01 · 2 legs
Safe
- Vojvodina to win51%
- Over 1.5 goals77%
Serbian Super LeagueKarađorđe-stadion, Novi Sad19°10 km/h
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FK IMT BeogradPossession controlAnna Karlsson · · A data-driven preview · How the predictions work
The clash between Vojvodina and FK IMT Beograd is set to pivot on contrasting styles. The hosts, Vojvodina, are in a rich vein of form with three consecutive victories, leveraging a high-press, possession-heavy approach. This strategy could unsettle the visitors, who prefer a more controlled possession game but have struggled to translate that into points, sitting on a solitary point so far.
The model's numbers suggest a tight contest but lean towards a Vojvodina victory with a 51% win probability. The expected goals underscore a similar story: 1.67 for Vojvodina against 1.09 for IMT Beograd. However, the visitors have demonstrated defensive sturdiness, boasting a remarkably low xGA per match of 0.32, which might help them withstand Vojvodina's attacking thrusts.
Despite their strong defensive metrics, IMT Beograd's offensive output has been less impressive, as reflected in their solitary point and the model's suggestion that they are less likely to find the net. Yet, their high xG per match of 2.5 raises the question of whether they can finally convert potential into goals. The small head-to-head sample offers little predictive power, leaving current form and expected goals as the more reliable indicators.
With Vojvodina’s momentum and IMT Beograd's defensive acumen, a narrow victory for the hosts, perhaps 1-0 or 2-1, seems plausible. The over 2.5 goals probability stands at 52%, hinting at a competitive match but not necessarily a high-scoring one.
01 · 2 legs
02 · 3 legs
03 · 4 legs
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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 | Vojvodina | FK IMT Beograd |
|---|---|---|
| Points | 18 | 1 |
| xPoints | 13 | 2.6 |
| xG per match | 2.1 | 2.5 |
| xGA per match | 1.3 | 0.32 |
| xG within 8s of winning the ball | 0.72 | 1.3 |
| xGA within 8s of losing the ball | 0.54 | 0.05 |
| Playing style | Vojvodina | FK IMT Beograd |
|---|---|---|
| Build-up efficiency | 0.3 | 0.31 |
| Field tilt | 0.62 | 0.57 |
| xT per match | 1.6 | 1.2 |
| xTA per match | 0.76 | 0.23 |
| Won balls, offensive half | 28 | 39 |
| Pressing intensity | 0.21 | 0.2 |
| Pressing efficiency | 0.29 | 0.35 |
| Pressing efficiency, offensive half | 0.26 | 0.36 |
| Entries into the box per match | 15 | 8 |
| Entries into the box against | 10 | 3 |
| Pass completion % | 0.75 | 0.67 |
| Pass completion % under pressure | 0.71 | 0.68 |
| Passes per match | 320 | 297 |
| Passes against per match | 266 | 252 |
| Switches of play per match | 20.7 | 8.9 |
| Long balls per match | 31 | 32 |
| Set pieces | Vojvodina | FK IMT Beograd |
|---|---|---|
| xG from free kicks | 0.03 | 0 |
| Corners per match | 5.3 | 4 |
| Corners against per match | 4.5 | 2 |
| xG per corner | 0.01 | 0 |
| xGA per corner against | 0.01 | 0.02 |
| First touch, offensive corners % | 0.39 | 0.25 |
| First touch, defensive corners % | 0.69 | 0.5 |
| Other | Vojvodina | FK IMT Beograd |
|---|---|---|
| Throw-in control | 0.65 | 0.88 |
| The goalkeepers | Dragan Rosić (Vojvodina) | Stefan Šapić (FK IMT Beograd) |
|---|---|---|
| Saves | 33 | 2 |
| Save % | 83% | 100% |
| xG prevented | 58% | 100% |
| Claims | 0 (0%) | 0 (0%) |
The model gives Vojvodina a 51% win probability. Full 1X2 picture: Vojvodina 51%, draw 27%, FK IMT Beograd 22%.
The model's most likely final score is 1-1 at 12% probability.
The model rates over 2.5 goals at 52% and under at 48%.
The probability of both teams scoring is 54% 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.