01 · 2 legs
Safe
- AGF to win62%
- Over 1.5 goals81%
Danish SuperligaCeres Park, Aarhus14°1,7 mm36 km/h
Läs på svenskaSofia Andersson · · The model's read on the match · How the predictions work
AGF Aarhus finds favor in the numbers with a 62% chance of victory, setting a clear expectation for their upcoming clash against Silkeborg. The model's inclination towards the home side is underpinned by superior expected goals (xG) stats, which reflect AGF's dynamic possession and high press style. In contrast, Silkeborg's balanced and physical approach yields a lesser xG, hinting at their challenge in breaking down AGF's setup. This tactical mismatch suggests the hosts have the upper hand at home.
Despite Silkeborg's current edge in points, AGF's underlying metrics, particularly their xPoints of 8.3 compared to Silkeborg's 7.5, indicate a stronger performance than the standings suggest. AGF's xG of 1.6 per match dwarfs Silkeborg's 0.92, while defensively, they also hold a slight advantage with a lower xGA. These statistics affirm the model's confidence in AGF's potential to secure a result on their home turf.
The head-to-head history between these sides since 2022 shows AGF unbeaten in four matches, with two wins and two draws. While this is a small sample, it adds weight to the argument that AGF knows how to handle Silkeborg. The model's most likely outcomes, such as a 2-1 or 2-0 victory for AGF, align with this narrative. The expectation of goals is further supported by a 59% chance of over 2.5 goals, suggesting an open game despite the weather forecasts indicating rain, which traditionally tempers goalmouth action.
Curiously, there’s notable value in the market for a low-scoring draw, specifically under 0.5 goals at attractive odds of 23.0 with Betsafe, Betsson, and Nordicbet. The model rates this outcome at 5%, translating to a sizeable 14% edge. While such an event remains a long shot, the discrepancy presents an intriguing angle for those looking to capitalize on market inefficiencies.
The verdict on the pre-built bet builders for this match, priced against the model’s score matrix before kickoff. Graded on the 90-minute result.
01 · 2 legs
02 · 3 legs
03 · 4 legs
Bets where the model's probability beats what the odds imply (EV+).
| Bookmaker | 1 · AGF | X | 2 · Silkeborg |
|---|---|---|---|
| Betfair Exchange | 1.10 | 1.10 | 1.10 |
| Betsafe | 1.52 | 4.30 | EV+ 7% 5.80 |
| Betsson | 1.52 | 4.35 | EV+ 9% 5.90 |
| Nordicbet | 1.52 | 4.35 | EV+ 9% 5.90 |
| Pinnacle | 1.51 | 4.83 | EV+ 6% 5.75 |
Odds updated 5 Sept, 10:32
1.51 → 1.51
4.79 → 4.83
5.30 → 5.75
Pinnacle · 11 recorded price levels · 03/09/2026 → 05/09/2026 · fixed scale 5 percentage points
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 | AGF | Silkeborg |
|---|---|---|
| Points | 3 | 5 |
| xPoints | 8.3 | 7.5 |
| xG per match | 1.6 | 0.92 |
| xGA per match | 1.4 | 1.6 |
| xG within 8s of winning the ball | 0.28 | 0.2 |
| xGA within 8s of losing the ball | 0.19 | 0.36 |
| Playing style | AGF | Silkeborg |
|---|---|---|
| Build-up efficiency | 0.3 | 0.32 |
| Field tilt | 0.6 | 0.39 |
| xT per match | 1.2 | 0.64 |
| xTA per match | 0.87 | 1.4 |
| Won balls, offensive half | 24 | 18 |
| Pressing intensity | 0.24 | 0.25 |
| Pressing efficiency | 0.3 | 0.25 |
| Pressing efficiency, offensive half | 0.26 | 0.19 |
| Entries into the box per match | 17 | 13 |
| Entries into the box against | 12 | 16 |
| Pass completion % | 0.78 | 0.8 |
| Pass completion % under pressure | 0.7 | 0.76 |
| Passes per match | 421 | 416 |
| Passes against per match | 276 | 468 |
| Switches of play per match | 25.8 | 15.6 |
| Long balls per match | 29 | 20 |
| Set pieces | AGF | Silkeborg |
|---|---|---|
| xG from free kicks | 0.07 | 0.05 |
| Corners per match | 8.3 | 5 |
| Corners against per match | 3.2 | 6 |
| xG per corner | 0.02 | 0.01 |
| xGA per corner against | 0.04 | 0.02 |
| First touch, offensive corners % | 0.3 | 0.63 |
| First touch, defensive corners % | 0.58 | 0.64 |
| Other | AGF | Silkeborg |
|---|---|---|
| Throw-in control | 0.7 | 0.7 |
| The goalkeepers | Mads Hedenstad Christiansen (AGF) | Aske Andresen (Silkeborg) |
|---|---|---|
| Saves | 13 | 19 |
| Save % | 62% | 68% |
| xG prevented | 51% | 43% |
| Claims | 0 (0%) | 0 (0%) |
The model gives AGF a 62% win probability. Full 1X2 picture: AGF 62%, draw 20%, Silkeborg 19%.
The model's most likely final score is 1-1 at 10% probability.
The model rates over 2.5 goals at 59% and under at 41%.
The probability of both teams scoring is 58% 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.
Predictions come from PlaymakerAI's match model and reflect the model's assessment — not betting advice. Gamble responsibly.