Ligue 2Stade Gaston Gérard, Dijon10°14 km/h

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    DijonDijon
    vs
    MetzMetz
    The model's lean: 1 · Dijon (44%)

    Dijon vs Metz · Ligue 2

    1 · Dijon 44%X 28%28% Metz · 2

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    Analysis: Dijon – Metz

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

    Dijon’s 44% win probability casts them as favorites against Metz, yet the market offers an intriguing opportunity. The hosts have shown consistent form, reflected in their expected goals of 1.61 compared to the visitors' 1.05. With the most likely scorelines being 1-1 at 12% and 1-0 at 11%, the odds suggest a tight contest, but it leans heavily toward a home advantage.

    Metz, holding a 28% chance of securing a win, are on the backfoot according to these numbers. The expected goals disparity underscores the struggle they may face in dismantling a relatively solid Dijon defense. While the market may not fully grasp this imbalance, the model’s lean towards Dijon reflects confidence in their ability to edge out the visitors, possibly by a single goal margin.

    The anticipated 1-1 or 1-0 scorelines indicate a game that could hinge on fine margins. This setup doesn’t scream for an abundance of goals, with the over 2.5 goals sitting at a tepid 50%. The bookmakers are wary, pricing this as a coin flip, but the underlying metrics don’t suggest a high-scoring shootout.

    As for both teams to score, the 52% probability slightly tilts toward a mutual breakthrough, but it’s hardly a foregone conclusion. Given the expected goals and model probabilities, a cautious approach to goals might be prudent, tipping the scale toward a game that fails to breach the 2.5-goal mark.

    Where’s the value? The standout is backing Dijon to win at odds of 2.25 offered by Pinnacle. With the model probability leaning at 44%, there's a calculated edge here for those looking for a market oversight. A 1-0 or 2-1 home victory feels most plausible, underpinned by the data — a reflection of Dijon’s stronger position without overstating Metz’s challenge.

    DijonDijon
    Form DLDWW
    Key players
    • Adel LembezatLWxG 0.27 · xT 0.43
    • Alexis N'TamackFxG 0.11 · xT 0.02
    • Ismaïl BouleghchaRBxG 0.00 · xT 0.20
    MetzMetz
    Form DDWLD
    Key players
    • Jahyann PandoreFxG 0.02 · xT 0.16
    • Idris MohamedCMxG 0.05 · xT 0.04
    • Pape Moussa FallFxG 0.63 · xT -0.04

    Match prediction: Dijon – Metz

    Predicted score matrix

    Metz →
    Dijon →
    0
    1
    2
    3
    4+
    0
    0–07.4%
    0–17.0%
    0–23.9%
    0–31.4%
    0–4+0.4%
    1
    1–010.9%
    1–112.2%
    1–26.2%
    1–32.2%
    1–4+0.7%
    2
    2–09.1%
    2–19.5%
    2–25.0%
    2–31.7%
    2–4+0.6%
    3
    3–04.9%
    3–15.1%
    3–22.7%
    3–30.9%
    3–4+0.3%
    4+
    4+–02.8%
    4+–12.9%
    4+–21.5%
    4+–30.5%
    4+–4+0.2%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-112%
    2. 2.1-011%
    3. 3.2-110%
    4. 4.2-09%
    5. 5.0-07%
    Expected goals
    1,61–1,05
    Both teams to score
    52%

    Over/under goals

    Expected goals: 2,7
    Under 2,550%
    –
    Over 2,550%
    –

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    01 · 2 legs

    Safe

    • Double chance Dijon or draw (1X)76%
    • Under 3.5 goals72%

    Combined probability

    54%

    Fair odds

    1.86

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

    02 · 3 legs

    Balanced

    • Double chance Dijon or draw (1X)76%
    • Under 2.5 goals50%
    • Samy Olivier Chouchane to score24%

    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 score52%
    • Over 2.5 goals50%
    • Samy Olivier Chouchane to score24%
    • Jessy Deminguet to be booked25%

    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

    No odds available yet.

    Statistics

    xG & xGA per match — 3-game rolling average

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

    Dijon
    Metz
    When goals are scored and conceded — 2026
    Dijon (10–10)
    Metz (10–7)
    Pass networks

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

    Dijon
    Lenny Stéphane Lacroix: 278 passningar, xT 0.46LacroixQuentin Bernard: 260 passningar, xT 0.41BernardSamy Olivier Chouchane: 198 passningar, xT 0.5ChouchaneBrandon Nsimba Nsimba Ndezi: 171 passningar, xT 0.51NdeziJordan Marie: 170 passningar, xT 0.34MariePaul Delecroix: 152 passningar, xT 0.31DelecroixMoussa Faty: 130 passningar, xT 0.42FatyPaul Bellon: 125 passningar, xT 0.24BellonIsmaïl Bouleghcha: 108 passningar, xT 0.38BouleghchaBen Chayeel Hamada: 105 passningar, xT 0.06HamadaWaly Diouf: 95 passningar, xT 0.1Diouf
    Metz
    Cristian David Castro Devenish: 258 passningar, xT 0.26DevenishBouna Junior Sarr: 202 passningar, xT 0.15SarrTéji Tedy Savanier: 155 passningar, xT 1.08SavanierJessy Deminguet: 153 passningar, xT 0.95DeminguetJonathan Fischer: 148 passningar, xT 0.16FischerJean Ruiz: 132 passningar, xT 0.07RuizBelieve Munongo: 125 passningar, xT 0.13MunongoFlorian Jérémie Miguel: 123 passningar, xT 0.82MiguelGiorgi Abuashvili: 82 passningar, xT 0.57AbuashviliJahyann Pandore: 80 passningar, xT 0.58PandoreMichel Mboula: 80 passningar, xT 0.14Mboula
    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.

    Dijon
    Lenny Stéphane Lacroix: 278 passningar, xT 0.46LacroixQuentin Bernard: 260 passningar, xT 0.41BernardSamy Olivier Chouchane: 198 passningar, xT 0.5ChouchaneBrandon Nsimba Nsimba Ndezi: 171 passningar, xT 0.51NdeziJordan Marie: 170 passningar, xT 0.34MariePaul Delecroix: 152 passningar, xT 0.31DelecroixMoussa Faty: 130 passningar, xT 0.42FatyPaul Bellon: 125 passningar, xT 0.24BellonIsmaïl Bouleghcha: 108 passningar, xT 0.38BouleghchaBen Chayeel Hamada: 105 passningar, xT 0.06HamadaWaly Diouf: 95 passningar, xT 0.1Diouf
    Metz
    Cristian David Castro Devenish: 258 passningar, xT 0.26DevenishBouna Junior Sarr: 202 passningar, xT 0.15SarrTéji Tedy Savanier: 155 passningar, xT 1.08SavanierJessy Deminguet: 153 passningar, xT 0.95DeminguetJonathan Fischer: 148 passningar, xT 0.16FischerJean Ruiz: 132 passningar, xT 0.07RuizBelieve Munongo: 125 passningar, xT 0.13MunongoFlorian Jérémie Miguel: 123 passningar, xT 0.82MiguelGiorgi Abuashvili: 82 passningar, xT 0.57AbuashviliJahyann Pandore: 80 passningar, xT 0.58PandoreMichel Mboula: 80 passningar, xT 0.14Mboula
    The goalkeepersPaul Delecroix (Dijon)Jonathan Fischer (Metz)
    Saves2026
    Save %69%81%
    xG prevented48%50%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Dijon vs Metz according to our model?

    The model gives Dijon a 44% win probability. Full 1X2 picture: Dijon 44%, draw 28%, Metz 28%.

    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 50% and under at 50%.

    Will both teams score?

    The probability of both teams scoring is 52% 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.