graham: 97 passningar, xT 0.11GrahamViktor Johansson: 95 passningar, xT 0.11JohanssonBenjamin Anthony Johnson: 91 passningar, xT 0.44JohnsonBosun Lawal: 78 passningar, xT 0.08LawalMaksym Taloverov: 77 passningar, xT 0.13TaloverovBenjamin Sorba William Thomas: 52 passningar, xT 1.22ThomasJun Ho Bae: 48 passningar, xT 0.48Bae
    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.

    Cardiff City
    Joel Matthew Bagan: 348 passningar, xT 0.65BaganAlexander Sean Pablo Robertson: 315 passningar, xT 0.27RobertsonPerry Tian Hee Ng: 275 passningar, xT 0.7NgGabriel Jeremiah Adedayo Osho: 260 passningar, xT 0.54OshoKrystian Bielik: 165 passningar, xT 0.37BielikNathan Wallace Newman Trott: 162 passningar, xT 0.19TrottCalum Alexander Scanlon: 121 passningar, xT 0.38ScanlonRubin James Colwill: 112 passningar, xT -0.29ColwillOllie Anthony Tanner: 84 passningar, xT 1.2TannerJack Moylan: 77 passningar, xT 0.69MoylanCian Ty Ashford: 75 passningar, xT -0.04Ashford
    Stoke City
    Ben Wilmot: 194 passningar, xT 0.23WilmotEthan Stuart William Galbraith: 158 passningar, xT 0.25GalbraithEric Junior Bocat: 143 passningar, xT 0.38BocatEl Hadji Djibril Soumaré: 134 passningar, xT 0.14SoumaréLuke Graham: 97 passningar, xT 0.11GrahamViktor Johansson: 95 passningar, xT 0.11JohanssonBenjamin Anthony Johnson: 91 passningar, xT 0.44JohnsonBosun Lawal: 78 passningar, xT 0.08LawalMaksym Taloverov: 77 passningar, xT 0.13TaloverovBenjamin Sorba William Thomas: 52 passningar, xT 1.22ThomasJun Ho Bae: 48 passningar, xT 0.48Bae

    The teams in numbers

    PerformanceCardiff CityStoke City
    Points36
    xPoints4.95.2
    xG per match1.60.94
    xGA per match1.61.5
    xG within 8s of winning the ball0.130.09
    xGA within 8s of losing the ball0.360.2
    Playing styleCardiff CityStoke City
    Build-up efficiency0.340.29
    Field tilt0.660.39
    xT per match1.21.1
    xTA per match0.810.67
    Won balls, offensive half2125
    Pressing intensity0.240.23
    Pressing efficiency0.340.3
    Pressing efficiency, offensive half0.270.27
    Entries into the box per match1310
    Entries into the box against1213
    Pass completion %0.790.73
    Pass completion % under pressure0.750.69
    Passes per match450275
    Passes against per match205361
    Switches of play per match4619.6
    Long balls per match4623
    Set piecesCardiff CityStoke City
    xG from free kicks0.010.17
    Corners per match7.93
    Corners against per match5.14.8
    xG per corner0.050.01
    xGA per corner against0.030.03
    First touch, offensive corners %0.150.33
    First touch, defensive corners %0.690.54
    OtherCardiff CityStoke City
    Throw-in control0.820.77
    The goalkeepersNathan Wallace Newman Trott (Cardiff City)Viktor Johansson (Stoke City)
    Saves1916
    Save %68%64%
    xG prevented43%24%
    Claims0 (0%)0 (0%)

    Frequently asked questions

    Who wins Cardiff City vs Stoke City according to our model?

    The model gives Cardiff City a 64% win probability. Full 1X2 picture: Cardiff City 64%, draw 20%, Stoke City 16%.

    What is the most likely scoreline?

    The model's most likely final score is 2-0 at 10% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 59% and under at 41%.

    Will both teams score?

    The probability of both teams scoring is 54% 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.