01 · 2 legs
Safe
- Lazio to win55%
- Over 1.5 goals77%
Serie AStadio Olimpico, Roma16°7 km/h
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Anna Karlsson · · A data-driven preview · How the predictions work
55% is a compelling figure. That's the model's probability for Lazio to take all three points against Monza. With the home side unbeaten in their last five league outings, momentum seems to favor them. Yet, Monza's direct style could pose challenges, especially given their xG advantage at 1.8 per match compared to Lazio's 1.3. These attacking metrics should not be overlooked, particularly in a tight contest like this.
Despite Lazio's head-to-head dominance, with two wins in as many encounters since 2021, the sample size is too small to decisively inform this matchup. Instead, Monza's potential to disrupt through direct play and their superior xPoints hint at a more complex narrative than the odds might suggest. Lazio's anticipated goal output stands at 1.76, against Monza's 1.01, pointing towards a narrow victory. Yet, the slim margin leaves room for variance, and the 11% likelihood for a 1-1 draw underscores this tension.
For the betting desk, the sharpest edge lies with Monza at odds of 5.75 with LeoVegas, offering an 18% edge by the model's rating. While the over/under leans slightly towards over 2.5 goals at 52%, the true intrigue lies in whether Monza can snatch a result against the odds.
01 · 2 legs
02 · 3 legs
03 · 4 legs
Bets where the model's probability beats what the odds imply (EV+).
| Bookmaker | 1 · Lazio | X | 2 · Monza |
|---|---|---|---|
| Betsafe | 1.58 | 3.85 | EV+ 21% 5.90 |
| LeoVegas | 1.57 | 4.00 | EV+ 18% 5.75 |
| Nordicbet | 1.60 | 3.90 | EV+ 22% 5.95 |
Odds updated 3 Oct, 07:37
Head-to-head based on Serie A data since 2021.
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 | Lazio | Monza |
|---|---|---|
| Points | 10 | 4 |
| xPoints | 6 | 8.5 |
| xG per match | 1.3 | 1.8 |
| xGA per match | 1.2 | 1.4 |
| xG within 8s of winning the ball | 0.08 | 0.14 |
| xGA within 8s of losing the ball | 0.34 | 0.23 |
| Playing style | Lazio | Monza |
|---|---|---|
| Build-up efficiency | 0.3 | 0.29 |
| Field tilt | 0.59 | 0.53 |
| xT per match | 0.98 | 1.1 |
| xTA per match | 1.1 | 1 |
| Won balls, offensive half | 19 | 26 |
| Pressing intensity | 0.22 | 0.21 |
| Pressing efficiency | 0.25 | 0.25 |
| Pressing efficiency, offensive half | 0.2 | 0.2 |
| Entries into the box per match | 9 | 12 |
| Entries into the box against | 11 | 14 |
| Pass completion % | 0.8 | 0.76 |
| Pass completion % under pressure | 0.75 | 0.68 |
| Passes per match | 351 | 331 |
| Passes against per match | 434 | 407 |
| Switches of play per match | 20.5 | 26.5 |
| Long balls per match | 22 | 33 |
| Set pieces | Lazio | Monza |
|---|---|---|
| xG from free kicks | 0 | 0.06 |
| Corners per match | 4.9 | 4.5 |
| Corners against per match | 4.2 | 4.2 |
| xG per corner | 0.03 | 0.02 |
| xGA per corner against | 0.06 | 0.05 |
| First touch, offensive corners % | 0.4 | 0.41 |
| First touch, defensive corners % | 0.24 | 0.43 |
| Other | Lazio | Monza |
|---|---|---|
| Throw-in control | 0.68 | 0.76 |
| The goalkeepers | Christos Mandas (Lazio) | Noel Max Joachim Törnqvist (Monza) |
|---|---|---|
| Saves | 16 | 7 |
| Save % | 84% | 88% |
| xG prevented | 88% | 91% |
| Claims | 0 (0%) | 0 (0%) |
The model gives Lazio a 55% win probability. Full 1X2 picture: Lazio 55%, draw 25%, Monza 20%.
The model's most likely final score is 1-1 at 11% probability.
The model rates over 2.5 goals at 52% and under at 48%.
The probability of both teams scoring is 53% 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.

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Hämta bonusPredictions come from PlaymakerAI's match model and reflect the model's assessment — not betting advice. Gamble responsibly.