Swedish Ettan

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    KarlbergKarlbergBalanced & physical
    vs
    ArlandaArlandaCounter-attacks & crosses
    The model's lean: 1 · Karlberg (39%)Soft draw

    KarlbergArlanda · Swedish Ettan

    1 · Karlberg 39%X 24%37% Arlanda · 2

    Analysis: KarlbergArlanda

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

    TEXT: Karlberg's physical style of play might just tip the scales in their favor against Arlanda's counter-attacking game. Despite Arlanda's slight lead in the standings with 36 points compared to the hosts' 25, Karlberg's underlying numbers tell a different story. They boast a higher expected points tally of 29.4 compared to Arlanda's 28.7, and their xG per match (1.5) also edges out the visitors' 1.4. This suggests that Karlberg may have been somewhat unlucky in terms of actual results.

    The head-to-head record offers little clarity, with just three encounters since the start of 2023: each team has taken a win, and they've played to a draw once. This small sample size means recent form and expected goals data should be weighted more heavily in any analysis. The model favors Karlberg, giving them a 39% chance of victory versus Arlanda's 37%, with a 24% chance of a draw. This underlines the hosts' potential to disrupt Arlanda's game plan, particularly if they can impose their physicality and disrupt the visitors' reliance on crosses and quick transitions.

    With expected goals at 1.71 for Karlberg and 1.44 for Arlanda, the prospect of both teams finding the net is high, reflected in the 63% probability for both teams to score and a 61% chance of over 2.5 goals. This aligns with the most probable scorelines, with 1-1 (11%) and 2-1 (9%) being the most likely outcomes.

    Given these dynamics, the most prudent prediction leans towards a narrow victory for Karlberg, possibly 2-1, where their balanced approach could just outmuscle Arlanda's counters. The attacking potential and defensive vulnerabilities both sides have displayed this season also support the over 2.5 goals market as a point of interest.

    KarlbergKarlberg
    Form LWLDL
    League ranking xG #12xGA #18xT #15xP/match #13Points #18
    Key players
    • Noah Tesfai NegashLWxG 0.20 · xT 0.26
    • Adam JemalFxG 0.46 · xT 0.18
    • Mattias MitkuFxG 0.28 · xT 0.15
    ArlandaArlanda
    Form DLWWL
    League ranking xG #15xGA #16xT #13xP/match #14Points #8
    Key players
    • Carl NorbergRWxG 0.06 · xT 0.64
    • Mario ButrosCAMxG 0.14 · xT 0.27
    • Isac AntholmLWxG 0.33 · xT 0.12

    Match prediction: KarlbergArlanda

    Predicted score matrix

    Arlanda
    Karlberg
    0
    1
    2
    3
    4+
    0
    0–04.6%
    0–15.9%
    0–24.5%
    0–32.1%
    0–4+1.1%
    1
    1–07.0%
    1–110.9%
    1–27.6%
    1–33.7%
    1–4+1.8%
    2
    2–06.2%
    2–19.0%
    2–26.5%
    2–33.1%
    2–4+1.5%
    3
    3–03.6%
    3–15.1%
    3–23.7%
    3–31.8%
    3–4+0.9%
    4+
    4+–02.2%
    4+–13.2%
    4+–22.3%
    4+–31.1%
    4+–4+0.6%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-111%
    2. 2.2-19%
    3. 3.1-28%
    4. 4.1-07%
    5. 5.2-26%
    Expected goals
    1,711,44
    Both teams to score
    63%

    Over/under goals

    Expected goals: 3,1
    Under 2,539%
    @2.25
    Over 2,561%
    @1.55

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Double chance Karlberg or draw (1X)68%
    • Over 1.5 goals83%

    Combined probability

    56%

    Fair odds

    1.78

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

    02 · 3 legs

    Balanced

    • Double chance Karlberg or draw (1X)68%
    • Over 2.5 goals61%
    • Adam Jemal to score33%

    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 goals61%
    • Adam Jemal to score33%
    • Mario Butros to be booked18%

    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

    Bookmaker1 · KarlbergX2 · Arlanda
    Betsafe2.523.452.42
    Betsson2.523.452.42
    Nordicbet2.523.452.42

    Odds updated 11 Sept, 05:37

    Odds movement

    1+10 %
    45 %25 %

    2.302.52

    X-1 %
    36 %16 %

    3.503.45

    2-8 %
    50 %30 %

    2.622.42

    Betsson · 10 recorded price levels · 07/09/2026 → 11/09/2026 · fixed scale 20 percentage points

    Statistics

    Head-to-head

    3 matches
    Karlberg 1Draw 1Arlanda 1
    Goals: 34 (⌀ 2,3)

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

    xG & xGA per match — 3-game rolling average

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

    Karlberg
    Arlanda
    When goals are scored and conceded 2026
    Karlberg (2831)
    Arlanda (3424)
    Pass networks

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

    Karlberg
    Hugo Åslund: 200 passningar, xT 0.15ÅslundAdam Backman: 199 passningar, xT 0.25BackmanLukas Sietsema: 195 passningar, xT 0.4SietsemaFilip Nieminen Eriksson: 183 passningar, xT 0.34ErikssonAbiel Sequar: 178 passningar, xT 0.39SequarArgyrios Gkoulios: 165 passningar, xT 0.32GkouliosFelix Högberg: 155 passningar, xT 0.33HögbergAladji Fati: 137 passningar, xT 0.13FatiMattias Mitku: 132 passningar, xT 0.51MitkuNoah Tesfai Negash: 108 passningar, xT 0.23NegashMilan Lalic: 81 passningar, xT 0.8Lalic
    Arlanda
    Erik Johansson Olsson: 232 passningar, xT 0.42OlssonCarl Norberg: 226 passningar, xT 3.18NorbergYoas Yemane: 175 passningar, xT 0.56YemaneLeonard Kleist: 168 passningar, xT 0.59KleistMark Gorgos: 133 passningar, xT 0.28GorgosIsac Giordano Eriksson: 106 passningar, xT 0.13ErikssonMuktar Ahmed: 83 passningar, xT 0.06AhmedAdam Smedberg Lagh: 78 passningar, xT 0.2LaghIsac Antholm: 65 passningar, xT 0.19AntholmSaifur Rehman: 54 passningar, xT -0.06RehmanLudvig Lars Johan Nyman: 52 passningar, xT -0.03Nyman
    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.

    Karlberg
    Hugo Åslund: 200 passningar, xT 0.15ÅslundAdam Backman: 199 passningar, xT 0.25BackmanLukas Sietsema: 195 passningar, xT 0.4SietsemaFilip Nieminen Eriksson: 183 passningar, xT 0.34ErikssonAbiel Sequar: 178 passningar, xT 0.39SequarArgyrios Gkoulios: 165 passningar, xT 0.32GkouliosFelix Högberg: 155 passningar, xT 0.33HögbergAladji Fati: 137 passningar, xT 0.13FatiMattias Mitku: 132 passningar, xT 0.51MitkuNoah Tesfai Negash: 108 passningar, xT 0.23NegashMilan Lalic: 81 passningar, xT 0.8Lalic
    Arlanda
    Erik Johansson Olsson: 232 passningar, xT 0.42OlssonCarl Norberg: 226 passningar, xT 3.18NorbergYoas Yemane: 175 passningar, xT 0.56YemaneLeonard Kleist: 168 passningar, xT 0.59KleistMark Gorgos: 133 passningar, xT 0.28GorgosIsac Giordano Eriksson: 106 passningar, xT 0.13ErikssonMuktar Ahmed: 83 passningar, xT 0.06AhmedAdam Smedberg Lagh: 78 passningar, xT 0.2LaghIsac Antholm: 65 passningar, xT 0.19AntholmSaifur Rehman: 54 passningar, xT -0.06RehmanLudvig Lars Johan Nyman: 52 passningar, xT -0.03Nyman

    The teams in numbers

    PerformanceKarlbergArlanda
    Points2536
    xPoints29.428.7
    xG per match1.51.4
    xGA per match1.41.4
    xG within 8s of winning the ball0.220.26
    xGA within 8s of losing the ball0.380.29
    Playing styleKarlbergArlanda
    Build-up efficiency0.350.34
    Field tilt0.470.41
    xT per match1.41.4
    xTA per match1.51.4
    Won balls, offensive half2833
    Pressing intensity0.520.5
    Pressing efficiency0.230.29
    Pressing efficiency, offensive half0.230.32
    Entries into the box per match1211
    Entries into the box against1414
    Pass completion %0.820.73
    Pass completion % under pressure0.770.67
    Passes per match372263
    Passes against per match381334
    Switches of play per match1317.7
    Long balls per match2732
    Set piecesKarlbergArlanda
    xG from free kicks0.20.13
    Corners per match4.33.6
    Corners against per match4.44.8
    xG per corner0.030.03
    xGA per corner against0.010.03
    First touch, offensive corners %0.430.45
    First touch, defensive corners %0.660.58
    OtherKarlbergArlanda
    Throw-in control0.610.42
    The goalkeepersArgyrios Gkoulios (Karlberg)Adam Smedberg Lagh (Arlanda)
    Saves5969
    Save %73%75%
    xG prevented52%56%
    Claims76 (91%)98 (95%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Karlberg vs Arlanda according to our model?

    The model gives Karlberg a 39% win probability. Full 1X2 picture: Karlberg 39%, draw 24%, Arlanda 37%.

    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 61% and under at 39%.

    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.

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