Eerste Divisie19°2,8 mm31 km/h

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    VitesseVitesseLow block & direct
    vs
    TOP OssTOP OssLow block & direct
    The model's lean: 1 · Vitesse (57%)Best value by the model: Under 1,5 @ 5.40 (+29 %)

    Vitesse – TOP Oss · Eerste Divisie

    1 · Vitesse 57%X 24%19% TOP Oss · 2

    Analysis: Vitesse – TOP Oss

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

    TEXT: Vitesse have a clear edge heading into their clash with TOP Oss, with a model probability of 57% favoring the hosts. This match's intrigue lies in its defensive undercurrents, both teams preferring a low-defence, direct approach. While Vitesse hold a slight advantage in head-to-heads with a win and three draws, this small sample size pales in comparison to the current form and expected goals data.

    With Vitesse's expected goals at 1.84 against TOP Oss's 0.90, the hosts are poised to control proceedings. The model's most likely scorelines, 1-0 and 2-0, reflect this dominance. However, the expected goals against (xGA) metric shows both sides equally vulnerable, each sitting at 1.7. This suggests any defensive lapses could swing the match unexpectedly, albeit with Vitesse having the better offensive firepower.

    The weather forecast—5.4 mm of rain—suggests a damp and potentially sluggish game, likely suppressing goal-scoring opportunities. The over 2.5 goals probability sits at a modest 52%, with both teams to score at 50%. This actually shows the model leans marginally towards the over, even though the value lies on the under side of the market.

    For those looking at value, the under 2.5 goals market offers a tempting proposition. With Betsafe, Betsson, and Nordicbet all offering odds of 2.48, there's a notable value edge of 20% against the model's 48% probability. Such opportunities don't come often, making it a solid bet for those favoring a more conservative approach.

    Ultimately, a 1-0 victory for Vitesse seems the most plausible outcome, bolstered by their superior xG figures and historical edge. This game is unlikely to thrill, but as the numbers suggest, the disciplined approach often pays off.

    VitesseVitesse
    Form LDWLW
    League ranking xG #4xGA #13xT #4xP/match #4Points #7
    Key players
    • Naoufal BannisFxG 0.89 · xT -0.15
    • Nathangelo Alexandro MarkeloRWBxG 0.08 · xT 0.51
    • Ricardo-Felipe SchwarzCMxG 0.15 · xT 0.21
    TOP OssTOP Oss
    Form WLLLW
    League ranking xG #11xGA #12xT #15xP/match #8Points #16
    Key players
    • Franslyn NsingiFxG 0.37 · xT 0.01
    • Mauresmo Johannes Jacob Danny Silvinho HinokeLWxG 0.21 · xT 0.10
    • Maurilio de LannoyFxG 0.21 · xT 0.16

    Match prediction: Vitesse – TOP Oss

    Predicted score matrix

    TOP Oss →
    Vitesse →
    0
    1
    2
    3
    4+
    0
    0–06.8%
    0–15.5%
    0–22.6%
    0–30.8%
    0–4+0.2%
    1
    1–011.6%
    1–111.0%
    1–24.8%
    1–31.4%
    1–4+0.4%
    2
    2–010.9%
    2–19.8%
    2–24.4%
    2–31.3%
    2–4+0.4%
    3
    3–06.7%
    3–16.0%
    3–22.7%
    3–30.8%
    3–4+0.2%
    4+
    4+–04.7%
    4+–14.2%
    4+–21.9%
    4+–30.6%
    4+–4+0.2%
    Probability per final score. Rows = home goals, columns = away goals.

    Most likely scorelines

    1. 1.1-012%
    2. 2.1-111%
    3. 3.2-011%
    4. 4.2-110%
    5. 5.0-07%
    Expected goals
    1,84–0,90
    Both teams to score
    50%

    Over/under goals

    Expected goals: 2,7
    Under 2,548%
    @2.52EV+22%
    Over 2,552%
    @1.49

    Ready-made bet suggestions

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    01 · 2 legs

    Safe

    • Vitesse to win57%
    • Over 1.5 goals76%

    Combined probability

    48%

    Fair odds

    2.10

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

    02 · 3 legs

    Balanced

    • Vitesse to win57%
    • Over 2.5 goals52%
    • Alexander Büttner to score26%

    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 score50%
    • Over 2.5 goals52%
    • Alexander Büttner to score26%
    • Marcelencio Esajas 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 1.524% probability@5.40BetsafeEV+29%reference odds
    • Under 1.524% probability@5.40BetssonEV+29%reference odds
    • Under 1.524% probability@5.40NordicbetEV+29%reference odds
    Bookmaker1 · VitesseX2 · TOP Oss
    Betsafe1.603.854.90
    Betsson1.603.854.90
    Nordicbet1.603.854.90

    Odds updated 3 Sept, 22:36

    Odds movement

    Market signal

    The market has moved clearly towards an TOP Oss win since 31 August — the odds have shortened from 5.40 to 4.90 (−9%).

    1+5 %
    62 %57 %

    1.52 → 1.60

    X-7 %
    25 %20 %

    4.15 → 3.85

    2-9 %
    21 %16 %

    5.40 → 4.90

    Over 2,50 %
    65 %60 %

    1.49 → 1.49

    Betsson · 7 recorded price levels · 31/08/2026 → 03/09/2026 · fixed scale 5 percentage points

    Statistics

    Head-to-head

    4 matches
    Vitesse 1Draw 3TOP Oss 0
    Goals: 4–3 (⌀ 1,8)

    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).

    Vitesse
    TOP Oss
    When goals are scored and conceded — 2026
    Vitesse (8–6)
    TOP Oss (3–7)
    Pass networks

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

    Vitesse
    Omar Achouitar: 207 passningar, xT 0.93AchouitarValon Zumberi: 167 passningar, xT 0.26ZumberiRicardo-Felipe Schwarz: 162 passningar, xT 0.61SchwarzMarco Schikora: 124 passningar, xT 0.9SchikoraAyman Sellouf: 112 passningar, xT 0.59SelloufNathangelo Alexandro Markelo: 110 passningar, xT 1MarkeloChiel Olde Keizer: 80 passningar, xT 0.62KeizerMaximilian Brull: 71 passningar, xT 0.01BrullMathijs Marschalk: 56 passningar, xT 0.04MarschalkConnor van den Berg: 50 passningar, xT 0.12BergSolomon Owusu Bonnah: 43 passningar, xT 0.06Bonnah
    TOP Oss
    Delano Vianello: 133 passningar, xT 0.65VianelloIlounga Isea Pata: 94 passningar, xT 0.67PataJulian Kuijpers: 90 passningar, xT 0.24KuijpersMike Havekotte: 87 passningar, xT 0.23HavekotteMarcelencio Esajas: 86 passningar, xT 0.06EsajasLeonel Miquel Francisco Miguel: 80 passningar, xT 0.09MiguelMauresmo Johannes Jacob Danny Silvinho Hinoke: 59 passningar, xT 0.33HinokeRichard Johannes Cornelis van der Venne: 43 passningar, xT 0.07VenneMaurilio de Lannoy: 41 passningar, xT 0.57LannoyMert Erkan: 30 passningar, xT 0.58ErkanFranslyn Nsingi: 28 passningar, xT 0.01Nsingi
    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.

    Vitesse
    Omar Achouitar: 207 passningar, xT 0.93AchouitarValon Zumberi: 167 passningar, xT 0.26ZumberiRicardo-Felipe Schwarz: 162 passningar, xT 0.61SchwarzMarco Schikora: 124 passningar, xT 0.9SchikoraAyman Sellouf: 112 passningar, xT 0.59SelloufNathangelo Alexandro Markelo: 110 passningar, xT 1MarkeloChiel Olde Keizer: 80 passningar, xT 0.62KeizerMaximilian Brull: 71 passningar, xT 0.01BrullMathijs Marschalk: 56 passningar, xT 0.04MarschalkConnor van den Berg: 50 passningar, xT 0.12BergSolomon Owusu Bonnah: 43 passningar, xT 0.06Bonnah
    TOP Oss
    Delano Vianello: 133 passningar, xT 0.65VianelloIlounga Isea Pata: 94 passningar, xT 0.67PataJulian Kuijpers: 90 passningar, xT 0.24KuijpersMike Havekotte: 87 passningar, xT 0.23HavekotteMarcelencio Esajas: 86 passningar, xT 0.06EsajasLeonel Miquel Francisco Miguel: 80 passningar, xT 0.09MiguelMauresmo Johannes Jacob Danny Silvinho Hinoke: 59 passningar, xT 0.33HinokeRichard Johannes Cornelis van der Venne: 43 passningar, xT 0.07VenneMaurilio de Lannoy: 41 passningar, xT 0.57LannoyMert Erkan: 30 passningar, xT 0.58ErkanFranslyn Nsingi: 28 passningar, xT 0.01Nsingi

    The teams in numbers

    PerformanceVitesseTOP Oss
    Points73
    xPoints6.76.3
    xG per match21.4
    xGA per match1.71.7
    xG within 8s of winning the ball0.450.27
    xGA within 8s of losing the ball0.180.18
    Playing styleVitesseTOP Oss
    Build-up efficiency0.320.31
    Field tilt0.570.35
    xT per match1.61.1
    xTA per match1.51.7
    Won balls, offensive half2426
    Pressing intensity0.220.25
    Pressing efficiency0.310.26
    Pressing efficiency, offensive half0.350.24
    Entries into the box per match1615
    Entries into the box against1718
    Pass completion %0.760.64
    Pass completion % under pressure0.720.59
    Passes per match342224
    Passes against per match330458
    Switches of play per match29.221.7
    Long balls per match3842
    Set piecesVitesseTOP Oss
    xG from free kicks0.050.06
    Corners per match46.3
    Corners against per match66.8
    xG per corner0.020.02
    xGA per corner against0.030.05
    First touch, offensive corners %0.380.4
    First touch, defensive corners %0.620.59
    OtherVitesseTOP Oss
    Throw-in control0.720.7
    The goalkeepersConnor van den Berg (Vitesse)Mike Havekotte (TOP Oss)
    Saves1015
    Save %91%68%
    xG prevented88%48%
    Claims0 (0%)0 (0%)

    Frequently asked questions

    Who wins Vitesse vs TOP Oss according to our model?

    The model gives Vitesse a 57% win probability. Full 1X2 picture: Vitesse 57%, draw 24%, TOP Oss 19%.

    What is the most likely scoreline?

    The model's most likely final score is 1-0 at 12% probability.

    Over or under 2.5 goals?

    The model rates over 2.5 goals at 52% and under at 48%.

    Will both teams score?

    The probability of both teams scoring is 50% 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.