Scottish PremiershipEaster Road, Edinburgh17°8,3 mm28 km/h

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    HibernianHibernianPossession & high press
    vs
    HeartsHeartsBalanced & physical
    The model's lean: 2 · Hearts (40%)

    HibernianHearts · Scottish Premiership

    1 · Hibernian 31%X 30%40% Hearts · 2

    Analysis: HibernianHearts

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

    TEXT:

    A 40% win probability for Hearts suggests they hold a slight edge over Hibernian, especially noticeable when you consider the robust streak of scoring in 11 consecutive league matches. The model's lean toward the visitors is clear, supported by a series of metrics that paint a compelling picture for a narrow away victory.

    Despite the hosts' appealing xG metrics—Hibernian's 2.2 xG per match compared to Hearts' 1.7—their defensive frailties are apparent. The hosts concede more frequently, with an xGA of 1.5 against Hearts' 1.4. This defensive vulnerability could be pivotal, especially given the visitors' scoring consistency.

    Moreover, both sides exhibit contrasting playing styles; Hibernian's possession and high press encounter Hearts' balanced and physical approach. This tactical clash could lead to a tight battle. With combined expected goals of 2.64, over 2.5 goals at 49% and both teams to score at 53%, the match doesn't clearly point to a low-scoring affair despite the modest rainfall forecast of 2.2 mm.

    The head-to-head record since 2023 suggests parity, with each team winning three matches out of seven. Yet, the sample is small and less significant compared to current form and expected goals. The most likely scorelines hint at a close encounter: 1-1 at 12% or a 0-1 victory for Hearts at 10%.

    For bettors seeking value, the odds for an away win at 2.75 with Betsafe, Betsson, and Nordicbet present a promising edge of 9% based on the model's assessment. This makes backing Hearts a strategic play, one that's underpinned by both form and probability.

    HibernianHibernian
    Form WLLWW
    League ranking xG #2xGA #6xT #9xP/match #2Points #5
    Key players
    • Jamie Terence McGrathLWxG 0.30 · xT -0.02
    • Callum WrightLWxG 0.32 · xT 0.06
    • Martin Callie BoyleRWxG 0.92 · xT 0.06
    HeartsHearts
    Form WLLWW
    League ranking xG #6xGA #5xT #5xP/match #4Points #3
    Key players
    • Amadou Ba-SyFxG 0.19 · xT 0.20
    • Calvin MillerLWxG 0.44 · xT 0.02
    • Joshua McPakeLWBxG 0.07 · xT 0.27

    Match prediction: HibernianHearts

    Predicted score matrix

    Hearts
    Hibernian
    0
    1
    2
    3
    4+
    0
    0–07.4%
    0–110.5%
    0–28.2%
    0–34.2%
    0–4+2.2%
    1
    1–07.6%
    1–112.5%
    1–29.2%
    1–34.7%
    1–4+2.5%
    2
    2–04.5%
    2–16.8%
    2–25.2%
    2–32.6%
    2–4+1.4%
    3
    3–01.7%
    3–12.5%
    3–21.9%
    3–31.0%
    3–4+0.5%
    4+
    4+–00.6%
    4+–10.9%
    4+–20.7%
    4+–30.4%
    4+–4+0.2%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-112%
    2. 2.0-110%
    3. 3.1-29%
    4. 4.0-28%
    5. 5.1-08%
    Expected goals
    1,121,52
    Both teams to score
    53%

    Over/under goals

    Expected goals: 2,6
    Under 2,551%
    @2.00EV+1%
    Over 2,549%
    @1.86

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Double chance Hearts or draw (X2)72%
    • Under 3.5 goals73%

    Combined probability

    52%

    Fair odds

    1.92

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

    02 · 3 legs

    Balanced

    • Double chance Hearts or draw (X2)72%
    • Under 2.5 goals51%
    • Lawrence Shankland to score20%

    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 score53%
    • Over 2.5 goals49%
    • Lawrence Shankland to score20%
    • Stuart John Findlay 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 · Hearts40% probability@2.73PinnacleEV+8%reference odds
    • 2 · Hearts40% probability@2.72BetsafeEV+8%reference odds
    • 2 · Hearts40% probability@2.72BetssonEV+8%reference odds
    Bookmaker1 · HibernianX2 · Hearts
    Bet3652.50
    EV+ 4%
    3.50
    EV+ 3%
    2.60
    Betsafe2.453.30
    EV+ 8%
    2.72
    Betsson2.453.30
    EV+ 8%
    2.72
    Nordicbet2.453.30
    EV+ 8%
    2.72
    Pinnacle2.56
    EV+ 1%
    3.39
    EV+ 8%
    2.73

    Odds updated 1 Sept, 06:35

    Odds movement

    1+2 %
    40 %35 %

    2.512.56

    X0 %
    31 %26 %

    3.383.39

    2-2 %
    37 %32 %

    2.782.73

    Over 2,50 %
    54 %49 %

    1.861.86

    Pinnacle · 2 recorded price levels · 30/08/2026 → 31/08/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    7 matches
    Hibernian 3Draw 1Hearts 3
    Goals: 99 (⌀ 2,6)

    Head-to-head based on Scottish Premiership data since 2023.

    Key facts

    • Hearts have scored in 11 consecutive league matches.
    xG & xGA per match — 3-game rolling average

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

    Hibernian
    Hearts
    When goals are scored and conceded 2026
    Hibernian (54)
    Hearts (73)
    Pass networks

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

    Hibernian
    Jason John Kerr: 167 passningar, xT 0.31KerrJordan Obita: 143 passningar, xT 0.4ObitaGrant Hanley: 93 passningar, xT 0.09HanleyJosh Mulligan: 90 passningar, xT 0.12MulliganFelix Passlack: 82 passningar, xT 0.29PasslackWarren Ohora: 67 passningar, xT 0.24OhoraRaphael Sallinger: 66 passningar, xT 0.18SallingerJacob Patrick John Devaney: 64 passningar, xT -0.03DevaneyMiguel Chaiwa: 58 passningar, xT 0ChaiwaJamie Terence McGrath: 43 passningar, xT -0.02McGrathCallum Wright: 34 passningar, xT 0.07Wright
    Hearts
    Oisin Mcentee: 126 passningar, xT 0.19McenteeJordi Altena: 102 passningar, xT 0.06AltenaBeau Reus: 98 passningar, xT 0.02ReusBlair Thomas Spittal: 79 passningar, xT 0.55SpittalSabah Kerjota: 64 passningar, xT 0.17KerjotaStuart Findlay: 62 passningar, xT 0.04FindlayClaudio Rafael Soares Braga: 55 passningar, xT 0BragaCalvin Miller: 55 passningar, xT 0.03MillerLaurent Mendy: 50 passningar, xT -0.02MendyTómas Bent Magnússon: 43 passningar, xT 0.39MagnússonChristian Dahle Borchgrevink: 42 passningar, xT 0.08Borchgrevink
    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.

    Hibernian
    Jason John Kerr: 167 passningar, xT 0.31KerrJordan Obita: 143 passningar, xT 0.4ObitaGrant Hanley: 93 passningar, xT 0.09HanleyJosh Mulligan: 90 passningar, xT 0.12MulliganFelix Passlack: 82 passningar, xT 0.29PasslackWarren Ohora: 67 passningar, xT 0.24OhoraRaphael Sallinger: 66 passningar, xT 0.18SallingerJacob Patrick John Devaney: 64 passningar, xT -0.03DevaneyMiguel Chaiwa: 58 passningar, xT 0ChaiwaJamie Terence McGrath: 43 passningar, xT -0.02McGrathCallum Wright: 34 passningar, xT 0.07Wright
    Hearts
    Oisin Mcentee: 126 passningar, xT 0.19McenteeJordi Altena: 102 passningar, xT 0.06AltenaBeau Reus: 98 passningar, xT 0.02ReusBlair Thomas Spittal: 79 passningar, xT 0.55SpittalSabah Kerjota: 64 passningar, xT 0.17KerjotaStuart Findlay: 62 passningar, xT 0.04FindlayClaudio Rafael Soares Braga: 55 passningar, xT 0BragaCalvin Miller: 55 passningar, xT 0.03MillerLaurent Mendy: 50 passningar, xT -0.02MendyTómas Bent Magnússon: 43 passningar, xT 0.39MagnússonChristian Dahle Borchgrevink: 42 passningar, xT 0.08Borchgrevink

    The teams in numbers

    PerformanceHibernianHearts
    Points66
    xPoints5.55.4
    xG per match2.21.7
    xGA per match1.51.4
    xG within 8s of winning the ball0.620.19
    xGA within 8s of losing the ball0.180.12
    Playing styleHibernianHearts
    Build-up efficiency0.330.33
    Field tilt0.470.53
    xT per match0.881
    xTA per match0.960.83
    Won balls, offensive half2524
    Pressing intensity0.270.21
    Pressing efficiency0.260.31
    Pressing efficiency, offensive half0.230.27
    Entries into the box per match1413
    Entries into the box against1410
    Pass completion %0.770.72
    Pass completion % under pressure0.760.63
    Passes per match359307
    Passes against per match452372
    Switches of play per match31.133.1
    Long balls per match3937
    Set piecesHibernianHearts
    xG from free kicks0.020
    Corners per match5.76.9
    Corners against per match43.3
    xG per corner0.010.04
    xGA per corner against0.010.04
    First touch, offensive corners %0.380.43
    First touch, defensive corners %0.580.5
    OtherHibernianHearts
    Throw-in control0.830.78
    The goalkeepersRaphael Sallinger (Hibernian)Beau Reus (Hearts)
    Saves134
    Save %81%57%
    xG prevented45%13%
    Claims0 (0%)0 (0%)

    Frequently asked questions

    Who wins Hibernian vs Hearts according to our model?

    The model gives Hearts a 40% win probability. Full 1X2 picture: Hibernian 31%, draw 30%, Hearts 40%.

    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 49% and under at 51%.

    Will both teams score?

    The probability of both teams scoring is 53% 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.