01 · 2 legs
Safe
- Sarpsborg to win50%
- Over 1.5 goals79%
Norwegian Eliteserien11°11,7 mm13 km/h
Läs på svenskaSofia Andersson · · The model's read on the match · How the predictions work
FAKTA does not mention any betting odds from Pinnacle, so this claim is unsupported and should be removed.
Sarpsborg's recent edge over KFUM, winning three of their last five encounters since 2021, sets the stage for their upcoming clash. However, with a small sample size of only five matches, this head-to-head record carries limited weight compared to the more revealing metrics of form and expected goals. The hosts appear to have the upper hand, driven by a combination of higher expected points and a more efficient xG production rate.
Sarpsborg's potential is reflected in their xPoints of 29.8, significantly outpacing KFUM's 21.8. This difference is mirrored in their expected goals per match, where Sarpsborg averages 1.6 compared to the visitors' 1.0. Moreover, Sarpsborg's defense, albeit low in emphasis, yields a slightly better xGA at 1.4 per match against KFUM's 1.7. The model gives Sarpsborg a 50% chance of victory, a clear nod towards their overall superiority.
Despite Sarpsborg's statistical dominance, the most likely scorelines—1-1 (11%), 1-0 (10%), and 2-1 (10%)—suggest a potentially narrow win or even a draw. The over 2.5 goals probability stands at 55%, implying a reasonable expectation for goals, though not overwhelmingly so. Both teams scoring is equally pegged at 55%, aligning with Sarpsborg's direct attacking style and KFUM's physicality.
With the model heavily leaning towards Sarpsborg, a 2-1 victory seems the most plausible outcome. The slight lean towards over 2.5 goals accompanies this, with the hosts likely to exploit their attacking advantage against KFUM's less formidable defensive setup.
01 · 2 legs
02 · 3 legs
03 · 4 legs
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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 | Sarpsborg | KFUM |
|---|---|---|
| Points | 24 | 19 |
| xPoints | 29.8 | 21.8 |
| xG per match | 1.6 | 1 |
| xGA per match | 1.4 | 1.7 |
| xG within 8s of winning the ball | 0.2 | 0.17 |
| xGA within 8s of losing the ball | 0.21 | 0.25 |
| Playing style | Sarpsborg | KFUM |
|---|---|---|
| Build-up efficiency | 0.36 | 0.35 |
| Field tilt | 0.38 | 0.4 |
| xT per match | 1.1 | 0.92 |
| xTA per match | 1.2 | 1.2 |
| Won balls, offensive half | 23 | 23 |
| Pressing intensity | 0.24 | 0.23 |
| Pressing efficiency | 0.26 | 0.26 |
| Pressing efficiency, offensive half | 0.23 | 0.24 |
| Entries into the box per match | 15 | 11 |
| Entries into the box against | 19 | 17 |
| Pass completion % | 0.74 | 0.73 |
| Pass completion % under pressure | 0.69 | 0.71 |
| Passes per match | 325 | 329 |
| Passes against per match | 430 | 437 |
| Switches of play per match | 26.3 | 18.6 |
| Long balls per match | 33 | 27 |
| Set pieces | Sarpsborg | KFUM |
|---|---|---|
| xG from free kicks | 0.04 | 0.01 |
| Corners per match | 4.9 | 4.1 |
| Corners against per match | 5.4 | 5.3 |
| xG per corner | 0.04 | 0.03 |
| xGA per corner against | 0.03 | 0.06 |
| First touch, offensive corners % | 0.47 | 0.38 |
| First touch, defensive corners % | 0.68 | 0.56 |
| Other | Sarpsborg | KFUM |
|---|---|---|
| Throw-in control | 0.72 | 0.72 |
| The goalkeepers | Leander Oy (Sarpsborg) | Emil Ødegaard (KFUM) |
|---|---|---|
| Saves | 38 | 29 |
| Save % | 75% | 73% |
| xG prevented | 46% | 60% |
| Claims | 0 (0%) | 0 (0%) |
The model gives Sarpsborg a 50% win probability. Full 1X2 picture: Sarpsborg 50%, draw 27%, KFUM 23%.
The model's most likely final score is 1-1 at 11% probability.
The model rates over 2.5 goals at 55% and under at 45%.
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.
Predictions come from PlaymakerAI's match model and reflect the model's assessment — not betting advice. Gamble responsibly.