01 · 2 legs
Safe
- Slovan Bratislava to win60%
- Over 1.5 goals85%
Slovak Super LeagueTehelné pole, Bratislava18°0,1 mm10 km/h
Läs på svenskaErik Lindberg · · Written from the model's numbers · How the predictions work
Slovan Bratislava's dominance at home, winning 63% of their matches historically, provides a solid foundation for their clash against Žilina. Although the visitors ride a four-game winning streak, the expected goals tell a different story. Slovan's xG of 2.0 per match overshadows Žilina's 1.7, suggesting the home side should generate more and better chances.
Despite Žilina's current form and a slight edge in league points, Slovan's defensive metrics stand out. With an xGA of just 0.93 compared to Žilina's 1.5, the hosts appear more robust at the back, which could prove decisive given their possession-control style against Žilina's high press. The model's probabilities tilt heavily towards Bratislava with a 60% win chance, and the expected goals suggest a 2-1 scoreline as the most likely outcome.
For bettors, the over 2.5 goals market seems promising, given the 66% probability and the high-scoring nature of previous encounters, averaging 4.1 goals per game, which aligns well with the model's analysis and the historical data favoring the hosts in this matchup.
01 · 2 legs
02 · 3 legs
03 · 4 legs
Bets where the model's probability beats what the odds imply (EV+).
| Bookmaker | 1 · Slovan Bratislava | X | 2 · Žilina |
|---|---|---|---|
| Betsafe | EV+ 1% 1.70 | 3.85 | 3.95 |
| Betsson | EV+ 1% 1.70 | 3.85 | 3.95 |
| Nordicbet | EV+ 1% 1.70 | 3.85 | 3.95 |
| Pinnacle | EV+ 5% 1.76 | 3.96 | 3.92 |
Odds updated 11 Sept, 14:39
Market signal
The market has moved clearly towards an Žilina win since 7 September — the odds have shortened from 5.21 to 3.92 (−25%).
1.49 → 1.76
4.63 → 3.96
5.21 → 3.92
Pinnacle · 10 recorded price levels · 07/09/2026 → 11/09/2026 · fixed scale 10 percentage points
Head-to-head based on Slovak Super League data since 2023.
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 | Slovan Bratislava | Žilina |
|---|---|---|
| Points | 12 | 16 |
| xPoints | 9.3 | 9.4 |
| xG per match | 2 | 1.7 |
| xGA per match | 0.93 | 1.5 |
| xG within 8s of winning the ball | 0.19 | 0.39 |
| xGA within 8s of losing the ball | 0.23 | 0.26 |
| Playing style | Slovan Bratislava | Žilina |
|---|---|---|
| Build-up efficiency | 0.33 | 0.31 |
| Field tilt | 0.65 | 0.53 |
| xT per match | 1.8 | 1.2 |
| xTA per match | 0.72 | 1.1 |
| Won balls, offensive half | 29 | 21 |
| Pressing intensity | 0.23 | 0.22 |
| Pressing efficiency | 0.36 | 0.28 |
| Pressing efficiency, offensive half | 0.35 | 0.26 |
| Entries into the box per match | 19 | 14 |
| Entries into the box against | 10 | 12 |
| Pass completion % | 0.82 | 0.77 |
| Pass completion % under pressure | 0.78 | 0.75 |
| Passes per match | 522 | 387 |
| Passes against per match | 218 | 293 |
| Switches of play per match | 39.6 | 19.8 |
| Long balls per match | 48 | 29 |
| Set pieces | Slovan Bratislava | Žilina |
|---|---|---|
| xG from free kicks | 0.02 | 0.04 |
| Corners per match | 5.9 | 6.3 |
| Corners against per match | 3.7 | 5.6 |
| xG per corner | 0.09 | 0.03 |
| xGA per corner against | 0.02 | 0.01 |
| First touch, offensive corners % | 0.51 | 0.39 |
| First touch, defensive corners % | 0.5 | 0.64 |
| Other | Slovan Bratislava | Žilina |
|---|---|---|
| Throw-in control | 0.8 | 0.75 |
| The goalkeepers | Aleksandar Popovic (Slovan Bratislava) | David Sipos (Žilina) |
|---|---|---|
| Saves | 10 | 23 |
| Save % | 77% | 70% |
| xG prevented | 71% | 49% |
| Claims | 0 (0%) | 0 (0%) |
The model gives Slovan Bratislava a 60% win probability. Full 1X2 picture: Slovan Bratislava 60%, draw 22%, Žilina 18%.
The model's most likely final score is 2-1 at 10% probability.
The model rates over 2.5 goals at 66% and under at 34%.
The probability of both teams scoring is 61% 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.