01 · 2 legs
Safe
- Podbrezová to win46%
- Over 1.5 goals79%
Slovak Super League16°0,6 mm12 km/h
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SkalicaLow block & direct
PodbrezováLow block & directSofia Andersson · · The model's read on the match · How the predictions work
In the four head-to-head clashes since 2023, Skalica has failed to secure a victory against Podbrezová, managing only a single draw. This small sample size suggests a pattern but weighs less than the current season's form and expected goals. Skalica's struggles are mirrored in their points tally, with only 8 compared to Podbrezová's 10, and their xPoints further highlight this disparity: 6.9 against the visitors' 10.3.
Podbrezová's strength is evident not just in their head-to-head superiority but in their overall xG metrics. Averaging 2.0 expected goals per match, they outshine Skalica's meager 0.98. Defensively, the hosts also falter, conceding an average of 2.1 xGA per game, while Podbrezová's defense is comparatively sturdier, allowing just 1.7 xGA per match.
The model probabilities lean towards Podbrezová with a 46% chance of victory, and the visitors are supported by the most likely scorelines of 1-2 and 0-1, each with a 9% probability. Skalica, profiling as a team with a low defensive line and direct play, faces a daunting task against Podbrezová's similarly direct but more efficient tactics. The expected goals tally of 1.23 for Skalica versus 1.70 for the visitors suggests the latter's attacking edge.
For those seeking value in the betting markets, Podbrezová to win at 2.20 offers a compelling angle, given their superiority in both form and statistical projection. Meanwhile, with a 56% likelihood of over 2.5 goals and a 58% chance of both teams finding the net, the match leans towards a more open contest than the teams' defensive profiles might suggest.
01 · 2 legs
02 · 3 legs
03 · 4 legs
No odds available yet.
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 | Skalica | Podbrezová |
|---|---|---|
| Points | 8 | 10 |
| xPoints | 6.9 | 10.3 |
| xG per match | 0.98 | 2 |
| xGA per match | 2.1 | 1.7 |
| xG within 8s of winning the ball | 0.29 | 0.33 |
| xGA within 8s of losing the ball | 0.25 | 0.48 |
| Playing style | Skalica | Podbrezová |
|---|---|---|
| Build-up efficiency | 0.31 | 0.33 |
| Field tilt | 0.38 | 0.55 |
| xT per match | 0.66 | 1.2 |
| xTA per match | 1.4 | 1.2 |
| Won balls, offensive half | 21 | 24 |
| Pressing intensity | 0.22 | 0.22 |
| Pressing efficiency | 0.31 | 0.26 |
| Pressing efficiency, offensive half | 0.25 | 0.22 |
| Entries into the box per match | 9 | 15 |
| Entries into the box against | 16 | 13 |
| Pass completion % | 0.63 | 0.73 |
| Pass completion % under pressure | 0.62 | 0.71 |
| Passes per match | 221 | 312 |
| Passes against per match | 364 | 355 |
| Switches of play per match | 14.9 | 20.3 |
| Long balls per match | 27 | 28 |
| Set pieces | Skalica | Podbrezová |
|---|---|---|
| xG from free kicks | 0.01 | 0.08 |
| Corners per match | 5.1 | 6.3 |
| Corners against per match | 5.7 | 5.2 |
| xG per corner | 0.02 | 0.03 |
| xGA per corner against | 0.05 | 0.03 |
| First touch, offensive corners % | 0.47 | 0.64 |
| First touch, defensive corners % | 0.47 | 0.58 |
| Other | Skalica | Podbrezová |
|---|---|---|
| Throw-in control | 0.7 | 0.73 |
| The goalkeepers | Erik Riska (Skalica) | Martin Trnovsky (Podbrezová) |
|---|---|---|
| Saves | 18 | 11 |
| Save % | 78% | 58% |
| xG prevented | 51% | 40% |
| Claims | 0 (0%) | 0 (0%) |
The model gives Podbrezová a 46% win probability. Full 1X2 picture: Skalica 27%, draw 27%, Podbrezová 46%.
The model's most likely final score is 1-1 at 12% probability.
The model rates over 2.5 goals at 56% and under at 44%.
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.