01 · 2 legs
Safe
- Dinamo Zagreb to win84%
- Over 1.5 goals85%
Croatian HNL18°5 km/h
Läs på svenskaOscar Nilsson · · Model-assisted analysis, fact-checked · How the predictions work
TEXT: Dinamo Zagreb's unbeaten streak of 28 league games sets a daunting stage for Lokomotiva Zagreb, who are currently grappling with four consecutive losses. The home side is heavily favored, not just by form but also by the numbers: an 84% probability of winning, with expected goals (xG) of 2.72 compared to the visitors' 0.66. This clash pits Dinamo's possession-heavy, high-pressing style against Lokomotiva's low-block, direct approach.
Despite Lokomotiva's struggles, the head-to-head record since 2023 offers a glimmer of competitive spirit: four wins for Dinamo, two draws, and two losses in eight encounters. However, in the broader context, Dinamo's superiority is clear, especially with a 3.1 goal average per meeting, suggesting that Lokomotiva's chances are slim. The model's most likely outcomes are dominant home victories—2-0 or 3-0—mirroring the expectation of Dinamo's control over proceedings.
The Over 2.5 goals market is enticing at 66%, aligning with both the historical goal pattern and Dinamo's attacking metrics. With Lokomotiva's defensive frailties (xGA of 1.9 per match), the hosts are primed to exploit any lapse in concentration. Yet, caution is advised on the "both teams to score" market, with only a 45% chance, indicating that Lokomotiva's offensive threat is limited.
In this context, Dinamo's high-press strategy should overwhelm Lokomotiva, whose recent form shows vulnerability. The expected result leans heavily toward a comprehensive victory for the home side, with Dinamo Zagreb to win and over 2.5 goals standing out as the value angle, capturing both the likely dominance and the potential for multiple goals.
01 · 2 legs
02 · 3 legs
03 · 4 legs
No odds available yet.
Head-to-head based on Croatian HNL 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 | Dinamo Zagreb | Lokomotiva Zagreb |
|---|---|---|
| Points | 13 | 6 |
| xPoints | 11.3 | 6.4 |
| xG per match | 2.6 | 1.1 |
| xGA per match | 0.48 | 1.9 |
| xG within 8s of winning the ball | 0.28 | 0.13 |
| xGA within 8s of losing the ball | 0.09 | 0.44 |
| Playing style | Dinamo Zagreb | Lokomotiva Zagreb |
|---|---|---|
| Build-up efficiency | 0.32 | 0.28 |
| Field tilt | 0.82 | 0.32 |
| xT per match | 1.7 | 0.69 |
| xTA per match | 0.45 | 1.4 |
| Won balls, offensive half | 31 | 22 |
| Pressing intensity | 0.2 | 0.24 |
| Pressing efficiency | 0.37 | 0.3 |
| Pressing efficiency, offensive half | 0.34 | 0.26 |
| Entries into the box per match | 20 | 8 |
| Entries into the box against | 4 | 18 |
| Pass completion % | 0.8 | 0.7 |
| Pass completion % under pressure | 0.75 | 0.67 |
| Passes per match | 491 | 257 |
| Passes against per match | 234 | 371 |
| Switches of play per match | 34.9 | 23.1 |
| Long balls per match | 32 | 29 |
| Set pieces | Dinamo Zagreb | Lokomotiva Zagreb |
|---|---|---|
| xG from free kicks | 0.07 | 0.01 |
| Corners per match | 8.2 | 4.6 |
| Corners against per match | 2.4 | 5.6 |
| xG per corner | 0.02 | 0.05 |
| xGA per corner against | 0.03 | 0.05 |
| First touch, offensive corners % | 0.34 | 0.46 |
| First touch, defensive corners % | 0.83 | 0.53 |
| Other | Dinamo Zagreb | Lokomotiva Zagreb |
|---|---|---|
| Throw-in control | 0.7 | 0.62 |
| The goalkeepers | Ivan Nevistić (Dinamo Zagreb) | Josip Posavec (Lokomotiva Zagreb) |
|---|---|---|
| Saves | 3 | 28 |
| Save % | 50% | 70% |
| xG prevented | 52% | 40% |
| Claims | 0 (0%) | 0 (0%) |
The model gives Dinamo Zagreb a 84% win probability. Full 1X2 picture: Dinamo Zagreb 84%, draw 11%, Lokomotiva Zagreb 5%.
The model's most likely final score is 2-0 at 13% probability.
The model rates over 2.5 goals at 66% and under at 34%.
The probability of both teams scoring is 45% 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.