Swedish AllsvenskanEleda Stadion, Malmö16°2,4 mm18 km/h

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    Malmö FFMalmö FFPossession & high press
    vs
    DjurgårdenDjurgårdenPossession & high press
    The model's lean: 1 · Malmö FF (40%)

    Malmö FFDjurgården · Swedish Allsvenskan

    1 · Malmö FF 40%X 25%35% Djurgården · 2

    Analysis: Malmö FFDjurgården

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

    Malmö FF have managed to find the back of the net in 23 consecutive league matches, a testament to their offensive consistency. Yet, facing Djurgårdens IF, a team that has been more effective in their expected goals metrics—boasting 1.9 xG per match against Malmö’s 1.5—presents a fascinating clash of current form versus historical dominance. While Malmö FF has the upper hand in head-to-head results, winning four of their seven encounters since 2023, this sample is too small to ignore the broader metrics which suggest a closer contest.

    Malmö FF's home form is formidable, winning 64% of their home games in the league's history. However, Djurgårdens IF's superior expected points (26.9 compared to Malmö’s 22.4) and their higher xG when regaining possession quickly (0.42 to 0.23) paint a picture of a side adept at capitalizing on transitional moments. Moreover, the possession-heavy styles of both teams might mean that whoever controls the tempo more effectively could edge this encounter.

    With the model giving Malmö FF a slight 40% win probability edge over Djurgårdens IF's 35%, the narrow margins are reflected in the most likely scorelines: 1-1 (11%) and 2-1 (9%). The expected goals tally also suggests a closely fought battle, with Malmö slightly ahead at 1.58 compared to Djurgårdens’ 1.44. This leaves the over 2.5 goals line—sitting at a 58% probability—as an enticing prospect.

    Weather conditions can often suppress goal-scoring, but since there are no weather concerns in the provided facts, the high-scoring prediction stands firm. For those keen on the betting angle, the model’s lean towards Malmö FF and the high likelihood of both teams finding the net (61%) makes a 2-1 scoreline a tempting consideration, particularly if you can find value at Bet365 with odds on the over 2.5 goals market. As always, these angles are assessments, not certainties, but the numbers suggest a lively encounter with goals on the cards.

    Malmö FFMalmö FF
    Form DLWLW
    League ranking xG #7xGA #7xT #12xP/match #10Points #6
    Key players
    • Taha Abdi AliLWxG 0.10 · xT 0.23
    • Erik BotheimFxG 0.50 · xT -0.04
    • Malte Frejd PålssonCBxG 0.02 · xT 0.15
    DjurgårdenDjurgården
    Form DWWLL
    League ranking xG #3xGA #4xT #4xP/match #4Points #5
    Key players
    • Bo HeglandFxG 0.36 · xT 0.29
    • Max LarssonLWxG 0.07 · xT 0.24
    • Kristian LienFxG 0.57 · xT 0.05

    Match prediction: Malmö FFDjurgården

    Predicted score matrix

    Djurgården
    Malmö FF
    0
    1
    2
    3
    4+
    0
    0–05.2%
    0–16.7%
    0–25.1%
    0–32.4%
    0–4+1.2%
    1
    1–07.3%
    1–111.4%
    1–28.0%
    1–33.9%
    1–4+1.9%
    2
    2–06.1%
    2–18.8%
    2–26.3%
    2–33.0%
    2–4+1.5%
    3
    3–03.2%
    3–14.6%
    3–23.3%
    3–31.6%
    3–4+0.8%
    4+
    4+–01.8%
    4+–12.6%
    4+–21.9%
    4+–30.9%
    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. 3.1-28%
    4. 4.1-07%
    5. 5.0-17%
    Expected goals
    1,581,44
    Both teams to score
    61%

    Over/under goals

    Expected goals: 3,0
    Under 2,542%
    @2.38
    Over 2,558%
    @1.55

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Double chance Malmö FF or draw (1X)66%
    • Over 1.5 goals81%

    Combined probability

    53%

    Fair odds

    1.89

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

    02 · 3 legs

    Balanced

    • Double chance Malmö FF or draw (1X)66%
    • Over 2.5 goals58%
    • Erik Botheim to score16%

    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 goals58%
    • Kristian Lien to score27%
    • Hampus Finndell 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 · Malmö FF40% probability@2.61BetsafeEV+5%reference odds
    • 1 · Malmö FF40% probability@2.61BetssonEV+5%reference odds
    • 1 · Malmö FF40% probability@2.61NordicbetEV+5%reference odds
    Bookmaker1 · Malmö FFX2 · Djurgården
    Betsafe
    EV+ 5%
    2.61
    3.482.61
    Betsson
    EV+ 5%
    2.61
    3.482.61
    Nordicbet
    EV+ 5%
    2.61
    3.482.61

    Odds updated 18 Aug, 10:36

    Odds movement

    10 %
    39 %34 %

    2.622.61

    X-4 %
    29 %24 %

    3.643.48

    2+4 %
    40 %35 %

    2.522.61

    Over 2,5+2 %
    63 %58 %

    1.521.55

    Betsson · 7 recorded price levels · 17/08/2026 → 18/08/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    7 matches
    Malmö FF 4Draw 1Djurgården 2
    Goals: 73 (⌀ 1,4)

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

    Key facts

    • Malmö FF dominate this fixture historically: 4 wins to 2 in 7 meetings.
    • Malmö FF have scored in 23 consecutive league matches.
    • Malmö FF win 64% of their home matches all-time (53 played).
    xG & xGA per match — 3-game rolling average

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

    Malmö FF
    Djurgården
    When goals are scored and conceded 2026
    Malmö FF (3227)
    Djurgården (3419)
    Pass networks

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

    Malmö FF
    Malte Frejd Pålsson: 317 passningar, xT 0.39PålssonAndrej Đurić: 303 passningar, xT 0.34ĐurićJens Stryger Larsen: 296 passningar, xT 1.58LarsenOtto Rosengren: 275 passningar, xT 0.5RosengrenSead Haksabanovic: 270 passningar, xT 1.66HaksabanovicNoah Åstrand John: 191 passningar, xT 0.43JohnAdrian Skogmar: 156 passningar, xT 0.03SkogmarKenan Busuladzic: 149 passningar, xT 0.48BusuladzicTheodor Lundbergh: 130 passningar, xT -0.07LundberghBleon Kurtulus: 126 passningar, xT 0.05KurtulusGabriel Dal Toe Busanello: 122 passningar, xT 0.48Busanello
    Djurgården
    Jacob Une: 336 passningar, xT 0.29UneMatias Siltanen: 290 passningar, xT 0.45SiltanenMax Larsson: 224 passningar, xT 1.09LarssonMiro Tenho: 217 passningar, xT 0.21TenhoHampus Finndell: 183 passningar, xT 0.28FinndellAdam Ståhl: 171 passningar, xT 0.21StåhlBo Hegland: 159 passningar, xT 1.55HeglandJacob Rinne: 152 passningar, xT 0.61RinnePatric Åslund: 116 passningar, xT 0.42ÅslundPiotr Johansson: 98 passningar, xT 0.08JohanssonOskar Fallenius: 88 passningar, xT -0.05Fallenius
    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.

    Malmö FF
    Malte Frejd Pålsson: 317 passningar, xT 0.39PålssonAndrej Đurić: 303 passningar, xT 0.34ĐurićJens Stryger Larsen: 296 passningar, xT 1.58LarsenOtto Rosengren: 275 passningar, xT 0.5RosengrenSead Haksabanovic: 270 passningar, xT 1.66HaksabanovicNoah Åstrand John: 191 passningar, xT 0.43JohnAdrian Skogmar: 156 passningar, xT 0.03SkogmarKenan Busuladzic: 149 passningar, xT 0.48BusuladzicTheodor Lundbergh: 130 passningar, xT -0.07LundberghBleon Kurtulus: 126 passningar, xT 0.05KurtulusGabriel Dal Toe Busanello: 122 passningar, xT 0.48Busanello
    Djurgården
    Jacob Une: 336 passningar, xT 0.29UneMatias Siltanen: 290 passningar, xT 0.45SiltanenMax Larsson: 224 passningar, xT 1.09LarssonMiro Tenho: 217 passningar, xT 0.21TenhoHampus Finndell: 183 passningar, xT 0.28FinndellAdam Ståhl: 171 passningar, xT 0.21StåhlBo Hegland: 159 passningar, xT 1.55HeglandJacob Rinne: 152 passningar, xT 0.61RinnePatric Åslund: 116 passningar, xT 0.42ÅslundPiotr Johansson: 98 passningar, xT 0.08JohanssonOskar Fallenius: 88 passningar, xT -0.05Fallenius

    The teams in numbers

    PerformanceMalmö FFDjurgården
    Points2626
    xPoints22.426.9
    xG per match1.51.9
    xGA per match1.31.1
    xG within 8s of winning the ball0.230.42
    xGA within 8s of losing the ball0.290.16
    Playing styleMalmö FFDjurgården
    Build-up efficiency0.350.37
    Field tilt0.590.6
    xT per match1.31.6
    xTA per match1.41.4
    Won balls, offensive half2733
    Pressing intensity0.50.52
    Pressing efficiency0.250.26
    Pressing efficiency, offensive half0.260.27
    Entries into the box per match1717
    Entries into the box against1512
    Pass completion %0.840.83
    Pass completion % under pressure0.80.78
    Passes per match462444
    Passes against per match326322
    Switches of play per match14.616.7
    Long balls per match3629
    Set piecesMalmö FFDjurgården
    xG from free kicks0.270.17
    Corners per match4.67
    Corners against per match5.54.1
    xG per corner0.040.03
    xGA per corner against0.030.01
    First touch, offensive corners %0.580.39
    First touch, defensive corners %0.520.62
    OtherMalmö FFDjurgården
    Throw-in control0.590.65
    The goalkeepersRobin Olsen (Malmö FF)Jacob Rinne (Djurgården)
    Saves3150
    Save %78%75%
    xG prevented68%51%
    Claims42 (96%)69 (91%)

    Frequently asked questions

    Who wins Malmö FF vs Djurgården according to our model?

    The model gives Malmö FF a 40% win probability. Full 1X2 picture: Malmö FF 40%, draw 25%, Djurgården 35%.

    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 58% and under at 42%.

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