01 · 2 legs
Safe
- Slavia Praha to win50%
- Over 1.5 goals83%
Czech First League15°0,3 mm19 km/h
Läs på svenskaMarcus Johansson · · Analysis from the match model · How the predictions work
Slavia's relentless high-pressing game has been a nightmare for Viktoria Plzen in recent clashes. The hosts have maintained an impressive unbeaten run in their last eight league matches and have found the net in 14 on the trot. Plzen, a more physically oriented side, will struggle to disrupt Slavia's rhythm, especially given the visitors have never beaten them in their past six encounters since 2023. This fixture historically leans toward Slavia, with the home side claiming five victories and one draw.
The numbers strongly favor Slavia. With expected goals at 1.90 compared to Plzen's 1.28, the hosts are likely to control the match tempo. Their superior xPoints of 13.5 over Plzen's 10.4 further emphasize this edge. Meanwhile, Slavia's xG per match at 2.5 dwarfs Plzen's 1.4, underscoring their attacking potency. The visitors' balanced approach might help them resist the onslaught to an extent, but the relentless pressure from Slavia's high press is likely to find its mark eventually.
Expect goals, as the model suggests a 61% chance of over 2.5 goals, while both teams to score is a 62% likelihood. The fixture has averaged 4.2 goals per meeting, pointing to an open game despite Plzen's defensive resilience. A 2-1 outcome, among the most probable scorelines at 10%, reflects Slavia's dominance and slight defensive vulnerabilities.
For those eyeing value, consider the over 2.5 goals market. Bookmakers have set the over/under line at 2.5, with the probabilities tilting towards a high-scoring affair. Given Slavia's aggressive style and Plzen's physicality, a lively contest is on the cards, with Slavia expected to edge out at home.
01 · 2 legs
02 · 3 legs
03 · 4 legs
No odds available yet.
Head-to-head based on Czech First 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 | Slavia Praha | Viktoria Plzeň |
|---|---|---|
| Points | 17 | 10 |
| xPoints | 13.5 | 10.4 |
| xG per match | 2.5 | 1.4 |
| xGA per match | 1 | 1.1 |
| xG within 8s of winning the ball | 0.58 | 0.17 |
| xGA within 8s of losing the ball | 0.2 | 0.14 |
| Playing style | Slavia Praha | Viktoria Plzeň |
|---|---|---|
| Build-up efficiency | 0.34 | 0.33 |
| Field tilt | 0.58 | 0.56 |
| xT per match | 1.2 | 1.2 |
| xTA per match | 0.82 | 0.71 |
| Won balls, offensive half | 27 | 21 |
| Pressing intensity | 0.22 | 0.22 |
| Pressing efficiency | 0.36 | 0.3 |
| Pressing efficiency, offensive half | 0.34 | 0.25 |
| Entries into the box per match | 16 | 13 |
| Entries into the box against | 9 | 12 |
| Pass completion % | 0.71 | 0.78 |
| Pass completion % under pressure | 0.69 | 0.74 |
| Passes per match | 287 | 390 |
| Passes against per match | 238 | 296 |
| Switches of play per match | 25.1 | 28 |
| Long balls per match | 36 | 33 |
| Set pieces | Slavia Praha | Viktoria Plzeň |
|---|---|---|
| xG from free kicks | 0.01 | 0.1 |
| Corners per match | 5.2 | 3.9 |
| Corners against per match | 5 | 4.6 |
| xG per corner | 0.05 | 0.01 |
| xGA per corner against | 0.02 | 0.02 |
| First touch, offensive corners % | 0.35 | 0.44 |
| First touch, defensive corners % | 0.6 | 0.5 |
| Other | Slavia Praha | Viktoria Plzeň |
|---|---|---|
| Throw-in control | 0.71 | 0.77 |
| The goalkeepers | Jakub Markovič (Slavia Praha) | Florian Wiegele (Viktoria Plzeň) |
|---|---|---|
| Saves | 12 | 21 |
| Save % | 71% | 66% |
| xG prevented | 44% | 49% |
| Claims | 0 (0%) | 0 (0%) |
The model gives Slavia Praha a 50% win probability. Full 1X2 picture: Slavia Praha 50%, draw 27%, Viktoria Plzeň 24%.
The model's most likely final score is 1-1 at 10% probability.
The model rates over 2.5 goals at 61% and under at 39%.
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.