Norwegian Eliteserien13°17 km/h

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    RosenborgRosenborgCounter-attacks & crosses
    40
    HamarkamerateneHamarkamerateneLow block & direct
    The model's lean: 1 · Rosenborg (59%)Best value by the model: 2 · Hamarkameratene @ 9.03 (+66 %)

    RosenborgHamarkameratene · Norwegian Eliteserien

    1 · Rosenborg 59%X 23%18% Hamarkameratene · 2

    Analysis: RosenborgHamarkameratene

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

    TEXT: Rosenborg's knack for scoring in the last eight league games sets the stage for a fascinating encounter against a Hamarkameratene side known for sturdy defensive tactics and direct play. With 59% win probability, the hosts are favored to extend their solid home form where they historically win 56% of matches. The visitors, with a mere 18% chance of victory, face a formidable challenge, especially given Rosenborg's attacking momentum.

    While the head-to-head record since 2021 shows Rosenborg with an upper hand, with three wins in four matches, the small sample size means recent form and expected goals carry more weight. Rosenborg's xG of 1.6 per match against Hamarkameratene's 1.3 suggests a slight offensive edge, while defensively, the hosts' xGA of 1.5 offers a tighter ship compared to the visitors' 1.7. These figures hint at a game where Rosenborg is poised to control the narrative, likely through counter-attacks and exploiting crosses.

    Goals seem likely, with the model suggesting a 62% chance of over 2.5 goals and a 59% probability of both teams finding the net. The most probable scorelines are 2-1 and 1-1, each at 10%, pointing to a narrow victory or a draw. However, Rosenborg’s ability to find net consistently positions them as the team to back, with a 2-1 scoreline appearing most plausible.

    Given the statistical lean towards goals and Rosenborg's attacking form, backing over 2.5 goals aligns well with the numbers. It's a dry play, grounded in a methodical analysis of current trends and expected match dynamics.

    RosenborgRosenborg
    Form WLWWL
    League ranking xG #6xGA #8xT #8xP/match #7Points #8
    Key players
    • Emil Konradsen CeideLWxG 0.18 · xT 0.19
    • Amin ChiakhaFxG 0.48 · xT 0.05
    • Iver FossumLWxG 0.21 · xT 0.14
    HamarkamerateneHamarkameratene
    Form LWDLD
    League ranking xG #13xGA #12xT #16xP/match #10Points #9
    Key players
    • Loris MettlerFxG 0.16 · xT 0.20
    • Markus JohnsgardFxG 0.37 · xT 0.02
    • Mame Alassane NiangFxG 0.31 · xT -0.04
    Final score
    40
    The model called the outcome
    Predicted probabilities: Rosenborg 59% · Draw 23% · Hamarkameratene 18%

    Match prediction: RosenborgHamarkameratene

    Predicted score matrix

    Hamarkameratene
    Rosenborg
    0
    1
    2
    3
    4+
    0
    0–04.4%
    0–14.2%
    0–22.5%
    0–30.9%
    0–4+0.3%
    1
    1–08.4%
    1–19.7%
    1–25.1%
    1–31.9%
    1–4+0.6%
    2
    2–09.1%
    2–19.9%
    2–25.4%
    2–32.0%
    2–4+0.7%
    3
    3–06.3%
    3–16.9%
    3–23.8%
    3–31.4%
    3–4+0.5%
    4+
    4+–05.4%
    4+–15.9%
    4+–23.2%
    4+–31.2%
    4+–4+0.4%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.2-110%
    2. 2.1-110%
    3. 3.2-09%
    4. 4.1-08%
    5. 5.3-17%
    Expected goals
    2,101,09
    Both teams to score
    59%

    Over/under goals

    Expected goals: 3,2
    Under 2,538%
    Over 2,562%

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Rosenborg to win59%
    • Over 1.5 goals83%

    Combined probability

    52%

    Fair odds

    1.93

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

    02 · 3 legs

    Balanced

    • Rosenborg to win59%
    • Over 2.5 goals62%
    • Amin Chiakha to score32%

    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 score59%
    • Over 2.5 goals62%
    • Amin Chiakha to score32%
    • Ethan Amundsen-Day 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+).

    • 2 · Hamarkameratene18% probability@9.03PinnacleEV+66%reference odds
    • X · Draw23% probability@5.89PinnacleEV+33%reference odds
    • Under 3.561% probability@1.72PinnacleEV+4%reference odds
    Bookmaker1 · RosenborgX2 · Hamarkameratene
    Pinnacle1.32
    EV+ 33%
    5.89
    EV+ 66%
    9.03

    Odds updated 5 Sept, 10:32

    Odds movement

    Market signal

    The market has moved clearly towards a Rosenborg win since 31 August — the odds have shortened from 1.40 to 1.32 (−6%).

    1-6 %
    75 %65 %

    1.401.32

    X+17 %
    23 %13 %

    5.035.89

    2+30 %
    17 %7 %

    6.939.03

    Pinnacle · 16 recorded price levels · 31/08/2026 → 05/09/2026 · fixed scale 10 percentage points

    Statistics

    Head-to-head

    4 matches
    Rosenborg 3Draw 0Hamarkameratene 1
    Goals: 54 (⌀ 2,2)

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

    Key facts

    • Rosenborg have scored in 8 consecutive league matches.
    • Rosenborg win 56% of their home matches all-time (39 played).
    xG & xGA per match — 3-game rolling average

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

    Rosenborg
    Hamarkameratene
    When goals are scored and conceded 2026
    Rosenborg (2726)
    Hamarkameratene (2632)
    Pass networks

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

    Rosenborg
    Tomas Nemcik: 282 passningar, xT 0.56NemcikOle Selnaes: 255 passningar, xT 0.83SelnaesMikkel Konradsen Ceide: 212 passningar, xT 0.2CeideAdrian Pereira: 187 passningar, xT 0.52PereiraMads Bomholt: 158 passningar, xT 0.85BomholtJonas Svensson: 153 passningar, xT 0.73SvenssonEmil Konradsen Ceide: 151 passningar, xT 0.86CeideAslak Fonn Witry: 93 passningar, xT 0.57WitryLeopold Wahlstedt: 70 passningar, xT 0.12WahlstedtIver Fossum: 66 passningar, xT 0.27FossumNoah Sahsah: 64 passningar, xT 0.3Sahsah
    Hamarkameratene
    Ethan Amundsen-Day: 259 passningar, xT 0.21Amundsen-DayLuc Mares: 207 passningar, xT 0.04MaresPatrick Metcalfe: 192 passningar, xT 0.76MetcalfeMartin Gjone: 190 passningar, xT 1.03GjoneFredrik Sjolstad: 186 passningar, xT 0.11SjolstadMarcus Sandberg: 172 passningar, xT 0.21SandbergAksel Baran Potur: 109 passningar, xT 0.33PoturSnorre Strand Nilsen: 90 passningar, xT 0.28NilsenAnders Trondsen: 80 passningar, xT 0.16TrondsenVidar Ari Jonsson: 79 passningar, xT -0.08JonssonAnton Ekeroth: 76 passningar, xT 0.08Ekeroth
    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.

    Rosenborg
    Tomas Nemcik: 282 passningar, xT 0.56NemcikOle Selnaes: 255 passningar, xT 0.83SelnaesMikkel Konradsen Ceide: 212 passningar, xT 0.2CeideAdrian Pereira: 187 passningar, xT 0.52PereiraMads Bomholt: 158 passningar, xT 0.85BomholtJonas Svensson: 153 passningar, xT 0.73SvenssonEmil Konradsen Ceide: 151 passningar, xT 0.86CeideAslak Fonn Witry: 93 passningar, xT 0.57WitryLeopold Wahlstedt: 70 passningar, xT 0.12WahlstedtIver Fossum: 66 passningar, xT 0.27FossumNoah Sahsah: 64 passningar, xT 0.3Sahsah
    Hamarkameratene
    Ethan Amundsen-Day: 259 passningar, xT 0.21Amundsen-DayLuc Mares: 207 passningar, xT 0.04MaresPatrick Metcalfe: 192 passningar, xT 0.76MetcalfeMartin Gjone: 190 passningar, xT 1.03GjoneFredrik Sjolstad: 186 passningar, xT 0.11SjolstadMarcus Sandberg: 172 passningar, xT 0.21SandbergAksel Baran Potur: 109 passningar, xT 0.33PoturSnorre Strand Nilsen: 90 passningar, xT 0.28NilsenAnders Trondsen: 80 passningar, xT 0.16TrondsenVidar Ari Jonsson: 79 passningar, xT -0.08JonssonAnton Ekeroth: 76 passningar, xT 0.08Ekeroth

    The teams in numbers

    PerformanceRosenborgHamarkameratene
    Points2423
    xPoints26.322.6
    xG per match1.61.3
    xGA per match1.51.7
    xG within 8s of winning the ball0.170.18
    xGA within 8s of losing the ball0.260.34
    Playing styleRosenborgHamarkameratene
    Build-up efficiency0.330.37
    Field tilt0.530.35
    xT per match1.10.84
    xTA per match1.21.3
    Won balls, offensive half2622
    Pressing intensity0.240.25
    Pressing efficiency0.30.24
    Pressing efficiency, offensive half0.280.24
    Entries into the box per match1411
    Entries into the box against1518
    Pass completion %0.770.77
    Pass completion % under pressure0.720.73
    Passes per match390370
    Passes against per match359425
    Switches of play per match20.926.7
    Long balls per match2634
    Set piecesRosenborgHamarkameratene
    xG from free kicks0.070.06
    Corners per match6.24.3
    Corners against per match6.25.5
    xG per corner0.020.03
    xGA per corner against0.050.03
    First touch, offensive corners %0.40.37
    First touch, defensive corners %0.610.59
    OtherRosenborgHamarkameratene
    Throw-in control0.70.69
    The goalkeepersLeopold Wahlstedt (Rosenborg)Marcus Sandberg (Hamarkameratene)
    Saves5664
    Save %68%69%
    xG prevented47%47%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Rosenborg vs Hamarkameratene according to our model?

    The model gives Rosenborg a 59% win probability. Full 1X2 picture: Rosenborg 59%, draw 23%, Hamarkameratene 18%.

    What is the most likely scoreline?

    The model's most likely final score is 2-1 at 10% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 62% and under at 38%.

    Will both teams score?

    The probability of both teams scoring is 59% 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.