Swedish AllsvenskanStora Valla, Örebro13°26 km/h

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    DegerforsDegerforsBalanced & physical
    vs
    HammarbyHammarbyPossession & high press
    The model's lean: 2 · Hammarby (65%)Best value by the model: 1 · Degerfors @ 8.58 (+21 %)

    Degerfors vs Hammarby · Swedish Allsvenskan

    1 · Degerfors 14%X 21%65% Hammarby · 2

    Analysis: DegerforsHammarby

    Oscar Nilsson · · Model-assisted analysis, fact-checked · How the predictions work

    Hammarby's attacking prowess is hard to overlook, with the team having found the back of the net in their last 12 league outings. This spells potential trouble for Degerfors, who on average concede 1.6 goals per match. The visitors' high press and possession play have not only helped them secure 40 points this season but also sustain an xG of 2.3 per match, a significant margin over Degerfors' 0.91. The model's 65% probability for a Hammarby win underscores this dominance.

    The head-to-head record doesn't flatter the hosts either. In the last five meetings, Hammarby have yet to taste defeat, winning three times. Although these encounters average 3.0 goals, suggesting an open fixture, Degerfors have struggled to convert their physical game into results against the visitors' style.

    Yet, where there's imbalance, there's opportunity — chiefly in the form of a value bet. Betsafe, Betsson, and Nordicbet all offer Degerfors at 9.7, whereas the model sees their chances at 14%. With a 37% edge, it’s the kind of long shot that intrigues the contrarian bettor, though it comes with its risks.

    Predicted scoreline leans heavily towards a 0-2 or 0-1 Hammarby victory, supported by their solid defensive record, conceding just 0.93 xGA per match. With an over 2.5 goals likelihood at 58%, the dynamics tilt towards a game with at least a couple of goals, likely from the visitors.

    For those keen on a calculated gamble, the odds on the home side offer the best return, albeit with a reality check against Hammarby's formbook and statistical superiority.

    DegerforsDegerfors
    Form WLLWL
    League ranking xG #16xGA #11xT #11xP/match #14Points #14
    Key players
    • Nahom Girmai NetabayRWxG 0.07 · xT 0.32
    • Dijan VukojevicFxG 0.23 · xT 0.21
    • Daniel SundgrenRWxG 0.03 · xT 0.23
    HammarbyHammarby
    Form WWLDW
    League ranking xG #1xGA #1xT #1xP/match #2Points #3
    Key players
    • Montader MadjedRWxG 0.27 · xT 0.27
    • Hampus SkoglundRWxG 0.03 · xT 0.18
    • Paulos AbrahamFxG 0.69 · xT 0.10

    Match prediction: DegerforsHammarby

    Predicted score matrix

    Hammarby
    Degerfors
    0
    1
    2
    3
    4+
    0
    0–05.1%
    0–110.3%
    0–211.4%
    0–38.3%
    0–4+7.4%
    1
    1–03.9%
    1–19.3%
    1–29.8%
    1–37.1%
    1–4+6.4%
    2
    2–01.8%
    2–13.9%
    2–24.2%
    2–33.0%
    2–4+2.7%
    3
    3–00.5%
    3–11.1%
    3–21.2%
    3–30.9%
    3–4+0.8%
    4+
    4+–00.1%
    4+–10.3%
    4+–20.3%
    4+–30.2%
    4+–4+0.2%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.0-211%
    2. 2.0-110%
    3. 3.1-210%
    4. 4.1-19%
    5. 5.0-38%
    Expected goals
    0,862,17
    Both teams to score
    51%

    Over/under goals

    Expected goals: 3,0
    Under 2,542%
    @2.38
    Over 2,558%
    @1.52

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Hammarby to win65%
    • Over 1.5 goals81%

    Combined probability

    57%

    Fair odds

    1.76

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

    02 · 3 legs

    Balanced

    • Hammarby to win65%
    • Over 2.5 goals58%
    • Paulos Abraham to score35%

    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 score51%
    • Over 2.5 goals58%
    • Paulos Abraham to score35%
    • Bilal Hussein to be booked21%

    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 · Degerfors14% probability@8.58BetsafeEV+21%reference odds
    • 1 · Degerfors14% probability@8.58BetssonEV+21%reference odds
    • 1 · Degerfors14% probability@8.58NordicbetEV+21%reference odds
    Bookmaker1 · DegerforsX2 · Hammarby
    Betfair Exchange1.101.101.10
    Betsafe
    EV+ 21%
    8.58
    EV+ 13%
    5.39
    1.33
    Betsson
    EV+ 21%
    8.58
    EV+ 13%
    5.39
    1.33
    Nordicbet
    EV+ 21%
    8.58
    EV+ 13%
    5.39
    1.33
    Pinnacle
    EV+ 14%
    8.07
    EV+ 13%
    5.39
    1.32

    Odds updated 19 Sept, 14:37

    Odds movement

    1-1 %
    14 %9 %

    8.138.07

    X-1 %
    20 %15 %

    5.475.39

    2+1 %
    74 %69 %

    1.311.32

    Pinnacle · 4 recorded price levels · 15/09/2026 → 19/09/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    5 matches
    Degerfors 0Draw 2Hammarby 3
    Goals: 411 (⌀ 3)

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

    Key facts

    • Hammarby dominate this fixture historically: 3 wins to 0 in 5 meetings.
    • A high-scoring fixture: 3.0 goals per meeting on average.
    • Hammarby have scored in 12 consecutive league matches.
    xG & xGA per match — 3-game rolling average

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

    Degerfors
    Hammarby
    When goals are scored and conceded 2026
    Degerfors (1933)
    Hammarby (4820)
    Pass networks

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

    Degerfors
    Bilal Hussein: 280 passningar, xT 0.26HusseinNikolai Skuseth: 269 passningar, xT 0.29SkusethAhmad Faqa: 257 passningar, xT 0.46FaqaCR Sebastian Ohlsson: 188 passningar, xT 0.6OhlssonDaniel Sundgren: 188 passningar, xT 0.49SundgrenDijan Vukojevic: 113 passningar, xT 1.02VukojevicRobin Dzabic: 105 passningar, xT 0.14DzabicNahom Girmai Netabay: 86 passningar, xT 0.42NetabaySamba Diatara: 84 passningar, xT 0.47DiataraKazper Karlsson: 83 passningar, xT -0.04KarlssonElias Barsoum: 77 passningar, xT 0.41Barsoum
    Hammarby
    Frederik Winther: 460 passningar, xT 0.53WintherHampus Skoglund: 415 passningar, xT 0.45SkoglundMarkus Karlsson: 302 passningar, xT 0.25KarlssonNoah Persson: 266 passningar, xT 0.77PerssonVictor Eriksson: 243 passningar, xT 0.17ErikssonIbrahima Breze Fofana: 232 passningar, xT 0.25FofanaVictor Stange Lind: 205 passningar, xT 1.17LindMontader Madjed: 187 passningar, xT 0.69MadjedFrank Junior Agyei: 152 passningar, xT 0.62AgyeiWarner Hahn: 130 passningar, xT 0.13HahnAmin Boudri: 110 passningar, xT 0.42Boudri
    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.

    Degerfors
    Bilal Hussein: 280 passningar, xT 0.26HusseinNikolai Skuseth: 269 passningar, xT 0.29SkusethAhmad Faqa: 257 passningar, xT 0.46FaqaCR Sebastian Ohlsson: 188 passningar, xT 0.6OhlssonDaniel Sundgren: 188 passningar, xT 0.49SundgrenDijan Vukojevic: 113 passningar, xT 1.02VukojevicRobin Dzabic: 105 passningar, xT 0.14DzabicNahom Girmai Netabay: 86 passningar, xT 0.42NetabaySamba Diatara: 84 passningar, xT 0.47DiataraKazper Karlsson: 83 passningar, xT -0.04KarlssonElias Barsoum: 77 passningar, xT 0.41Barsoum
    Hammarby
    Frederik Winther: 460 passningar, xT 0.53WintherHampus Skoglund: 415 passningar, xT 0.45SkoglundMarkus Karlsson: 302 passningar, xT 0.25KarlssonNoah Persson: 266 passningar, xT 0.77PerssonVictor Eriksson: 243 passningar, xT 0.17ErikssonIbrahima Breze Fofana: 232 passningar, xT 0.25FofanaVictor Stange Lind: 205 passningar, xT 1.17LindMontader Madjed: 187 passningar, xT 0.69MadjedFrank Junior Agyei: 152 passningar, xT 0.62AgyeiWarner Hahn: 130 passningar, xT 0.13HahnAmin Boudri: 110 passningar, xT 0.42Boudri

    The teams in numbers

    PerformanceDegerforsHammarby
    Points1940
    xPoints21.739
    xG per match0.912.3
    xGA per match1.60.93
    xG within 8s of winning the ball0.240.45
    xGA within 8s of losing the ball0.320.24
    Playing styleDegerforsHammarby
    Build-up efficiency0.350.35
    Field tilt0.450.76
    xT per match1.41.7
    xTA per match1.40.84
    Won balls, offensive half3338
    Pressing intensity0.470.57
    Pressing efficiency0.240.25
    Pressing efficiency, offensive half0.270.25
    Entries into the box per match1120
    Entries into the box against148
    Pass completion %0.790.87
    Pass completion % under pressure0.750.83
    Passes per match361560
    Passes against per match420318
    Switches of play per match13.811
    Long balls per match2724
    Set piecesDegerforsHammarby
    xG from free kicks0.080.21
    Corners per match4.96.6
    Corners against per match5.32.7
    xG per corner0.030.03
    xGA per corner against0.030.04
    First touch, offensive corners %0.250.53
    First touch, defensive corners %0.640.6
    OtherDegerforsHammarby
    Throw-in control0.550.72
    The goalkeepersMatvei Igonen (Degerfors)Warner Hahn (Hammarby)
    Saves7442
    Save %69%68%
    xG prevented43%36%
    Claims101 (91%)80 (98%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Degerfors vs Hammarby according to our model?

    The model gives Hammarby a 65% win probability. Full 1X2 picture: Degerfors 14%, draw 21%, Hammarby 65%.

    What is the most likely scoreline?

    The model's most likely final score is 0-2 at 11% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 58% and under at 42%.

    Will both teams score?

    The probability of both teams scoring is 51% 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.