01 · 2 legs
Safe
- Double chance Sevilla FC or draw (X2)64%
- Under 3.5 goals74%
La LigaEstadi Ciutat de València, Valencia17°10 km/h
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Sofia Andersson · · The model's read on the match · How the predictions work
TEXT: The duel between Levante and Sevilla FC looks set to be defined by contrasting styles, with the hosts leaning on a low defensive line and direct play, while the visitors focus on controlling possession. The model leans slightly towards Sevilla, giving them a 38% chance of victory compared to Levante's 31%. However, the margin is razor-thin, and the draw at 31% is a tantalizing possibility.
Despite Levante's two wins in the last two meetings, the small sample size of these head-to-head results should not overshadow the current form and statistical indicators. Sevilla's 13 points and expected points of 9.8 reveal a more robust performance than Levante's actual 5 points and xPoints of 6.2. Yet, the hosts have shown some offensive promise with an xG per match of 1.1, slightly edging Sevilla's 1.0.
Defensively, the visitors seem more solid. Sevilla's xGA of 1.3 per match is notably better than Levante's 1.9, suggesting they can absorb Levante's attacks more efficiently, especially given the possession they are likely to command. This defensive edge, combined with their controlled play, points toward a narrow victory for Sevilla, likely aligning with a 0-1 scoreline — the model's second-most likely outcome at 10%.
The betting angle shines on the under 2.5 goals market, with a probability of just 47% for over 2.5 goals, indicating a low-scoring affair. This is a calculated stance, not a guarantee, but one that aligns with the numbers and the game's likely rhythm.
01 · 2 legs
02 · 3 legs
03 · 4 legs
Bets where the model's probability beats what the odds imply (EV+).
| Bookmaker | 1 · Levante | X | 2 · Sevilla FC |
|---|---|---|---|
| Betsafe | 2.65 | EV+ 4% 3.30 | 2.65 |
| Nordicbet | 2.65 | EV+ 4% 3.30 | 2.65 |
| Pinnacle | 2.68 | EV+ 5% 3.32 | EV+ 2% 2.72 |
Odds updated 3 Oct, 07:36
Head-to-head based on La Liga data since 2022.
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 | Levante | Sevilla FC |
|---|---|---|
| Points | 5 | 13 |
| xPoints | 6.2 | 9.8 |
| xG per match | 1.1 | 1 |
| xGA per match | 1.9 | 1.3 |
| xG within 8s of winning the ball | 0.21 | 0.24 |
| xGA within 8s of losing the ball | 0.36 | 0.38 |
| Playing style | Levante | Sevilla FC |
|---|---|---|
| Build-up efficiency | 0.32 | 0.29 |
| Field tilt | 0.31 | 0.47 |
| xT per match | 0.64 | 0.74 |
| xTA per match | 0.84 | 0.82 |
| Won balls, offensive half | 22 | 34 |
| Pressing intensity | 0.22 | 0.24 |
| Pressing efficiency | 0.22 | 0.26 |
| Pressing efficiency, offensive half | 0.19 | 0.22 |
| Entries into the box per match | 8 | 11 |
| Entries into the box against | 12 | 10 |
| Pass completion % | 0.75 | 0.7 |
| Pass completion % under pressure | 0.67 | 0.68 |
| Passes per match | 297 | 258 |
| Passes against per match | 493 | 397 |
| Switches of play per match | 24.5 | 22.1 |
| Long balls per match | 30 | 31 |
| Set pieces | Levante | Sevilla FC |
|---|---|---|
| xG from free kicks | 0.03 | 0.03 |
| Corners per match | 3 | 3.2 |
| Corners against per match | 5.8 | 3.4 |
| xG per corner | 0.05 | 0.02 |
| xGA per corner against | 0.02 | 0.03 |
| First touch, offensive corners % | 0.33 | 0.43 |
| First touch, defensive corners % | 0.4 | 0.58 |
| Other | Levante | Sevilla FC |
|---|---|---|
| Throw-in control | 0.64 | 0.71 |
| The goalkeepers | Mathew Ryan (Levante) | Odysseas Vlachodimos (Sevilla FC) |
|---|---|---|
| Saves | 23 | 20 |
| Save % | 66% | 69% |
| xG prevented | 39% | 46% |
| Claims | 0 (0%) | 0 (0%) |
The model gives Sevilla FC a 38% win probability. Full 1X2 picture: Levante 31%, draw 31%, Sevilla FC 38%.
The model's most likely final score is 1-1 at 13% probability.
The model rates over 2.5 goals at 47% and under at 53%.
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.