Swedish Ettan

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    KarlbergKarlbergBalanced & physical
    vs
    AFC EskilstunaAFC EskilstunaLow block & direct
    The model's lean: 1 · Karlberg (43%)Best value by the model: Under 2,5 @ 2.62 (+9 %)
    Limited data — The model has thin or uncertain data for this match — the forecast may be unreliable and the match is excluded from our value lists.

    Karlberg – AFC Eskilstuna · Swedish Ettan

    1 · Karlberg 43%X 25%32% AFC Eskilstuna · 2

    Analysis: Karlberg – AFC Eskilstuna

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

    Two of the Ettan's sides will meet with Karlberg hosting AFC Eskilstuna. The head-to-head record between these teams is too limited to heavily influence the analysis, leaving us to focus on current form and expected goals. With the home side sitting slightly behind in actual points (24) compared to Eskilstuna's 28, there is a nuance to be explored. Karlberg's xPoints of 27.5 hint at underachievement, while the visitors' 25.1 suggests they might have been riding their luck to some extent.

    Karlberg's balanced and physical approach has earned them a slight edge in xG terms, averaging 1.6 per match compared to Eskilstuna's 1.4. Despite AFC's direct style, their defensive frailties are exposed by an xGA of 1.4, slightly worse than Karlberg's 1.3. These numbers subtly nudge the scales towards the hosts, aligning with the model's 43% win probability for Karlberg as opposed to Eskilstuna's 32%.

    In a matchup where the most likely scorelines appear evenly split between 1-1, 2-1, and 1-0, the 59% probability for over 2.5 goals and 61% for both teams to score suggests we might see an open game. Yet, the numbers whisper caution. The model's top scoreline, 1-1, underscores the potential for a tightly contested affair, although a 2-1 home win isn't far behind.

    From a betting perspective, the model's lean towards Karlberg at 43% implies a potential value on the hosts, particularly if odds are favorable. With Bet365 offering 3.10 for a Karlberg win, this might be the angle that pays the bills. Not a guarantee, but a calculated play on a night where margins could be as slim as the expected difference in goals.

    KarlbergKarlberg
    Form WWWLW
    League ranking xG #6xGA #12xT #9xP/match #6Points #15
    Key players
    • Noah Tesfai NegashLWxG 0.21 · xT 0.28
    • Adam JemalFxG 0.50 · xT 0.20
    • Mattias MitkuFxG 0.29 · xT 0.18
    AFC EskilstunaAFC Eskilstuna
    League ranking xG #14xGA #18xT #31xP/match #11Points #9
    Key players
    • Sixten SköldqvistFxG 0.18 · xT 0.08
    • Robin BjörkmanFxG 0.27 · xT 0.10
    • Lee HanssonFxG 0.29 · xT 0.25

    Match prediction: Karlberg – AFC Eskilstuna

    Predicted score matrix

    AFC Eskilstuna →
    Karlberg →
    0
    1
    2
    3
    4+
    0
    0–05.1%
    0–16.2%
    0–24.4%
    0–32.0%
    0–4+0.9%
    1
    1–07.7%
    1–111.3%
    1–27.4%
    1–33.4%
    1–4+1.5%
    2
    2–06.8%
    2–19.2%
    2–26.2%
    2–32.8%
    2–4+1.3%
    3
    3–03.8%
    3–15.2%
    3–23.5%
    3–31.6%
    3–4+0.7%
    4+
    4+–02.3%
    4+–13.2%
    4+–22.1%
    4+–31.0%
    4+–4+0.4%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-111%
    2. 2.2-19%
    3. 3.1-08%
    4. 4.1-27%
    5. 5.2-07%
    Expected goals
    1,68–1,36
    Both teams to score
    61%

    Over/under goals

    Expected goals: 3,0
    Under 2,541%
    @2.62EV+9%
    Over 2,559%
    @1.43

    Ready-made bet suggestions

    More combos & build your own →

    01 · 2 legs

    Safe

    • Double chance Karlberg or draw (1X)69%
    • Over 1.5 goals81%

    Combined probability

    57%

    Fair odds

    1.77

    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)69%
    • Over 2.5 goals59%
    • Arthin Jamshidi to score38%

    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 score61%
    • Over 2.5 goals59%
    • Arthin Jamshidi to score38%
    • Ryan Williams to be booked19%

    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+).

    • Under 2.541% probability@2.62BetsafeEV+9%reference odds
    • Under 2.541% probability@2.62BetssonEV+9%reference odds
    • Under 2.541% probability@2.62NordicbetEV+9%reference odds
    Bookmaker1 · KarlbergX2 · AFC Eskilstuna
    Betsafe2.003.752.95
    Betsson2.003.752.95
    Nordicbet2.003.752.95

    Odds updated 19 Aug, 00:36

    Odds movement

    1+4 %
    50 %45 %

    1.92 → 2.00

    X-1 %
    27 %22 %

    3.80 → 3.75

    2-5 %
    31 %26 %

    3.10 → 2.95

    Betsson · 7 recorded price levels · 18/08/2026 → 19/08/2026 · fixed scale 5 percentage points

    Statistics

    xG & xGA per match — 3-game rolling average

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

    Karlberg
    When goals are scored and conceded — 2026
    Karlberg (28–25)
    Pass networks

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

    Karlberg
    Robin Sundgren: 202 passningar, xT 0.22SundgrenViktor Steen: 178 passningar, xT 0.14SteenNoah Tesfai Negash: 155 passningar, xT 0.8NegashFilip Nieminen Eriksson: 146 passningar, xT 0.39ErikssonLukas Sietsema: 130 passningar, xT 0.2SietsemaAbiel Sequar: 117 passningar, xT 0.25SequarHugo Åslund: 116 passningar, xT 0.08ÅslundMattias Mitku: 99 passningar, xT 0.42MitkuArgyrios Gkoulios: 86 passningar, xT 0.14GkouliosNino Geiger: 77 passningar, xT 0.01GeigerHugo Fernández: 68 passningar, xT 0.98Fernández
    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
    Robin Sundgren: 202 passningar, xT 0.22SundgrenViktor Steen: 178 passningar, xT 0.14SteenNoah Tesfai Negash: 155 passningar, xT 0.8NegashFilip Nieminen Eriksson: 146 passningar, xT 0.39ErikssonLukas Sietsema: 130 passningar, xT 0.2SietsemaAbiel Sequar: 117 passningar, xT 0.25SequarHugo Åslund: 116 passningar, xT 0.08ÅslundMattias Mitku: 99 passningar, xT 0.42MitkuArgyrios Gkoulios: 86 passningar, xT 0.14GkouliosNino Geiger: 77 passningar, xT 0.01GeigerHugo Fernández: 68 passningar, xT 0.98Fernández

    The teams in numbers

    PerformanceKarlbergAFC Eskilstuna
    Points2428
    xPoints27.525.1
    xG per match1.61.4
    xGA per match1.31.4
    xG within 8s of winning the ball0.250.33
    xGA within 8s of losing the ball0.380.21
    Playing styleKarlbergAFC Eskilstuna
    Build-up efficiency0.350.38
    Field tilt0.480.45
    xT per match1.51
    xTA per match1.51.5
    Won balls, offensive half2929
    Pressing intensity0.510.49
    Pressing efficiency0.240.22
    Pressing efficiency, offensive half0.240.24
    Entries into the box per match1312
    Entries into the box against1413
    Pass completion %0.810.79
    Pass completion % under pressure0.770.73
    Passes per match358344
    Passes against per match381403
    Switches of play per match1316.4
    Long balls per match2632
    Set piecesKarlbergAFC Eskilstuna
    xG from free kicks0.210.12
    Corners per match4.54.8
    Corners against per match4.24.5
    xG per corner0.040.02
    xGA per corner against0.010.05
    First touch, offensive corners %0.430.45
    First touch, defensive corners %0.650.54
    OtherKarlbergAFC Eskilstuna
    Throw-in control0.60.56
    The goalkeepersArgyrios Gkoulios (Karlberg)AFC Eskilstuna
    Saves39–
    Save %71%–
    xG prevented48%–
    Claims57 (91%)–

    Frequently asked questions

    Who wins Karlberg vs AFC Eskilstuna according to our model?

    The model gives Karlberg a 43% win probability. Full 1X2 picture: Karlberg 43%, draw 25%, AFC Eskilstuna 32%.

    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 59% and under at 41%.

    Will both teams score?

    The probability of both teams scoring is 61% 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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    GefleGefle
    1 28%X 21%2 51%
    The model called the outcome
    IFK StocksundIFK Stocksund
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    1 40%X 20%2 40%
    The model called the outcome

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