Eerste Divisie16°11 km/h

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    Jong PSVJong PSVPossession & high press
    vs
    TOP OssTOP OssLow block & direct
    The model's lean: 1 · Jong PSV (53%)Best value by the model: 2 · TOP Oss @ 4.40 (+10 %)

    Jong PSVTOP Oss · Eerste Divisie

    1 · Jong PSV 53%X 22%25% TOP Oss · 2

    Analysis: Jong PSVTOP Oss

    Marcus Johansson · · Analysis from the match model · How the predictions work

    Four matches, two wins, two draws; that's the head-to-head tally since 2023 between PSV U21 and TOP Oss. A small sample, yet it hints at a trend, but the real intrigue lies elsewhere. PSV U21's playing style, a possession-heavy and high-press dynamism, stands in stark contrast to TOP Oss's low-block, direct approach. Such stylistic opposition often spells tactical fireworks rather than stalemate.

    PSV U21 have claimed three points from their few outings, a modest tally but one that eclipses TOP Oss's empty pocket. Expected goals reveal a deeper narrative: PSV U21 command a healthier xG at 2.1 per match compared to TOP Oss's 1.5, and their xGA at 0.65 is markedly superior to the visitors’ 2.0. The numbers not only highlight PSV U21’s structural advantage but also underscore a defensive solidity that TOP Oss sorely lacks.

    A 53% probability leans in favour of a PSV U21 victory, with the model's most probable scorelines echoing a narrow win — either 2-1 or 2-0 looms large at 10% and 9% likelihoods, respectively. While a 1-1 draw is equally probable at 10%, it seems less compelling given PSV U21's evident edge across most metrics. Still, with a 61% chance of seeing over 2.5 goals and a 59% probability that both sides will find the net, goals appear to be on the menu, though perhaps not in abundance.

    PSV U21 enters this fixture with the wind in their sails, literally and figuratively. Should the winds rise, as forecasted, it might just temper the scoring potential slightly, though not enough to derail the goal-happy expectations. With bookmaker value emerging on PSV U21 at 2.10 odds as an EV+ bet, it seems the sharpest angle to back. In a clash of strategy and spirit, PSV U21 appears poised to outplay and outscore their opposition.

    Jong PSVJong PSV
    Form WLLWL
    League ranking xG #3xGA #2xT #8xP/match #3Points #5
    Key players
    • Fabio KluitLWxG 0.72 · xT -0.03
    • Jordy BawuahCDMxG 0.15 · xT 0.06
    • Essien BasseyRBxG 0.08 · xT 0.20
    TOP OssTOP Oss
    Form WWWLL
    League ranking xG #9xGA #17xT #17xP/match #6Points #21
    Key players
    • Franslyn NsingiFxG 0.50 · xT -0.02
    • Mauresmo Johannes Jacob Danny Silvinho HinokeLWxG 0.15 · xT -0.01
    • Marcelencio EsajasCMxG 0.00 · xT 0.03

    Match prediction: Jong PSVTOP Oss

    Predicted score matrix

    TOP Oss
    Jong PSV
    0
    1
    2
    3
    4+
    0
    0–04.6%
    0–14.6%
    0–22.8%
    0–31.1%
    0–4+0.4%
    1
    1–08.3%
    1–110.1%
    1–25.6%
    1–32.1%
    1–4+0.8%
    2
    2–08.7%
    2–19.9%
    2–25.6%
    2–32.1%
    2–4+0.8%
    3
    3–05.8%
    3–16.6%
    3–23.8%
    3–31.4%
    3–4+0.5%
    4+
    4+–04.7%
    4+–15.3%
    4+–23.0%
    4+–31.1%
    4+–4+0.4%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-110%
    2. 2.2-110%
    3. 3.2-09%
    4. 4.1-08%
    5. 5.3-17%
    Expected goals
    2,011,14
    Both teams to score
    59%

    Over/under goals

    Expected goals: 3,2
    Under 2,539%
    @2.75EV+7%
    Over 2,561%
    @1.43

    Ready-made bet suggestions

    More combos & build your own

    01 · 2 legs

    Safe

    • Jong PSV to win53%
    • Over 1.5 goals83%

    Combined probability

    49%

    Fair odds

    2.05

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

    02 · 3 legs

    Balanced

    • Jong PSV to win53%
    • Over 2.5 goals61%
    • Joël van den Berg 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 score59%
    • Over 2.5 goals61%
    • Joël van den Berg to score27%
    • Jordy Bawuah to be booked22%

    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 · TOP Oss25% probability@4.40BetsafeEV+10%reference odds
    • 2 · TOP Oss25% probability@4.40BetssonEV+10%reference odds
    • 2 · TOP Oss25% probability@4.40NordicbetEV+10%reference odds
    Bookmaker1 · Jong PSVX2 · TOP Oss
    Betsafe1.624.05
    EV+ 10%
    4.40
    Betsson1.624.05
    EV+ 10%
    4.40
    Nordicbet1.624.05
    EV+ 10%
    4.40

    Odds updated 18 Aug, 11:37

    Odds movement

    1+1 %
    60 %55 %

    1.601.62

    X0 %
    25 %20 %

    4.054.05

    2-5 %
    23 %18 %

    4.654.40

    Over 2,5+1 %
    69 %64 %

    1.411.43

    Betsson · 4 recorded price levels · 17/08/2026 → 18/08/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    4 matches
    Jong PSV 2Draw 2TOP Oss 0
    Goals: 83 (⌀ 2,8)

    Head-to-head based on Eerste Divisie data since 2023.

    xG & xGA per match — 3-game rolling average

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

    Jong PSV
    TOP Oss
    When goals are scored and conceded 2026
    Jong PSV (45)
    TOP Oss (15)
    Pass networks

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

    Jong PSV
    Essien Bassey: 85 passningar, xT 0.37BasseyJordy Bawuah: 84 passningar, xT 0.07BawuahJoël van den Berg: 73 passningar, xT 0.01BergMadi Monamay: 70 passningar, xT 0.06MonamayGino Verhulst: 66 passningar, xT 0.22VerhulstYarek Gąsiorowski Hernandis: 62 passningar, xT 0.11HernandisMichael Bresser: 61 passningar, xT 0.28BresserFabian Merién: 56 passningar, xT 0.04MeriénFabio Kluit: 49 passningar, xT -0.1KluitKhadim Ngom: 42 passningar, xT 0.02NgomJorvimar Martina: 38 passningar, xT 0.05Martina
    TOP Oss
    Delano Vianello: 58 passningar, xT 0.45VianelloMarcelencio Esajas: 47 passningar, xT 0.05EsajasJulian Kuijpers: 43 passningar, xT 0.08KuijpersMike Havekotte: 38 passningar, xT 0.05HavekotteLeonel Miquel Francisco Miguel: 32 passningar, xT 0.06MiguelMauresmo Johannes Jacob Danny Silvinho Hinoke: 30 passningar, xT -0.04HinokeIlounga Isea Pata: 29 passningar, xT 0.28PataRichard Johannes Cornelis van der Venne: 27 passningar, xT 0.03VenneJustin Mathieu: 18 passningar, xT 0.28MathieuMaurilio de Lannoy: 15 passningar, xT 0.51LannoyJafar Howard Bynoe: 14 passningar, xT -0.08Bynoe
    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.

    Jong PSV
    Essien Bassey: 85 passningar, xT 0.37BasseyJordy Bawuah: 84 passningar, xT 0.07BawuahJoël van den Berg: 73 passningar, xT 0.01BergMadi Monamay: 70 passningar, xT 0.06MonamayGino Verhulst: 66 passningar, xT 0.22VerhulstYarek Gąsiorowski Hernandis: 62 passningar, xT 0.11HernandisMichael Bresser: 61 passningar, xT 0.28BresserFabian Merién: 56 passningar, xT 0.04MeriénFabio Kluit: 49 passningar, xT -0.1KluitKhadim Ngom: 42 passningar, xT 0.02NgomJorvimar Martina: 38 passningar, xT 0.05Martina
    TOP Oss
    Delano Vianello: 58 passningar, xT 0.45VianelloMarcelencio Esajas: 47 passningar, xT 0.05EsajasJulian Kuijpers: 43 passningar, xT 0.08KuijpersMike Havekotte: 38 passningar, xT 0.05HavekotteLeonel Miquel Francisco Miguel: 32 passningar, xT 0.06MiguelMauresmo Johannes Jacob Danny Silvinho Hinoke: 30 passningar, xT -0.04HinokeIlounga Isea Pata: 29 passningar, xT 0.28PataRichard Johannes Cornelis van der Venne: 27 passningar, xT 0.03VenneJustin Mathieu: 18 passningar, xT 0.28MathieuMaurilio de Lannoy: 15 passningar, xT 0.51LannoyJafar Howard Bynoe: 14 passningar, xT -0.08Bynoe

    The teams in numbers

    PerformanceJong PSVTOP Oss
    Points30
    xPoints4.13.1
    xG per match2.11.5
    xGA per match0.652
    xG within 8s of winning the ball0.120.32
    xGA within 8s of losing the ball0.110.24
    Playing styleJong PSVTOP Oss
    Build-up efficiency0.290.31
    Field tilt0.760.23
    xT per match1.40.89
    xTA per match0.412.2
    Won balls, offensive half2624
    Pressing intensity0.220.27
    Pressing efficiency0.420.24
    Pressing efficiency, offensive half0.40.23
    Entries into the box per match1312
    Entries into the box against821
    Pass completion %0.780.63
    Pass completion % under pressure0.760.58
    Passes per match441205
    Passes against per match239508
    Switches of play per match22.822.9
    Long balls per match3739
    Set piecesJong PSVTOP Oss
    xG from free kicks0.010.1
    Corners per match7.16.6
    Corners against per match2.57.6
    xG per corner0.020.03
    xGA per corner against0.060.06
    First touch, offensive corners %0.360.38
    First touch, defensive corners %0.60.53
    OtherJong PSVTOP Oss
    Throw-in control0.670.74
    The goalkeepersKhadim Ngom (Jong PSV)Delano Vianello (TOP Oss)
    Saves35
    Save %50%100%
    xG prevented68%100%
    Claims0 (0%)0 (0%)

    Frequently asked questions

    Who wins Jong PSV vs TOP Oss according to our model?

    The model gives Jong PSV a 53% win probability. Full 1X2 picture: Jong PSV 53%, draw 22%, TOP Oss 25%.

    What is the most likely scoreline?

    The model's most likely final score is 1-1 at 10% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 61% and under at 39%.

    Will both teams score?

    The probability of both teams scoring is 59% 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.