Norwegian Eliteserien17°1,5 mm19 km/h

    Läs på svenska
    SandefjordSandefjordPossession control
    00
    BrannBrannPossession control
    The model's lean: 2 · Brann (49%)

    SandefjordBrann · Norwegian Eliteserien

    1 · Sandefjord 27%X 23%49% Brann · 2

    Analysis: SandefjordBrann

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

    TEXT: A clash of styles is unlikely when two possession-oriented teams, Sandefjord and Brann, meet. Both sides favor control and methodical buildup, setting the stage for a tactical battle rather than an open spectacle. Brann, with the upper hand historically in this fixture, have won three of their last five encounters against Sandefjord, a stat that weighs lightly given the small sample size but cannot be ignored.

    The numbers paint a clear picture: Brann is favored with a 49% likelihood of victory, compared to Sandefjord’s 27%, and the probabilities suggest a tilt toward the visitors. The expected goals forecast of 1.94 for Brann versus 1.32 for Sandefjord underlines the visitors' attacking edge. This matches with Brann’s streak of scoring in 13 consecutive league matches, suggesting they have the firepower to breach the hosts' defense.

    With a 63% probability for over 2.5 goals and both teams to score, the model leans towards a lively affair in terms of scoring despite the possession-heavy styles. This aligns with the most likely scorelines of 1-1 and 1-2, both at 10%. Yet, the visitors’ defensive solidity, reflected in their xGA of 1.6 compared to Sandefjord’s 1.8, might just tip the balance, forecasting a likely 1-2 win for Brann.

    For those seeking value, Brann offers a promising opportunity. Nordicbet provides odds of 2.2 for an away win, translating to an 8% edge according to the model. Betsafe and Betsson also offer competitive odds at 2.18 and 2.15, respectively. These figures suggest a compelling case for backing Brann, with value clearly on their side.

    SandefjordSandefjord
    Form LLLLW
    League ranking xG #13xGA #13xT #14xP/match #14Points #13
    Key players
    • Sebastian Holm MathisenFxG 0.40 · xT -0.02
    • Evangelos PatoulidisRWxG 0.19 · xT 0.19
    • Jakob DunsbyLWxG 0.23 · xT 0.20
    BrannBrann
    Form WWLWW
    League ranking xG #3xGA #9xT #2xP/match #10Points #6
    Key players
    • Noah Jean HolmFxG 0.48 · xT 0.05
    • Joachim SoltvedtLWBxG 0.21 · xT 0.36
    • Denzel De RoeveRBxG 0.10 · xT 0.30
    Final score
    00
    The model missed the outcome
    Predicted probabilities: Sandefjord 27% · Draw 23% · Brann 49%

    How the bookmaker bet builders went

    The verdict on the pre-built bet builders for this match, priced against the model’s score matrix before kickoff. Graded on the 90-minute result.

    Matchresultat - BrannBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 4,96fair 5,16-4 %
    Miss
    Matchresultat - SandefjordBåda lagen gör mål - JaTotalt antal mål - Över 3.5
    odds 7,92fair 11,30-30 %
    Miss

    Match prediction: SandefjordBrann

    Predicted score matrix

    Brann
    Sandefjord
    0
    1
    2
    3
    4+
    0
    0–04.1%
    0–17.2%
    0–27.2%
    0–34.7%
    0–4+3.6%
    1
    1–04.8%
    1–110.1%
    1–29.5%
    1–36.2%
    1–4+4.7%
    2
    2–03.3%
    2–16.5%
    2–26.3%
    2–34.1%
    2–4+3.1%
    3
    3–01.5%
    3–12.8%
    3–22.8%
    3–31.8%
    3–4+1.4%
    4+
    4+–00.6%
    4+–11.2%
    4+–21.2%
    4+–30.8%
    4+–4+0.6%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-110%
    2. 2.1-210%
    3. 3.0-27%
    4. 4.0-17%
    5. 5.2-16%
    Expected goals
    1,321,94
    Both teams to score
    63%

    Over/under goals

    Expected goals: 3,3
    Under 2,537%
    @2.55
    Over 2,563%
    @1.55

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Brann to win49%
    • Over 1.5 goals84%

    Combined probability

    44%

    Fair odds

    2.25

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

    02 · 3 legs

    Balanced

    • Brann to win49%
    • Over 2.5 goals63%
    • Noah Emmanuel Jean Holm to score28%

    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 score63%
    • Over 2.5 goals63%
    • Noah Emmanuel Jean Holm to score28%
    • Sander Risan Mørk 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+).

    • 2 · Brann49% probability@2.20NordicbetEV+8%reference odds
    • 2 · Brann49% probability@2.18BetsafeEV+7%reference odds
    • 2 · Brann49% probability@2.15Bet365EV+6%reference odds
    Bookmaker1 · SandefjordX2 · Brann
    Bet3652.903.70
    EV+ 6%
    2.15
    Betsafe2.953.85
    EV+ 7%
    2.18
    Betsson3.253.70
    EV+ 6%
    2.15
    Nordicbet2.983.90
    EV+ 8%
    2.20
    Pinnacle3.303.84
    EV+ 5%
    2.13

    Odds updated 30 Aug, 05:14

    Odds movement

    1+5 %
    33 %28 %

    3.143.30

    X+3 %
    28 %23 %

    3.743.84

    2-1 %
    47 %42 %

    2.162.13

    Pinnacle · 7 recorded price levels · 21/08/2026 → 30/08/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    5 matches
    Sandefjord 1Draw 1Brann 3
    Goals: 48 (⌀ 2,4)

    Head-to-head based on Eliteserien data since 2021.

    Key facts

    • Brann dominate this fixture historically: 3 wins to 1 in 5 meetings.
    • Brann have scored in 13 consecutive league matches.
    xG & xGA per match — 3-game rolling average

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

    Sandefjord
    Brann
    When goals are scored and conceded 2026
    Sandefjord (1523)
    Brann (3627)
    Pass networks

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

    Sandefjord
    Xander Lambrix: 301 passningar, xT 0.32LambrixSander Risan Mork: 284 passningar, xT 0.45MorkVetle Walle Egeli: 219 passningar, xT 0.35EgeliFredrik Carson Pedersen: 200 passningar, xT 0.2PedersenRasmus Holten: 191 passningar, xT 0.44HoltenElias Hadaya: 176 passningar, xT 0.09HadayaEdvard Sundbø Pettersen: 123 passningar, xT 0.28PettersenEvangelos Patoulidis: 90 passningar, xT 0.36PatoulidisStian Kristiansen: 68 passningar, xT 0.05KristiansenTobias Borchgrevink Børkeeiet: 54 passningar, xT 0.06BørkeeietJakob Dunsby: 51 passningar, xT 0.69Dunsby
    Brann
    Joachim Soltvedt: 379 passningar, xT 2.52SoltvedtThore Pedersen: 259 passningar, xT 0.39PedersenVetle Dragsnes: 231 passningar, xT 0.32DragsnesFredrik Pallesen Knudsen: 217 passningar, xT 0.22KnudsenDenzel De Roeve: 200 passningar, xT 1.48RoeveNiklas Castro: 181 passningar, xT 2.34CastroJakob Lungi Sørensen: 179 passningar, xT 0.29SørensenMathias Dyngeland: 165 passningar, xT 0.14DyngelandFelix Horn Myhre: 143 passningar, xT 0.22MyhreNiklas Wassberg: 132 passningar, xT 0.02WassbergKristian Eriksen: 96 passningar, xT 0.19Eriksen
    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.

    Sandefjord
    Xander Lambrix: 301 passningar, xT 0.32LambrixSander Risan Mork: 284 passningar, xT 0.45MorkVetle Walle Egeli: 219 passningar, xT 0.35EgeliFredrik Carson Pedersen: 200 passningar, xT 0.2PedersenRasmus Holten: 191 passningar, xT 0.44HoltenElias Hadaya: 176 passningar, xT 0.09HadayaEdvard Sundbø Pettersen: 123 passningar, xT 0.28PettersenEvangelos Patoulidis: 90 passningar, xT 0.36PatoulidisStian Kristiansen: 68 passningar, xT 0.05KristiansenTobias Borchgrevink Børkeeiet: 54 passningar, xT 0.06BørkeeietJakob Dunsby: 51 passningar, xT 0.69Dunsby
    Brann
    Joachim Soltvedt: 379 passningar, xT 2.52SoltvedtThore Pedersen: 259 passningar, xT 0.39PedersenVetle Dragsnes: 231 passningar, xT 0.32DragsnesFredrik Pallesen Knudsen: 217 passningar, xT 0.22KnudsenDenzel De Roeve: 200 passningar, xT 1.48RoeveNiklas Castro: 181 passningar, xT 2.34CastroJakob Lungi Sørensen: 179 passningar, xT 0.29SørensenMathias Dyngeland: 165 passningar, xT 0.14DyngelandFelix Horn Myhre: 143 passningar, xT 0.22MyhreNiklas Wassberg: 132 passningar, xT 0.02WassbergKristian Eriksen: 96 passningar, xT 0.19Eriksen

    The teams in numbers

    PerformanceSandefjordBrann
    Points1825
    xPoints20.121.6
    xG per match1.31.8
    xGA per match1.81.6
    xG within 8s of winning the ball0.210.32
    xGA within 8s of losing the ball0.250.16
    Playing styleSandefjordBrann
    Build-up efficiency0.290.32
    Field tilt0.420.65
    xT per match0.861.6
    xTA per match1.21.2
    Won balls, offensive half2529
    Pressing intensity0.240.23
    Pressing efficiency0.280.31
    Pressing efficiency, offensive half0.250.31
    Entries into the box per match1221
    Entries into the box against1814
    Pass completion %0.780.76
    Pass completion % under pressure0.730.71
    Passes per match393431
    Passes against per match376278
    Switches of play per match26.227.4
    Long balls per match3735
    Set piecesSandefjordBrann
    xG from free kicks0.030.04
    Corners per match5.76.7
    Corners against per match6.65.1
    xG per corner0.040.04
    xGA per corner against0.040.04
    First touch, offensive corners %0.30.42
    First touch, defensive corners %0.650.61
    OtherSandefjordBrann
    Throw-in control0.670.7
    The goalkeepersElias Hadaya (Sandefjord)Mathias Dyngeland (Brann)
    Saves6030
    Save %72%64%
    xG prevented51%38%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Sandefjord vs Brann according to our model?

    The model gives Brann a 49% win probability. Full 1X2 picture: Sandefjord 27%, draw 23%, Brann 49%.

    What is the most likely scoreline?

    The model's most likely final score is 1-1 at 10% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 63% and under at 37%.

    Will both teams score?

    The probability of both teams scoring is 63% 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.