01 · 2 legs
Safe
- Viborg to win46%
- Over 1.5 goals76%
Danish SuperligaCepheus Park, Randers8°1,2 mm16 km/h
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Anna Karlsson · · A data-driven preview · How the predictions work
46% — that's the model's clear lean towards Viborg securing a win against Randers. Despite the hosts' commendable head-to-head streak of three wins in four encounters since 2022, it's the visitors' broader season form and xG numbers that tell a compelling story. Viborg's attacking potency shines with an average of 1.6 expected goals per match compared to Randers' 1.1, indicating their superior offensive capabilities which are likely to tip the balance in their favor.
While the head-to-head sample remains small and less significant than current season dynamics, the expected goals and points suggest Viborg are the more formidable side. Randers' defensive frailties, conceding an average of 1.5 goals per match, contrast with Viborg's more robust backline. Yet, the most likely scorelines — 1-1, 0-1, and 1-2 — reflect a tight, competitive fixture, underscored by a 55% chance of both teams finding the net.
A sharp betting angle emerges with the under 2.5 goals market, offering value at odds of 2.15 with LeoVegas. The model's rating of 49% suggests a savvy play here, considering the defensive strategies and expected goals. This clash might just play out tighter than many anticipate, with Viborg edging it 0-1 or 1-2.
01 · 2 legs
02 · 3 legs
03 · 4 legs
Bets where the model's probability beats what the odds imply (EV+).
| Bookmaker | 1 · Randers | X | 2 · Viborg |
|---|---|---|---|
| Betsafe | 3.20 | EV+ 1% 3.60 | 2.10 |
| LeoVegas | 3.25 | EV+ 2% 3.65 | 2.08 |
| Nordicbet | 3.25 | EV+ 2% 3.65 | 2.12 |
Odds updated 3 Oct, 07:36
Head-to-head based on Danish Superliga data since 2022.
Solid line = created (xG), dashed = conceded (xGA).
Last 5 matches. Circle size = pass volume, line width = combinations between players. Attacking left to right.
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.
| Performance | Randers | Viborg |
|---|---|---|
| Points | 10 | 17 |
| xPoints | 11 | 14.8 |
| xG per match | 1.1 | 1.6 |
| xGA per match | 1.5 | 1.2 |
| xG within 8s of winning the ball | 0.17 | 0.25 |
| xGA within 8s of losing the ball | 0.28 | 0.29 |
| Playing style | Randers | Viborg |
|---|---|---|
| Build-up efficiency | 0.31 | 0.31 |
| Field tilt | 0.4 | 0.45 |
| xT per match | 0.87 | 1.1 |
| xTA per match | 1.3 | 0.97 |
| Won balls, offensive half | 24 | 23 |
| Pressing intensity | 0.25 | 0.24 |
| Pressing efficiency | 0.29 | 0.26 |
| Pressing efficiency, offensive half | 0.22 | 0.23 |
| Entries into the box per match | 10 | 14 |
| Entries into the box against | 16 | 12 |
| Pass completion % | 0.75 | 0.79 |
| Pass completion % under pressure | 0.7 | 0.75 |
| Passes per match | 351 | 391 |
| Passes against per match | 456 | 419 |
| Switches of play per match | 23.5 | 31.4 |
| Long balls per match | 29 | 32 |
| Set pieces | Randers | Viborg |
|---|---|---|
| xG from free kicks | 0.04 | 0.04 |
| Corners per match | 4 | 5 |
| Corners against per match | 7.8 | 6.1 |
| xG per corner | 0.03 | 0.02 |
| xGA per corner against | 0.02 | 0.02 |
| First touch, offensive corners % | 0.39 | 0.3 |
| First touch, defensive corners % | 0.71 | 0.65 |
| Other | Randers | Viborg |
|---|---|---|
| Throw-in control | 0.74 | 0.71 |
| The goalkeepers | Jannich Storch (Randers) | Kasper Kiilerich (Viborg) |
|---|---|---|
| Saves | 18 | 26 |
| Save % | 72% | 77% |
| xG prevented | 61% | 49% |
| Claims | 0 (0%) | 0 (0%) |
The model gives Viborg a 46% win probability. Full 1X2 picture: Randers 26%, draw 28%, Viborg 46%.
The model's most likely final score is 1-1 at 12% probability.
The model rates over 2.5 goals at 51% and under at 49%.
The probability of both teams scoring is 55% according to the model.
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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Hämta bonusPredictions come from PlaymakerAI's match model and reflect the model's assessment — not betting advice. Gamble responsibly.