Norwegian Eliteserien12°19 km/h

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    RosenborgRosenborgCounter-attacks & crosses
    vs
    TromsøTromsøPossession & high press
    The model's lean: 1 · Rosenborg (51%)Best value by the model: 2 · Tromsø @ 4.95 (+22 %)

    RosenborgTromsø · Norwegian Eliteserien

    1 · Rosenborg 51%X 24%25% Tromsø · 2

    Analysis: RosenborgTromsø

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

    Rosenborg's 57% home win record might make them look like favorites, but there's more to this matchup than meets the eye. While the model leans towards a home victory, giving Rosenborg a 51% chance of winning, Tromsø's form this season cannot be ignored, as they lead on points with 34 compared to the hosts' 27. The expected goals tell a slightly different story, with both teams averaging 1.7 xG per match. Yet, the edge in xPoints is with Rosenborg, suggesting they've been a bit unlucky or inefficient compared to Tromsø.

    Rosenborg's recent scoring streak—finding the net in nine consecutive league games—highlights their attacking potency, which might help them break down Tromsø's high press. However, Tromsø's strategy of possession and high pressing could disrupt Rosenborg’s rhythm, potentially leading to a tighter contest than expected. Despite the home advantage, Rosenborg’s defense, allowing 1.5 xGA per match, could be vulnerable to Tromsø's attacking phases.

    The goal probabilities hint at a close affair, with the most likely scorelines being 1-1 and either team edging it with a single-goal margin. The over 2.5 goals probability at 51% barely tips the scale, but the model sees both teams scoring as slightly more probable. Yet, the smart money might be elsewhere.

    Value hunters should note the odds suggesting value in betting on under 2.5 goals at 2.3 with Nordicbet, as the model calculates a 49% chance of that outcome, offering a 12% edge. Moreover, the away win at odds 4.5 with Betsson also presents a significant edge of 11% according to the model. While the hosts may have the edge in several metrics, Tromsø's value and form make them a tempting outsider bet.

    RosenborgRosenborg
    Form LWWLW
    League ranking xG #6xGA #8xT #8xP/match #7Points #6
    Key players
    • Emil Konradsen CeideLWxG 0.18 · xT 0.19
    • Amin ChiakhaFxG 0.51 · xT 0.05
    • Iver FossumLWxG 0.21 · xT 0.14
    TromsøTromsø
    Form LDL
    League ranking xG #5xGA #4xT #5xP/match #5Points #3
    Key players
    • Daniel BrautFxG 0.54 · xT -0.02
    • Abubacarr Sedi KintehCBxG 0.04 · xT 0.21
    • Heine Asen LarsenFxG 0.52 · xT 0.04

    Match prediction: RosenborgTromsø

    Predicted score matrix

    Tromsø
    Rosenborg
    0
    1
    2
    3
    4+
    0
    0–06.9%
    0–16.9%
    0–23.9%
    0–31.4%
    0–4+0.5%
    1
    1–010.4%
    1–112.1%
    1–26.4%
    1–32.3%
    1–4+0.8%
    2
    2–08.7%
    2–19.5%
    2–25.2%
    2–31.9%
    2–4+0.7%
    3
    3–04.7%
    3–15.2%
    3–22.8%
    3–31.0%
    3–4+0.4%
    4+
    4+–02.8%
    4+–13.0%
    4+–21.6%
    4+–30.6%
    4+–4+0.2%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-112%
    2. 2.1-010%
    3. 3.2-110%
    4. 4.2-09%
    5. 5.0-07%
    Expected goals
    1,631,09
    Both teams to score
    54%

    Over/under goals

    Expected goals: 2,7
    Under 2,549%
    @2.30EV+10%
    Over 2,551%
    @1.62

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Rosenborg to win51%
    • Over 1.5 goals76%

    Combined probability

    39%

    Fair odds

    2.57

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

    02 · 3 legs

    Balanced

    • Rosenborg to win51%
    • Over 2.5 goals51%
    • Amin Chiakha to score29%

    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 score54%
    • Over 2.5 goals51%
    • Amin Chiakha to score29%
    • David Mikael Edvardsson to be booked26%

    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 · Tromsø25% probability@4.95BetssonEV+22%reference odds
    • 2 · Tromsø25% probability@4.95NordicbetEV+22%reference odds
    • 2 · Tromsø25% probability@4.90BetsafeEV+21%reference odds
    Bookmaker1 · RosenborgX2 · Tromsø
    Betsafe1.753.65
    EV+ 21%
    4.90
    Betsson1.753.65
    EV+ 22%
    4.95
    Nordicbet1.753.65
    EV+ 22%
    4.95
    Pinnacle1.69
    EV+ 3%
    4.21
    EV+ 17%
    4.76

    Odds updated 11 Sept, 16:38

    Odds movement

    Market signal

    The market has moved clearly towards a Rosenborg win since 7 September — the odds have shortened from 1.78 to 1.69 (−5%).

    1-5 %
    57 %52 %

    1.781.69

    X+7 %
    26 %21 %

    3.944.21

    2+12 %
    24 %19 %

    4.244.76

    Pinnacle · 12 recorded price levels · 07/09/2026 → 11/09/2026 · fixed scale 5 percentage points

    Statistics

    Key facts

    • Rosenborg have scored in 9 consecutive league matches.
    • Rosenborg win 57% of their home matches all-time (40 played).
    xG & xGA per match — 3-game rolling average

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

    Rosenborg
    Tromsø
    When goals are scored and conceded 2026
    Rosenborg (3126)
    Tromsø (3217)
    Pass networks

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

    Rosenborg
    Tomas Nemcik: 277 passningar, xT 0.55NemcikOle Selnaes: 264 passningar, xT 1.09SelnaesMikkel Konradsen Ceide: 214 passningar, xT 0.2CeideAdrian Pereira: 191 passningar, xT 0.48PereiraEmil Konradsen Ceide: 178 passningar, xT 0.96CeideMads Bomholt: 159 passningar, xT 0.92BomholtAslak Fonn Witry: 114 passningar, xT 0.57WitryJonas Svensson: 112 passningar, xT 0.56SvenssonNoah Sahsah: 81 passningar, xT 0.28SahsahLeopold Wahlstedt: 70 passningar, xT 0.12WahlstedtSimen Bolkan Nordli: 65 passningar, xT -0.03Nordli
    Tromsø
    Leon Hien: 201 passningar, xT 0.19HienIsak Vadebu: 192 passningar, xT 0.43VadebuAlexander Rickard Chadchai Thongla-Iad Warneryd: 132 passningar, xT 0.08WarnerydDavid Edvardsson: 126 passningar, xT 0.12EdvardssonSander Havik Innvaer: 98 passningar, xT 0.15InnvaerVince Chijioke Osuji: 88 passningar, xT 0.12OsujiJakob Haugaard: 80 passningar, xT 0.21HaugaardRuben Yttergard Jenssen: 77 passningar, xT 0.34JenssenTroy Engseth Nyhammer: 74 passningar, xT 0.54NyhammerMathias Tonnessen: 52 passningar, xT 0.26TonnessenHeine Asen Larsen: 48 passningar, xT -0.08Larsen
    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: 277 passningar, xT 0.55NemcikOle Selnaes: 264 passningar, xT 1.09SelnaesMikkel Konradsen Ceide: 214 passningar, xT 0.2CeideAdrian Pereira: 191 passningar, xT 0.48PereiraEmil Konradsen Ceide: 178 passningar, xT 0.96CeideMads Bomholt: 159 passningar, xT 0.92BomholtAslak Fonn Witry: 114 passningar, xT 0.57WitryJonas Svensson: 112 passningar, xT 0.56SvenssonNoah Sahsah: 81 passningar, xT 0.28SahsahLeopold Wahlstedt: 70 passningar, xT 0.12WahlstedtSimen Bolkan Nordli: 65 passningar, xT -0.03Nordli
    Tromsø
    Leon Hien: 201 passningar, xT 0.19HienIsak Vadebu: 192 passningar, xT 0.43VadebuAlexander Rickard Chadchai Thongla-Iad Warneryd: 132 passningar, xT 0.08WarnerydDavid Edvardsson: 126 passningar, xT 0.12EdvardssonSander Havik Innvaer: 98 passningar, xT 0.15InnvaerVince Chijioke Osuji: 88 passningar, xT 0.12OsujiJakob Haugaard: 80 passningar, xT 0.21HaugaardRuben Yttergard Jenssen: 77 passningar, xT 0.34JenssenTroy Engseth Nyhammer: 74 passningar, xT 0.54NyhammerMathias Tonnessen: 52 passningar, xT 0.26TonnessenHeine Asen Larsen: 48 passningar, xT -0.08Larsen

    The teams in numbers

    PerformanceRosenborgTromsø
    Points2734
    xPoints28.324.5
    xG per match1.71.7
    xGA per match1.51.4
    xG within 8s of winning the ball0.170.37
    xGA within 8s of losing the ball0.250.21
    Playing styleRosenborgTromsø
    Build-up efficiency0.330.33
    Field tilt0.550.49
    xT per match1.11.2
    xTA per match1.11.1
    Won balls, offensive half2726
    Pressing intensity0.240.23
    Pressing efficiency0.30.24
    Pressing efficiency, offensive half0.280.23
    Entries into the box per match1416
    Entries into the box against1513
    Pass completion %0.770.8
    Pass completion % under pressure0.720.76
    Passes per match399427
    Passes against per match354432
    Switches of play per match2123.3
    Long balls per match2742
    Set piecesRosenborgTromsø
    xG from free kicks0.060.07
    Corners per match6.25.6
    Corners against per match6.14.5
    xG per corner0.030.06
    xGA per corner against0.050.04
    First touch, offensive corners %0.420.36
    First touch, defensive corners %0.610.55
    OtherRosenborgTromsø
    Throw-in control0.70.75
    The goalkeepersLeopold Wahlstedt (Rosenborg)Jakob Haugaard (Tromsø)
    Saves583
    Save %69%60%
    xG prevented49%33%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Rosenborg vs Tromsø according to our model?

    The model gives Rosenborg a 51% win probability. Full 1X2 picture: Rosenborg 51%, draw 24%, Tromsø 25%.

    What is the most likely scoreline?

    The model's most likely final score is 1-1 at 12% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 51% and under at 49%.

    Will both teams score?

    The probability of both teams scoring is 54% 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.