Ligue 2Stade de la Mosson, Montpellier20°9 km/h

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    MontpellierMontpellier
    vs
    PauPau
    The model's lean: 1 · Montpellier (51%)Best value by the model: 2 · Pau @ 4.28 (+6 %)

    MontpellierPau · Ligue 2

    1 · Montpellier 51%X 24%25% Pau · 2

    Analysis: MontpellierPau

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

    A tight contest looms as Montpellier hosts Pau, with the model giving the home side a 51% chance of victory. Despite the hosts' edge in probability, a 1-1 draw is the most likely scoreline at 12%, followed closely by a narrow 1-0 win for Montpellier at 10%. These scenarios reflect the hosts' expected goals at 1.55 compared to Pau's 1.14, suggesting a closely contested battle rather than an easy ride for the favorites.

    Montpellier's recent history against Pau is hardly dominant, with only two encounters since 2023 producing a draw and a loss for the home team. Such a small head-to-head sample doesn't give substantial weight over current form and expected goals but does hint at Pau's potential to disrupt. The visitors have shown they can challenge Montpellier, which adds an unpredictable edge to this clash.

    The market is split on whether goals will flow, with a 50% chance of over 2.5 goals and a slightly higher 54% chance of both teams finding the net. This suggests value in exploring the both teams to score market, with the probabilities indicating a match that could see action at both ends. The expected goals back this up, pointing to opportunities for each side to find the back of the net.

    For those seeking value, Unibet offers odds of 3.80 for a 1-1 draw, which aligns well with the most likely scoreline prediction. With Montpellier not fully stamping their authority in their head-to-head record and Pau capable of holding their own, this outcome presents a viable betting angle. Keeping an eye on both sides' attacking efforts could pay off as the tension of a potential draw builds throughout the match.

    MontpellierMontpellier
    Form DWWDL
    Key players
    • Florian TardieuCAMxG 0.26 · xT 0.07
    • Nicolas PaysRWxG 0.15 · xT 0.12
    • Naoufel El HannachRWBxG 0.03 · xT 0.09
    PauPau
    Form LWLDD
    Key players
    • Babacar LeyeFxG 0.89 · xT -0.04
    • Joseph KaluluLWBxG 0.01 · xT 0.09
    • Hacène BenaliFxG 0.04 · xT -0.04

    Match prediction: MontpellierPau

    Predicted score matrix

    Pau
    Montpellier
    0
    1
    2
    3
    4+
    0
    0–07.2%
    0–17.4%
    0–24.4%
    0–31.7%
    0–4+0.6%
    1
    1–010.2%
    1–112.4%
    1–26.8%
    1–32.6%
    1–4+0.9%
    2
    2–08.2%
    2–19.3%
    2–25.3%
    2–32.0%
    2–4+0.7%
    3
    3–04.2%
    3–14.8%
    3–22.7%
    3–31.0%
    3–4+0.4%
    4+
    4+–02.3%
    4+–12.6%
    4+–21.5%
    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. 3.2-19%
    4. 4.2-08%
    5. 5.0-17%
    Expected goals
    1,551,14
    Both teams to score
    54%

    Over/under goals

    Expected goals: 2,7
    Under 2,550%
    @1.85
    Over 2,550%
    @2.01EV+1%

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Montpellier to win51%
    • Under 3.5 goals72%

    Combined probability

    32%

    Fair odds

    3.13

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

    02 · 3 legs

    Balanced

    • Montpellier to win51%
    • Over 2.5 goals50%
    • Lacine Megnan Pave to score34%

    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 goals50%
    • Lacine Megnan Pave to score34%
    • Luan Gadegbeku 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+).

    • 2 · Pau25% probability@4.28PinnacleEV+6%reference odds
    • Over 2.550% probability@2.01PinnacleEV+1%reference odds
    Bookmaker1 · MontpellierX2 · Pau
    Betsafe1.853.304.00
    Betsson1.853.304.00
    Nordicbet1.853.304.00
    Pinnacle1.873.60
    EV+ 6%
    4.28

    Odds updated 11 Sept, 10:21

    Odds movement

    Market signal

    The market has moved clearly towards under 2.5 goals since 6 September — the odds have shortened from 2.00 to 1.85 (−7%).

    1-4 %
    55 %45 %

    1.941.87

    X0 %
    31 %21 %

    3.593.60

    2+15 %
    29 %19 %

    3.724.28

    Over 2,5+11 %
    55 %45 %

    1.812.01

    Pinnacle · 15 recorded price levels · 06/09/2026 → 11/09/2026 · fixed scale 10 percentage points

    Statistics

    Head-to-head

    2 matches
    Montpellier 0Draw 1Pau 1
    Goals: 01 (⌀ 0,5)

    Head-to-head based on Ligue 2 data since 2023.

    xG & xGA per match — 3-game rolling average

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

    Montpellier
    Pau
    When goals are scored and conceded 2026
    Montpellier (44)
    Pau (45)
    Pass networks

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

    Montpellier
    Julien Laporte: 289 passningar, xT 0.31LaporteThéo Sainte-Luce: 217 passningar, xT 0.46Sainte-LuceSimon Ngapandouetnbu: 185 passningar, xT 0.08NgapandouetnbuYael Mouanga: 180 passningar, xT 0.13MouangaDaylam Meddah: 178 passningar, xT 0.15MeddahFlorian Tardieu: 160 passningar, xT 0.25TardieuNaoufel El Hannach: 126 passningar, xT 0.19HannachNicolas Pays: 99 passningar, xT 0.57PaysNordan Mukiele: 78 passningar, xT 0.65MukieleThéo Chennahi: 71 passningar, xT 0.17ChennahiNoah Vidal-Cartoux: 61 passningar, xT 0.32Vidal-Cartoux
    Pau
    Axel Dodote: 227 passningar, xT 0.43DodoteTom Pouilly: 218 passningar, xT 1.26PouillyGaëtan Paquiez: 211 passningar, xT 0.65PaquiezJessy Benet: 174 passningar, xT 0.51BenetAxel Bamba: 167 passningar, xT 0.15BambaBrice Maubleu: 109 passningar, xT 0.03MaubleuLorenzo Rajot: 85 passningar, xT 0.37RajotCheikh Fall: 84 passningar, xT 0.15FallJoseph Kalulu: 69 passningar, xT 0.1KaluluAnthony Briançon: 64 passningar, xT 0.36BriançonHacène Benali: 61 passningar, xT -0.26Benali
    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.

    Montpellier
    Julien Laporte: 289 passningar, xT 0.31LaporteThéo Sainte-Luce: 217 passningar, xT 0.46Sainte-LuceSimon Ngapandouetnbu: 185 passningar, xT 0.08NgapandouetnbuYael Mouanga: 180 passningar, xT 0.13MouangaDaylam Meddah: 178 passningar, xT 0.15MeddahFlorian Tardieu: 160 passningar, xT 0.25TardieuNaoufel El Hannach: 126 passningar, xT 0.19HannachNicolas Pays: 99 passningar, xT 0.57PaysNordan Mukiele: 78 passningar, xT 0.65MukieleThéo Chennahi: 71 passningar, xT 0.17ChennahiNoah Vidal-Cartoux: 61 passningar, xT 0.32Vidal-Cartoux
    Pau
    Axel Dodote: 227 passningar, xT 0.43DodoteTom Pouilly: 218 passningar, xT 1.26PouillyGaëtan Paquiez: 211 passningar, xT 0.65PaquiezJessy Benet: 174 passningar, xT 0.51BenetAxel Bamba: 167 passningar, xT 0.15BambaBrice Maubleu: 109 passningar, xT 0.03MaubleuLorenzo Rajot: 85 passningar, xT 0.37RajotCheikh Fall: 84 passningar, xT 0.15FallJoseph Kalulu: 69 passningar, xT 0.1KaluluAnthony Briançon: 64 passningar, xT 0.36BriançonHacène Benali: 61 passningar, xT -0.26Benali
    The goalkeepersSimon Ngapandouetnbu (Montpellier)Brice Maubleu (Pau)
    Saves2221
    Save %85%81%
    xG prevented74%52%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Frequently asked questions

    Who wins Montpellier vs Pau according to our model?

    The model gives Montpellier a 51% win probability. Full 1X2 picture: Montpellier 51%, draw 24%, Pau 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 50% and under at 50%.

    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.