J1 LeagueMachida GION Stadium, Machida15°10 km/h

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    Machida ZelviaMachida ZelviaBalanced & physical
    vs
    Gamba OsakaGamba OsakaPossession control
    The model's lean: 1 · Machida Zelvia (63%)

    Machida Zelvia vs Gamba Osaka · J1 League

    1 · Machida Zelvia 63%X 20%16% Gamba Osaka · 2

    Prediction summary

    BetBuilders AI model prediction for Machida Zelvia vs Gamba Osaka (J1 League, Sunday, 1 November 2026): Machida Zelvia win 63%, draw 20%, Gamba Osaka win 16%. Expected goals (xG): Machida Zelvia 2.16, Gamba Osaka 0.94. Most likely score: 2-0 (11%). Over 2.5 goals 60%, both teams to score 54%. Double chance: Machida Zelvia or draw 84%, Gamba Osaka or draw 37%. Prediction updated Friday, 23 October 2026.

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    Analysis: Machida Zelvia – Gamba Osaka

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

    63% is the number that matters: Machida Zelvia are clear home favourites against Gamba Osaka. The model has it 2.16 expected goals to 0.94, while the 27–11 points gap is backed by 21.5–12.0 xPoints. The hosts’ balanced, physical game should carry more weight than the visitors’ possession control.

    Machida produce 1.9 xG per match and concede 1.0; Gamba post 1.2 and allow 1.7. Tråkiga, well-supported plays pay the bills. The analysis points plainly to a home win, with 2-0 the most likely scoreline at 11%, ahead of 2-1 at 10% and 1-0 at 9%. Over 2.5 goals has the lean at 60%.

    The head-to-head since 2023 reads 3W 0D 0L for the hosts, but three matches is a small sample and weighs less than form and expected goals. The value assessment is home at 1.769 with LeoVegas, rated 63% by the model for a 12% edge; 1.75 at Betsafe and Nordicbet rates as a 10% edge. Machida at 1.769 with LeoVegas is the sharpest angle.

    Machida ZelviaMachida Zelvia
    Form LWWWD
    League ranking xG #3xGA #4xT #4xP/match #3Points #1
    Key players
    • Daihachi OkamuraCBxG 0.09 · xT 0.04
    • Hiroyuki MaeCDMxG 0.03 · xT 0.08
    • Gen ShojiCBxG 0.01 · xT 0.07
    Gamba OsakaGamba Osaka
    Form LLDWD
    League ranking xG #11xGA #19xT #14xP/match #20Points #15
    Key players
    • Takashi UsamiCAMxG 0.06 · xT 0.26
    • Takeru KishimotoRBxG 0.04 · xT 0.11
    • Shinnosuke NakataniCBxG 0.02 · xT 0.09

    Match prediction: Machida Zelvia – Gamba Osaka

    Predicted score matrix

    Gamba Osaka →
    Machida Zelvia →
    0
    1
    2
    3
    4+
    0
    0–04.8%
    0–14.0%
    0–22.0%
    0–30.6%
    0–4+0.2%
    1
    1–09.5%
    1–19.4%
    1–24.3%
    1–31.3%
    1–4+0.4%
    2
    2–010.5%
    2–19.9%
    2–24.6%
    2–31.4%
    2–4+0.4%
    3
    3–07.6%
    3–17.1%
    3–23.3%
    3–31.0%
    3–4+0.3%
    4+
    4+–06.8%
    4+–16.4%
    4+–23.0%
    4+–30.9%
    4+–4+0.3%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.2-011%
    2. 2.2-110%
    3. 3.1-09%
    4. 4.1-19%
    5. 5.3-08%
    Expected goals
    2,16–0,94
    Both teams to score
    54%

    Over/under goals

    Expected goals: 3,1
    Under 2,540%
    @1.95
    Over 2,560%
    @1.78EV+7%

    Ready-made bet suggestions

    More combos & build your own →

    01 · 2 legs

    Safe

    • Machida Zelvia to win63%
    • Over 1.5 goals82%

    Combined probability

    56%

    Fair odds

    1.80

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

    02 · 3 legs

    Balanced

    • Machida Zelvia to win63%
    • Over 2.5 goals60%
    • Yusuke Matsuo 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 goals60%
    • Yusuke Matsuo to score29%
    • Shuto Abe 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+).

    • 1 · Machida Zelvia63% probability@1.77LeoVegasEV+12%reference odds
    • 1 · Machida Zelvia63% probability@1.75BetsafeEV+10%reference odds
    • 1 · Machida Zelvia63% probability@1.75NordicbetEV+10%reference odds
    Bookmaker1 · Machida ZelviaX2 · Gamba Osaka
    Betsafe
    EV+ 10%
    1.75    		3.504.20
    LeoVegas
    EV+ 12%
    1.77    		3.604.10
    Nordicbet
    EV+ 10%
    1.75    		3.504.20

    Odds updated 26 Oct, 13:36

    Odds movement

    1+2 %
    55 %50 %

    1.73 → 1.77

    X-4 %
    28 %23 %

    3.75 → 3.60

    20 %
    25 %20 %

    4.10 → 4.10

    Over 2,5+4 %
    56 %51 %

    1.70 → 1.77

    LeoVegas · 5 recorded price levels · 25/10/2026 → 26/10/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    3 matches
    Machida Zelvia 3Draw 0Gamba Osaka 0
    Goals: 7–2 (⌀ 3)

    Head-to-head based on J1 League data since 2023.

    xG & xGA per match — 3-game rolling average

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

    Machida Zelvia
    Gamba Osaka
    When goals are scored and conceded — 2026
    Machida Zelvia (30–10)
    Gamba Osaka (14–21)
    Pass networks

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

    Machida Zelvia
    Thomas Ouwejan: 245 passningar, xT 1.12OuwejanHiroyuki Mae: 223 passningar, xT 0.21MaeDaihachi Okamura: 218 passningar, xT 0.17OkamuraGen Shoji: 212 passningar, xT 0.45ShojiYuki Soma: 163 passningar, xT 0.94SomaNeta Lavi: 142 passningar, xT 0.14LaviTakahiro Akimoto: 139 passningar, xT 1.23AkimotoKosei Tani: 115 passningar, xT 0.22TaniHenry Heroki Mochizuki: 85 passningar, xT 0.87MochizukiRyohei Shirasaki: 65 passningar, xT -0.02ShirasakiKoki Ogawa: 62 passningar, xT -0.18Ogawa
    Gamba Osaka
    Shinnosuke Nakatani: 206 passningar, xT 0.34NakataniShuto Abe: 206 passningar, xT 0.44AbeShota Fukuoka: 165 passningar, xT 0.19FukuokaTakashi Usami: 141 passningar, xT 0.94UsamiSoya Fujiwara: 122 passningar, xT 0.52FujiwaraRyo Hatsuse: 120 passningar, xT 0.41HatsuseRyoya Yamashita: 114 passningar, xT 0.67YamashitaTakeru Kishimoto: 99 passningar, xT 0.37KishimotoRin Mito: 94 passningar, xT 0.06MitoShinya Nakano: 79 passningar, xT 0.37NakanoJun Ichimori: 74 passningar, xT 0.07Ichimori
    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.

    Machida Zelvia
    Thomas Ouwejan: 245 passningar, xT 1.12OuwejanHiroyuki Mae: 223 passningar, xT 0.21MaeDaihachi Okamura: 218 passningar, xT 0.17OkamuraGen Shoji: 212 passningar, xT 0.45ShojiYuki Soma: 163 passningar, xT 0.94SomaNeta Lavi: 142 passningar, xT 0.14LaviTakahiro Akimoto: 139 passningar, xT 1.23AkimotoKosei Tani: 115 passningar, xT 0.22TaniHenry Heroki Mochizuki: 85 passningar, xT 0.87MochizukiRyohei Shirasaki: 65 passningar, xT -0.02ShirasakiKoki Ogawa: 62 passningar, xT -0.18Ogawa
    Gamba Osaka
    Shinnosuke Nakatani: 206 passningar, xT 0.34NakataniShuto Abe: 206 passningar, xT 0.44AbeShota Fukuoka: 165 passningar, xT 0.19FukuokaTakashi Usami: 141 passningar, xT 0.94UsamiSoya Fujiwara: 122 passningar, xT 0.52FujiwaraRyo Hatsuse: 120 passningar, xT 0.41HatsuseRyoya Yamashita: 114 passningar, xT 0.67YamashitaTakeru Kishimoto: 99 passningar, xT 0.37KishimotoRin Mito: 94 passningar, xT 0.06MitoShinya Nakano: 79 passningar, xT 0.37NakanoJun Ichimori: 74 passningar, xT 0.07Ichimori

    The teams in numbers

    PerformanceMachida ZelviaGamba Osaka
    Points2711
    xPoints21.512
    xG per match1.91.2
    xGA per match11.7
    xG within 8s of winning the ball0.250.21
    xGA within 8s of losing the ball0.110.35
    Playing styleMachida ZelviaGamba Osaka
    Build-up efficiency0.350.31
    Field tilt0.490.54
    xT per match1.40.93
    xTA per match0.911.2
    Won balls, offensive half2725
    Pressing intensity0.230.24
    Pressing efficiency0.30.32
    Pressing efficiency, offensive half0.280.32
    Entries into the box per match1412
    Entries into the box against1215
    Pass completion %0.760.76
    Pass completion % under pressure0.740.71
    Passes per match376380
    Passes against per match362293
    Switches of play per match19.124.4
    Long balls per match2930
    Set piecesMachida ZelviaGamba Osaka
    xG from free kicks0.040.12
    Corners per match4.24.6
    Corners against per match4.35.7
    xG per corner0.050.02
    xGA per corner against0.040.04
    First touch, offensive corners %0.240.27
    First touch, defensive corners %0.460.68
    OtherMachida ZelviaGamba Osaka
    Throw-in control0.740.74
    The goalkeepersKosei Tani (Machida Zelvia)Jun Ichimori (Gamba Osaka)
    Saves3328
    Save %79%68%
    xG prevented58%57%
    Claims0 (0%)0 (0%)

    Teams & more matches this round

    Machida Zelvia
    Fixtures, form & tips
    Gamba Osaka
    Fixtures, form & tips

    Frequently asked questions

    Who wins Machida Zelvia vs Gamba Osaka according to our model?

    The model gives Machida Zelvia a 63% win probability. Full 1X2 picture: Machida Zelvia 63%, draw 20%, Gamba Osaka 16%.

    What is the most likely scoreline?

    The model's most likely final score is 2-0 at 11% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 60% and under at 40%.

    Will both teams score?

    The probability of both teams scoring is 54% according to the model.

    How many goals are expected in Machida Zelvia vs Gamba Osaka?

    The model expects 2.16 goals (xG) for Machida Zelvia and 0.94 for Gamba Osaka, 3.10 in total.

    What does the model say about double chance?

    Machida Zelvia or draw (1X) 84%, Gamba Osaka or draw (X2) 37% and no draw (12) 80%.

    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.