Ligue 1Stade Louis II, Monaco23°13 km/h

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    MonacoMonacoLow block & direct
    vs
    LensLensBalanced & physical
    The model's lean: 1 · Monaco (46%)Best value by the model: Under 2,5 @ 2.56 (+16 %)

    MonacoLens · Ligue 1

    1 · Monaco 46%X 25%29% Lens · 2

    Analysis: MonacoLens

    Anna Karlsson · · A data-driven preview · How the predictions work

    TEXT:

    Monaco's recent surge in form, marked by three consecutive victories, sets the stage for an intriguing clash against Lens. With a 46% chance of victory according to model probabilities, the home side is favored to edge this encounter. However, the numbers suggest a tight contest. Lens may have the upper hand in head-to-head encounters with two wins in the last four matches, but this small sample size is less significant than Monaco's current form and tactical approach.

    Monaco's attacking strategy, best described as low defense and direct, is complemented by their impressive record at home, winning 66% of their matches on familiar turf. Yet, their expected goals of 1.54 against Lens' 1.32 suggest a narrow margin. The visitors are no pushovers, thriving on a balanced and physical style, and this season they’ve generated more xG per match (2.4) compared to Monaco’s 1.2. This imbalance hints at a high-stakes chess match, where each side will look to exploit the other's vulnerabilities.

    With both teams boasting strong attacking potential, the model reflects a 55% probability of over 2.5 goals and a 58% chance that both teams will find the net. The most likely scorelines indicate a close affair, with a 1-1 draw as the most probable outcome at 12%. Yet, a 2-1 victory for the hosts is not far behind at 9%, reflecting Monaco's slight ascendancy in the model's eyes.

    MonacoMonaco
    Form LLWWW
    League ranking xG #16xGA #11xT #15xP/match #8Points #1
    Key players
    • Lamine CamaraCMxG 0.01 · xT -0.01
    • Paris BrunnerFxG 0.71 · xT -0.06
    • Stanis IdumboLWxG 0.29 · xT 0.07
    LensLens
    Form LWWLL
    League ranking xG #2xGA #7xT #2xP/match #3Points #10
    Key players
    • Florian Tristán Mariano ThauvinRWxG 0.85 · xT 0.47
    • Abdallah SimaFxG 0.16 · xT 0.04
    • Franjo IvanovićLWxG 0.29 · xT 0.27

    Match prediction: MonacoLens

    Predicted score matrix

    Lens
    Monaco
    0
    1
    2
    3
    4+
    0
    0–06.0%
    0–17.2%
    0–25.0%
    0–32.2%
    0–4+1.0%
    1
    1–08.5%
    1–112.0%
    1–27.7%
    1–33.4%
    1–4+1.5%
    2
    2–06.8%
    2–19.0%
    2–25.9%
    2–32.6%
    2–4+1.1%
    3
    3–03.5%
    3–14.6%
    3–23.0%
    3–31.3%
    3–4+0.6%
    4+
    4+–01.9%
    4+–12.5%
    4+–21.7%
    4+–30.7%
    4+–4+0.3%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-112%
    2. 2.2-19%
    3. 3.1-08%
    4. 4.1-28%
    5. 5.0-17%
    Expected goals
    1,541,32
    Both teams to score
    58%

    Over/under goals

    Expected goals: 2,9
    Under 2,545%
    @2.56EV+16%
    Over 2,555%
    @1.52

    Ready-made bet suggestions

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    01 · 2 legs

    Safe

    • Monaco to win46%
    • Over 1.5 goals78%

    Combined probability

    34%

    Fair odds

    2.96

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

    02 · 3 legs

    Balanced

    • Monaco to win46%
    • Over 2.5 goals55%
    • Maghnes Akliouche to score27%

    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 score58%
    • Over 2.5 goals55%
    • Maghnes Akliouche to score27%
    • Pierre-Ismaëlo Ganiou 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+).

    • Under 2.545% probability@2.56BetsafeEV+16%reference odds
    • Under 2.545% probability@2.56BetssonEV+16%reference odds
    • Under 2.545% probability@2.56NordicbetEV+16%reference odds
    Bookmaker1 · MonacoX2 · Lens
    Betsafe
    EV+ 5%
    2.30
    3.602.85
    Betsson
    EV+ 5%
    2.30
    3.602.85
    Nordicbet
    EV+ 5%
    2.30
    3.602.85

    Odds updated 11 Sept, 07:38

    Statistics

    Head-to-head

    4 matches
    Monaco 1Draw 1Lens 2
    Goals: 511 (⌀ 4)

    Head-to-head based on Ligue 1 data since 2022.

    Key facts

    • Monaco come into this round on 3 straight wins.
    • Monaco win 66% of their home matches all-time (35 played).
    xG & xGA per match — 3-game rolling average

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

    Monaco
    Lens
    When goals are scored and conceded 2026
    Monaco (51)
    Lens (65)
    Pass networks

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

    Monaco
    Lamine Camara: 149 passningar, xT -0.01CamaraSadibou Sané: 112 passningar, xT 0.16SanéEric Dier: 112 passningar, xT 0.15DierFlávio Basilua Jacinto Nazinho: 99 passningar, xT 0.19NazinhoVanderson de Oliveira Campos: 97 passningar, xT 0.23CamposDenis Zakaria: 84 passningar, xT 0.03ZakariaMamadou Coulibaly: 71 passningar, xT 0.13CoulibalyLukas Hradecky: 68 passningar, xT 0.11HradeckyStanis Idumbo: 57 passningar, xT 0.17IdumboAleksandr Golovin: 51 passningar, xT 0.48GolovinParis Brunner: 25 passningar, xT -0.08Brunner
    Lens
    Ismaelo Ganiou: 160 passningar, xT 0.52GaniouYassine Mohammed Titraoui: 147 passningar, xT 0.11TitraouiSouleymane Sagnan: 140 passningar, xT 0.24SagnanFlorian Tristán Mariano Thauvin: 108 passningar, xT 1.38ThauvinMichał Krzysztof Skóraś: 106 passningar, xT 0.88SkóraśRobin Risser: 92 passningar, xT 0.06RisserMaik Nawrocki: 80 passningar, xT 0.11NawrockiMichaël Bruno Dominique Cuisance: 65 passningar, xT 0.02CuisanceMatthieu Udol: 63 passningar, xT 0.25UdolRuben Aguilar: 60 passningar, xT 0.36AguilarKyllian Anderson Antonio: 59 passningar, xT 0.14Antonio
    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.

    Monaco
    Lamine Camara: 149 passningar, xT -0.01CamaraSadibou Sané: 112 passningar, xT 0.16SanéEric Dier: 112 passningar, xT 0.15DierFlávio Basilua Jacinto Nazinho: 99 passningar, xT 0.19NazinhoVanderson de Oliveira Campos: 97 passningar, xT 0.23CamposDenis Zakaria: 84 passningar, xT 0.03ZakariaMamadou Coulibaly: 71 passningar, xT 0.13CoulibalyLukas Hradecky: 68 passningar, xT 0.11HradeckyStanis Idumbo: 57 passningar, xT 0.17IdumboAleksandr Golovin: 51 passningar, xT 0.48GolovinParis Brunner: 25 passningar, xT -0.08Brunner
    Lens
    Ismaelo Ganiou: 160 passningar, xT 0.52GaniouYassine Mohammed Titraoui: 147 passningar, xT 0.11TitraouiSouleymane Sagnan: 140 passningar, xT 0.24SagnanFlorian Tristán Mariano Thauvin: 108 passningar, xT 1.38ThauvinMichał Krzysztof Skóraś: 106 passningar, xT 0.88SkóraśRobin Risser: 92 passningar, xT 0.06RisserMaik Nawrocki: 80 passningar, xT 0.11NawrockiMichaël Bruno Dominique Cuisance: 65 passningar, xT 0.02CuisanceMatthieu Udol: 63 passningar, xT 0.25UdolRuben Aguilar: 60 passningar, xT 0.36AguilarKyllian Anderson Antonio: 59 passningar, xT 0.14Antonio

    The teams in numbers

    PerformanceMonacoLens
    Points93
    xPoints4.35.4
    xG per match1.22.4
    xGA per match1.61.4
    xG within 8s of winning the ball0.170.44
    xGA within 8s of losing the ball0.190.33
    Playing styleMonacoLens
    Build-up efficiency0.30.29
    Field tilt0.30.58
    xT per match0.731.7
    xTA per match1.20.98
    Won balls, offensive half2725
    Pressing intensity0.240.24
    Pressing efficiency0.230.28
    Pressing efficiency, offensive half0.190.25
    Entries into the box per match1117
    Entries into the box against1614
    Pass completion %0.780.82
    Pass completion % under pressure0.710.76
    Passes per match321431
    Passes against per match542373
    Switches of play per match21.232.2
    Long balls per match3134
    Set piecesMonacoLens
    xG from free kicks0.10
    Corners per match35.9
    Corners against per match6.73.3
    xG per corner0.020.02
    xGA per corner against0.030
    First touch, offensive corners %0.330.39
    First touch, defensive corners %0.80.5
    OtherMonacoLens
    Throw-in control0.680.72
    The goalkeepersLukas Hradecky (Monaco)Robin Risser (Lens)
    Saves149
    Save %93%64%
    xG prevented76%28%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Monaco vs Lens according to our model?

    The model gives Monaco a 46% win probability. Full 1X2 picture: Monaco 46%, draw 25%, Lens 29%.

    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 55% and under at 45%.

    Will both teams score?

    The probability of both teams scoring is 58% 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.