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    PAOKPAOK
    vs
    BrannBrann
    The model's lean: 1 · PAOK (60%)

    PAOKBrann · Conference League

    1 · PAOK 60%X 22%18% Brann · 2

    Analysis: PAOKBrann

    Sofia Andersson · · The model's read on the match · How the predictions work

    PAOK Thessaloniki enters this Conference League clash with a solid 60% probability of victory, a testament to their form and the formidable atmosphere at their home ground. The expected goals (xG) suggest a significant edge too, pegged at 1.90 for PAOK against Brann's 1.03. This gap sets the stage for what should be a controlled yet competitive affair, with PAOK likely dictating the pace.

    Brann, with only an 18% chance of winning, faces an uphill battle. While their overall season form shows resilience, the numbers suggest they may struggle to break down a well-drilled PAOK side. It’s also noteworthy that the most likely scorelines—1-1 (11%), 2-1 (10%), and 1-0 (10%)—reflect the narrow margins by which PAOK has been edging matches, suggesting competence in grinding out results rather than blowing opponents away.

    The model leans towards a PAOK victory, emphasizing a subtle edge in attacking output and defensive solidity. Despite the 56% chance of over 2.5 goals, the projected xG and potential for a tightly-knit contest hint that this might not be the goal-fest some might expect. Weather, if relevant, isn't a factor dampening this prediction, allowing for pure form and tactics to dictate the tempo.

    Brann's defensive vulnerabilities, especially away from home, might be exposed here, yet their ability to find the net remains—55% on both teams to score aligns with a likely PAOK win but not without a scare. Considering all these factors, a 2-1 scoreline in favor of PAOK feels like the sweet spot, balancing PAOK's home prowess against Brann's potential to snag at least one goal.

    For bettors, the sharpest play appears to be on the side of PAOK Thessaloniki outright, with their 60% win probability reflecting solid value. For those who prefer goals, leaning slightly towards over 2.5 goals at 56% could offer a compelling angle, especially if Brann can muster a surprise goal.

    PAOKPAOK
    Form WLWLL
    Key players
    • Giannis KonstanteliasFxG 0.35 · xT 0.20
    • Theocharis TsingarasCDMxG 0.05 · xT 0.04
    • Andrija ŽivkovićRWxG 0.20 · xT 0.29
    BrannBrann
    Form LWDD
    Key players
    • Felix MyhreCAMxG 0.05 · xT 0.17
    • Bård FinneFxG 0.24 · xT 0.07
    • Sivert NilsenCDMxG 0.00 · xT 0.11

    Match prediction: PAOKBrann

    Predicted score matrix

    Brann
    PAOK
    0
    1
    2
    3
    4+
    0
    0–05.6%
    0–15.2%
    0–22.8%
    0–31.0%
    0–4+0.3%
    1
    1–09.8%
    1–110.7%
    1–25.4%
    1–31.8%
    1–4+0.6%
    2
    2–09.6%
    2–19.9%
    2–25.1%
    2–31.8%
    2–4+0.6%
    3
    3–06.1%
    3–16.3%
    3–23.2%
    3–31.1%
    3–4+0.4%
    4+
    4+–04.5%
    4+–14.6%
    4+–22.4%
    4+–30.8%
    4+–4+0.3%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-111%
    2. 2.2-110%
    3. 3.1-010%
    4. 4.2-010%
    5. 5.3-16%
    Expected goals
    1,901,03
    Both teams to score
    55%

    Over/under goals

    Expected goals: 2,9
    Under 2,544%
    @2.25
    Over 2,556%
    @1.78

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • PAOK to win60%
    • Over 1.5 goals79%

    Combined probability

    48%

    Fair odds

    2.10

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

    02 · 3 legs

    Balanced

    • PAOK to win60%
    • Over 2.5 goals56%
    • Brandon Thomas Llamas to score26%

    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 score55%
    • Over 2.5 goals56%
    • Niklas Fernando Nygård Castro to score29%
    • Soualiho Meïté to be booked24%

    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 · PAOK60% probability@1.70BetsafeEV+2%reference odds
    • 1 · PAOK60% probability@1.70BetssonEV+2%reference odds
    • 1 · PAOK60% probability@1.70NordicbetEV+2%reference odds
    Bookmaker1 · PAOKX2 · Brann
    Betsafe
    EV+ 2%
    1.70
    3.454.65
    Betsson
    EV+ 2%
    1.70
    3.454.65
    Nordicbet
    EV+ 2%
    1.70
    3.454.65
    Paddy Power1.534.005.00

    Odds updated 18 Aug, 16:35

    Odds movement

    Market signal

    The market has moved clearly towards under 2.5 goals since 14 August — the odds have shortened from 2.22 to 1.92 (−14%).

    1+8 %
    61 %51 %

    1.581.70

    X-10 %
    30 %20 %

    3.853.45

    2-5 %
    24 %14 %

    4.904.65

    Over 2,5+13 %
    60 %50 %

    1.581.78

    Betsson · 34 recorded price levels · 14/08/2026 → 18/08/2026 · fixed scale 10 percentage points

    Statistics

    When goals are scored and conceded 2023
    PAOK (3418)
    Brann (87)
    Pass networks

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

    PAOK
    Tomasz Kędziora: 249 passningar, xT 0.46KędzioraSoualiho Meïté: 218 passningar, xT 0.48MeïtéTaison: 207 passningar, xT 1.19TaisonAbdul Baba: 196 passningar, xT 0.59BabaKonstantinos Koulierakis: 192 passningar, xT 0.63KoulierakisJonny Otto: 139 passningar, xT 0.24OttoMagomed Ozdoev: 122 passningar, xT -0.13OzdoevDominik Kotarski: 119 passningar, xT 0.18KotarskiAndrija Živković: 115 passningar, xT 0.44ŽivkovićGiannis Michailidis: 97 passningar, xT 0.07MichailidisVieirinha: 86 passningar, xT 0.48Vieirinha
    Brann
    Sivert Nilsen: 202 passningar, xT 0.38NilsenRuben Kristiansen: 181 passningar, xT 0.01KristiansenFredrik Knudsen: 154 passningar, xT 0.51KnudsenThore Pedersen: 135 passningar, xT 0.34PedersenSvenn Crone: 127 passningar, xT 0.45CroneMathias Dyngeland: 125 passningar, xT 0.57DyngelandFelix Myhre: 125 passningar, xT 0.37MyhreFrederik Børsting: 77 passningar, xT 0.16BørstingNiklas Nygård Castro: 55 passningar, xT 0.57CastroSander Kartum: 51 passningar, xT 0.25KartumMoonga Simba: 48 passningar, xT 0.03Simba
    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.

    PAOK
    Tomasz Kędziora: 249 passningar, xT 0.46KędzioraSoualiho Meïté: 218 passningar, xT 0.48MeïtéTaison: 207 passningar, xT 1.19TaisonAbdul Baba: 196 passningar, xT 0.59BabaKonstantinos Koulierakis: 192 passningar, xT 0.63KoulierakisJonny Otto: 139 passningar, xT 0.24OttoMagomed Ozdoev: 122 passningar, xT -0.13OzdoevDominik Kotarski: 119 passningar, xT 0.18KotarskiAndrija Živković: 115 passningar, xT 0.44ŽivkovićGiannis Michailidis: 97 passningar, xT 0.07MichailidisVieirinha: 86 passningar, xT 0.48Vieirinha
    Brann
    Sivert Nilsen: 202 passningar, xT 0.38NilsenRuben Kristiansen: 181 passningar, xT 0.01KristiansenFredrik Knudsen: 154 passningar, xT 0.51KnudsenThore Pedersen: 135 passningar, xT 0.34PedersenSvenn Crone: 127 passningar, xT 0.45CroneMathias Dyngeland: 125 passningar, xT 0.57DyngelandFelix Myhre: 125 passningar, xT 0.37MyhreFrederik Børsting: 77 passningar, xT 0.16BørstingNiklas Nygård Castro: 55 passningar, xT 0.57CastroSander Kartum: 51 passningar, xT 0.25KartumMoonga Simba: 48 passningar, xT 0.03Simba
    The goalkeepersDominik Kotarski (PAOK)Mathias Dyngeland (Brann)
    Saves4620
    Save %72%74%
    xG prevented54%58%
    Claims0 (0%)0 (0%)

    Frequently asked questions

    Who wins PAOK vs Brann according to our model?

    The model gives PAOK a 60% win probability. Full 1X2 picture: PAOK 60%, draw 22%, Brann 18%.

    What is the most likely scoreline?

    The model's most likely final score is 1-1 at 11% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 56% and under at 44%.

    Will both teams score?

    The probability of both teams scoring is 55% 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.

    More matches in the league

    Predictions come from PlaymakerAI's match model and reflect the model's assessment — not betting advice. Gamble responsibly.