01 · 2 legs
Safe
- Vålerenga to win48%
- Over 1.5 goals82%
Norwegian Eliteserien12°0,9 mm7 km/h
Läs på svenskaOscar Nilsson · · Model-assisted analysis, fact-checked · How the predictions work
TEXT: Fredrikstad might be enjoying a points lead over Vålerenga in the Eliteserien standings, but the numbers tell a more nuanced story. The model gives Vålerenga a 48% chance of winning, suggesting the market might slightly underestimate the hosts. While the head-to-head record shows no wins for Vålerenga in their last three meetings, this small sample carries less weight than the current form and expected goals data.
Vålerenga's expected goals (1.80) surpass Fredrikstad's (1.33), indicating that the hosts are creating higher quality chances. Despite being just marginally ahead on xPoints, Vålerenga's xGA of 1.7 compared to Fredrikstad's 1.9 suggests they are slightly more resilient at the back. It’s a tight contest, yet these underlying metrics favor the home side.
Goals may well flow, with a 60% chance of over 2.5 goals and a 62% likelihood that both teams find the net. Such probabilities hint at a lively encounter, where defenses might struggle to keep clean sheets. The most likely scoreline, 1-1, reflects the visitors' ability to compete, but Vålerenga's 2-1 and 1-0 win probabilities suggest a slight edge in their favor.
In this tightly poised matchup, the slight lean towards Vålerenga, both in terms of underlying numbers and model probabilities, makes them the more interesting side to consider. It's a case of metrics trumping the narrative of recent head-to-head struggles.
01 · 2 legs
02 · 3 legs
03 · 4 legs
No odds available yet.
Head-to-head based on Eliteserien data since 2021.
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 | Vålerenga | Fredrikstad |
|---|---|---|
| Points | 23 | 26 |
| xPoints | 23.2 | 20.7 |
| xG per match | 1.4 | 1.3 |
| xGA per match | 1.7 | 1.9 |
| xG within 8s of winning the ball | 0.3 | 0.16 |
| xGA within 8s of losing the ball | 0.24 | 0.3 |
| Playing style | Vålerenga | Fredrikstad |
|---|---|---|
| Build-up efficiency | 0.36 | 0.36 |
| Field tilt | 0.51 | 0.41 |
| xT per match | 1.2 | 0.9 |
| xTA per match | 1.1 | 1.1 |
| Won balls, offensive half | 25 | 24 |
| Pressing intensity | 0.23 | 0.24 |
| Pressing efficiency | 0.29 | 0.26 |
| Pressing efficiency, offensive half | 0.27 | 0.26 |
| Entries into the box per match | 16 | 11 |
| Entries into the box against | 16 | 16 |
| Pass completion % | 0.76 | 0.77 |
| Pass completion % under pressure | 0.72 | 0.74 |
| Passes per match | 380 | 377 |
| Passes against per match | 384 | 437 |
| Switches of play per match | 24.3 | 25.3 |
| Long balls per match | 33 | 37 |
| Set pieces | Vålerenga | Fredrikstad |
|---|---|---|
| xG from free kicks | 0.01 | 0.07 |
| Corners per match | 6.7 | 4 |
| Corners against per match | 5.7 | 6 |
| xG per corner | 0.03 | 0.04 |
| xGA per corner against | 0.05 | 0.04 |
| First touch, offensive corners % | 0.41 | 0.38 |
| First touch, defensive corners % | 0.51 | 0.51 |
| Other | Vålerenga | Fredrikstad |
|---|---|---|
| Throw-in control | 0.76 | 0.76 |
| The goalkeepers | Oscar Thore Hedvall (Vålerenga) | Martin Borsheim (Fredrikstad) |
|---|---|---|
| Saves | 66 | 65 |
| Save % | 62% | 68% |
| xG prevented | 48% | 38% |
| Claims | 0 (0%) | 0 (0%) |
The model gives Vålerenga a 48% win probability. Full 1X2 picture: Vålerenga 48%, draw 26%, Fredrikstad 25%.
The model's most likely final score is 1-1 at 11% probability.
The model rates over 2.5 goals at 60% and under at 40%.
The probability of both teams scoring is 62% 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.