Croatian HNL15°27 km/h

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    Hajduk SplitHajduk SplitPossession & high press
    vs
    GoricaGoricaLow block & direct
    The model's lean: 1 · Hajduk Split (79%)

    Hajduk Split vs Gorica · Croatian HNL

    1 · Hajduk Split 79%X 14%6% Gorica · 2

    Prediction summary

    BetBuilders AI model prediction for Hajduk Split vs Gorica (Croatian HNL, Saturday, 31 October 2026): Hajduk Split win 79%, draw 14%, Gorica win 6%. Expected goals (xG): Hajduk Split 2.51, Gorica 0.66. Most likely score: 2-0 (13%). Over 2.5 goals 61%, both teams to score 45%. Double chance: Hajduk Split or draw 94%, Gorica or draw 21%. Prediction updated Friday, 23 October 2026.

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    Analysis: Hajduk Split – Gorica

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

    79% is the number that matters: Hajduk Split are clear model favourites against Gorica, with a 14% draw chance and just 6% for the visitors. The likeliest score is 2-0 at 13%, ahead of 3-0 at 11% and 1-0 at 10%. That points plainly to a home win built on control rather than drama.

    The hosts’ 2.51 expected goals dwarf Gorica’s 0.66. Hajduk’s 1.6 xG per match and 0.72 xGA also stack up cleanly against the visitors’ 0.91 and 1.6. Possession and a high press meet a low block and direct football; the likely pattern is Hajduk pinning them back. The points gap is 22 to 7, while xPoints read 16.5 to 11.7.

    Since 2023, Hajduk hold a 6W, 1D, 2L edge in nine head-to-head meetings, and they win 69% of 42 home matches. Over 2.5 goals has a 61% model lean, despite both teams scoring sitting at only 45%. The stable play is Hajduk to win; the sharper totals angle is over 2.5, with 3-0 live behind the 2-0 favourite.

    Hajduk SplitHajduk Split
    Form WWLWW
    League ranking xG #3xGA #1xT #3xP/match #3Points #1
    Key players
    • Rokas PukštasCDMxG 0.34 · xT 0.24
    • Šimun HrgovićLWBxG 0.05 · xT 0.15
    • Adrion PajazitiCAMxG 0.11 · xT 0.09
    GoricaGorica
    Form DWLDD
    League ranking xG #9xGA #7xT #8xP/match #9Points #10
    Key players
    • Gonçalo Faria CostaLWBxG 0.04 · xT 0.19
    • Jakov FilipovićCBxG 0.02 · xT 0.06
    • Luka VrzićRWxG 0.12 · xT 0.16

    Match prediction: Hajduk Split – Gorica

    Predicted score matrix

    Gorica →
    Hajduk Split →
    0
    1
    2
    3
    4+
    0
    0–04.4%
    0–12.6%
    0–20.9%
    0–30.2%
    0–4+0.0%
    1
    1–010.3%
    1–17.2%
    1–22.3%
    1–30.5%
    1–4+0.1%
    2
    2–013.2%
    2–18.7%
    2–22.9%
    2–30.6%
    2–4+0.1%
    3
    3–011.1%
    3–17.3%
    3–22.4%
    3–30.5%
    3–4+0.1%
    4+
    4+–012.6%
    4+–18.3%
    4+–22.8%
    4+–30.6%
    4+–4+0.1%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.2-013%
    2. 2.3-011%
    3. 3.1-010%
    4. 4.2-19%
    5. 5.3-17%
    Expected goals
    2,51–0,66
    Both teams to score
    45%

    Over/under goals

    Expected goals: 3,2
    Under 2,539%
    @2.12
    Over 2,561%
    @1.62

    Ready-made bet suggestions

    More combos & build your own →

    01 · 2 legs

    Safe

    • Hajduk Split to win79%
    • Over 1.5 goals83%

    Combined probability

    67%

    Fair odds

    1.49

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

    02 · 3 legs

    Balanced

    • Hajduk Split to win79%
    • Over 2.5 goals61%
    • Dalisson de Almeida Leite to score37%

    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 score45%
    • Over 2.5 goals61%
    • Dalisson de Almeida Leite to score37%
    • Tom Jacques Daniel Lacoux to be booked23%

    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 · Hajduk Split79% probability@1.31BetsafeEV+4%reference odds
    • 1 · Hajduk Split79% probability@1.31NordicbetEV+4%reference odds
    • Over 3.539% probability@2.58BetsafeEV+1%reference odds
    Bookmaker1 · Hajduk SplitX2 · Gorica
    Betsafe
    EV+ 4%
    1.31    		4.808.00
    Nordicbet
    EV+ 4%
    1.31    		4.808.00

    Odds updated 26 Oct, 19:36

    Odds movement

    1-1 %
    72 %67 %

    1.33 → 1.31

    X0 %
    22 %17 %

    4.80 → 4.80

    2+3 %
    14 %9 %

    7.80 → 8.00

    Over 2,50 %
    59 %54 %

    1.62 → 1.62

    Nordicbet · 2 recorded price levels · 26/10/2026 → 26/10/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    9 matches
    Hajduk Split 6Draw 1Gorica 2
    Goals: 15–7 (⌀ 2,4)

    Head-to-head based on Croatian HNL data since 2023.

    Key facts

    • Hajduk Split dominate this fixture historically: 6 wins to 2 in 9 meetings.
    • Hajduk Split win 69% of their home matches all-time (42 played).
    xG & xGA per match — 3-game rolling average

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

    Hajduk Split
    Gorica
    When goals are scored and conceded — 2026
    Hajduk Split (19–9)
    Gorica (7–15)
    Pass networks

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

    Hajduk Split
    Dario Marešić: 380 passningar, xT 0.46MarešićMathieu Acapandié: 281 passningar, xT 0.19AcapandiéRon Raçi: 275 passningar, xT 0.26RaçiKhalil Fayad: 204 passningar, xT 0.53FayadŠimun Hrgović: 172 passningar, xT 0.34HrgovićAlberto del Moral Saelices: 153 passningar, xT 0.06SaelicesDalisson de Almeida Leite: 130 passningar, xT 0.36LeiteAdrion Pajaziti: 126 passningar, xT 0.13PajazitiToni Silić: 118 passningar, xT 0.07SilićDennis Hadžikadunić: 111 passningar, xT 0.15HadžikadunićAbdoulie Sanyang: 63 passningar, xT 0.42Sanyang
    Gorica
    Jakov Filipović: 271 passningar, xT 0.45FilipovićDušan Stevanović: 218 passningar, xT 0.27StevanovićFilip Braut: 214 passningar, xT 0.69BrautTom Jacques Daniel Lacoux: 166 passningar, xT 0.15LacouxRenato Josipović: 146 passningar, xT 0.12JosipovićJuraj Frigan: 145 passningar, xT 0.09FriganGonçalo Faria Costa: 119 passningar, xT 0.73CostaDomagoj Pavičić: 102 passningar, xT 0.62PavičićIvan Cvijanović: 54 passningar, xT 0.66CvijanovićBruno Bogojević: 50 passningar, xT 0.13BogojevićJakov Pranjić: 42 passningar, xT 0.06Pranjić
    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.

    Hajduk Split
    Dario Marešić: 380 passningar, xT 0.46MarešićMathieu Acapandié: 281 passningar, xT 0.19AcapandiéRon Raçi: 275 passningar, xT 0.26RaçiKhalil Fayad: 204 passningar, xT 0.53FayadŠimun Hrgović: 172 passningar, xT 0.34HrgovićAlberto del Moral Saelices: 153 passningar, xT 0.06SaelicesDalisson de Almeida Leite: 130 passningar, xT 0.36LeiteAdrion Pajaziti: 126 passningar, xT 0.13PajazitiToni Silić: 118 passningar, xT 0.07SilićDennis Hadžikadunić: 111 passningar, xT 0.15HadžikadunićAbdoulie Sanyang: 63 passningar, xT 0.42Sanyang
    Gorica
    Jakov Filipović: 271 passningar, xT 0.45FilipovićDušan Stevanović: 218 passningar, xT 0.27StevanovićFilip Braut: 214 passningar, xT 0.69BrautTom Jacques Daniel Lacoux: 166 passningar, xT 0.15LacouxRenato Josipović: 146 passningar, xT 0.12JosipovićJuraj Frigan: 145 passningar, xT 0.09FriganGonçalo Faria Costa: 119 passningar, xT 0.73CostaDomagoj Pavičić: 102 passningar, xT 0.62PavičićIvan Cvijanović: 54 passningar, xT 0.66CvijanovićBruno Bogojević: 50 passningar, xT 0.13BogojevićJakov Pranjić: 42 passningar, xT 0.06Pranjić

    The teams in numbers

    PerformanceHajduk SplitGorica
    Points227
    xPoints16.511.7
    xG per match1.60.91
    xGA per match0.721.6
    xG within 8s of winning the ball0.220.14
    xGA within 8s of losing the ball0.170.19
    Playing styleHajduk SplitGorica
    Build-up efficiency0.30.28
    Field tilt0.690.35
    xT per match1.10.88
    xTA per match0.561.3
    Won balls, offensive half2725
    Pressing intensity0.230.24
    Pressing efficiency0.360.3
    Pressing efficiency, offensive half0.30.24
    Entries into the box per match1211
    Entries into the box against814
    Pass completion %0.80.72
    Pass completion % under pressure0.750.66
    Passes per match427308
    Passes against per match248379
    Switches of play per match26.625.4
    Long balls per match3337
    Set piecesHajduk SplitGorica
    xG from free kicks0.010.03
    Corners per match4.34
    Corners against per match2.56
    xG per corner0.020.03
    xGA per corner against0.010.04
    First touch, offensive corners %0.430.36
    First touch, defensive corners %0.640.47
    OtherHajduk SplitGorica
    Throw-in control0.720.69
    The goalkeepersToni Silić (Hajduk Split)Renato Josipović (Gorica)
    Saves1432
    Save %61%84%
    xG prevented28%53%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Hajduk Split
    Fixtures, form & tips
    Gorica
    Fixtures, form & tips

    Frequently asked questions

    Who wins Hajduk Split vs Gorica according to our model?

    The model gives Hajduk Split a 79% win probability. Full 1X2 picture: Hajduk Split 79%, draw 14%, Gorica 6%.

    What is the most likely scoreline?

    The model's most likely final score is 2-0 at 13% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 61% and under at 39%.

    Will both teams score?

    The probability of both teams scoring is 45% according to the model.

    How many goals are expected in Hajduk Split vs Gorica?

    The model expects 2.51 goals (xG) for Hajduk Split and 0.66 for Gorica, 3.17 in total.

    What does the model say about double chance?

    Hajduk Split or draw (1X) 94%, Gorica or draw (X2) 21% and no draw (12) 86%.

    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.