01 · 2 legs
Safe
- Juventus to win54%
- Over 1.5 goals78%
Serie AAllianz Stadium, Torino21°3 km/h
Läs på svenskaSofia Andersson · · The model's read on the match · How the predictions work
TEXT: Juventus' high pressing and possession-heavy style should tilt the balance in their favor against Atalanta. The home side's 1.74 expected goals compared to Atalanta's 1.12 reflect a significant edge, with the model leaning towards a Juventus win at a 54% probability. Although the head-to-head record since 2021 is a balanced 1 win, 2 draws, and 1 loss for Juventus, the small sample size makes it less reliable than current form and statistical expectations.
The Bianconeri have been strong at their fortress, winning 55% of their home matches in the given sample. Their defensive solidity, as evidenced by their 0.3 expected goals against per match, starkly contrasts with the visitors' 2.3 xGA, highlighting a vulnerability in Atalanta's back line against high-caliber opposition. This should give the hosts a clear path to goal and an opportunity to exploit this weakness.
Most likely scorelines such as 1-1 and 2-1 show that while Atalanta can mount a challenge, Juventus' offensive capabilities, driven by their tactical setup, make them more likely to clinch a narrow victory. With both teams to score at a 56% chance and an over 2.5 goals probability of 54%, the data suggests a competitive affair with goals on both sides.
However, despite the relatively high chance of over 2.5 goals, the model suggests a 1-1 finish as the most plausible outcome. The odds favor Juventus, and considering their home advantage and substantial xPoints edge (6.4 vs 1.7), the value lies in backing them to secure the win.
01 · 2 legs
02 · 3 legs
03 · 4 legs
Bets where the model's probability beats what the odds imply (EV+).
| Bookmaker | 1 · Juventus | X | 2 · Atalanta |
|---|---|---|---|
| Betsafe | 1.70 | 3.85 | EV+ 13% 4.85 |
| Betsson | 1.70 | 3.85 | EV+ 14% 4.90 |
| Nordicbet | 1.70 | 3.85 | EV+ 14% 4.90 |
| Pinnacle | 1.71 | 3.87 | EV+ 17% 5.03 |
Odds updated 15 Sept, 05:36
1.63 → 1.71
3.95 → 3.87
5.18 → 5.03
1.71 → 1.80
Pinnacle · 4 recorded price levels · 12/09/2026 → 15/09/2026 · fixed scale 5 percentage points
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 | Juventus | Atalanta |
|---|---|---|
| Points | 7 | 6 |
| xPoints | 6.4 | 1.7 |
| xG per match | 1.7 | 0.62 |
| xGA per match | 0.3 | 2.3 |
| xG within 8s of winning the ball | 0.61 | 0.07 |
| xGA within 8s of losing the ball | 0.09 | 0.21 |
| Playing style | Juventus | Atalanta |
|---|---|---|
| Build-up efficiency | 0.32 | 0.33 |
| Field tilt | 0.71 | 0.33 |
| xT per match | 1.5 | 0.7 |
| xTA per match | 0.32 | 1.9 |
| Won balls, offensive half | 31 | 14 |
| Pressing intensity | 0.23 | 0.24 |
| Pressing efficiency | 0.28 | 0.18 |
| Pressing efficiency, offensive half | 0.25 | 0.12 |
| Entries into the box per match | 15 | 9 |
| Entries into the box against | 6 | 23 |
| Pass completion % | 0.81 | 0.81 |
| Pass completion % under pressure | 0.76 | 0.77 |
| Passes per match | 425 | 399 |
| Passes against per match | 310 | 537 |
| Switches of play per match | 28.9 | 25.2 |
| Long balls per match | 29 | 31 |
| Set pieces | Juventus | Atalanta |
|---|---|---|
| xG from free kicks | 0 | 0 |
| Corners per match | 9.5 | 2 |
| Corners against per match | 2 | 6.6 |
| xG per corner | 0.04 | 0.01 |
| xGA per corner against | 0.01 | 0.04 |
| First touch, offensive corners % | 0.66 | 0.5 |
| First touch, defensive corners % | 0.67 | 0.25 |
| Other | Juventus | Atalanta |
|---|---|---|
| Throw-in control | 0.68 | 0.73 |
| The goalkeepers | Guglielmo Vicario (Juventus) | Marco Carnesecchi (Atalanta) |
|---|---|---|
| Saves | 5 | 19 |
| Save % | 83% | 86% |
| xG prevented | 89% | 78% |
| Claims | 0 (0%) | 0 (0%) |
The model gives Juventus a 54% win probability. Full 1X2 picture: Juventus 54%, draw 22%, Atalanta 23%.
The model's most likely final score is 1-1 at 11% probability.
The model rates over 2.5 goals at 54% and under at 46%.
The probability of both teams scoring is 56% 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.