Friday, 11/09/2026 at 21:00
Full timeSevilla 1:0 Valencia
Sevilla were the model's likeliest winner before kick-off at 40%. They won 1–0. The biggest difference was Valencia's attack: 0.10 xG against 0.89 projected (−0.79).
Goals
- 81' Juan Iglesias Sevilla · 0.35 xG chance 1–0
The model against the result
- Sevilla
- 40% What happened
- Draw
- 35%
- Valencia
- 26%
Data coverage Both teams have the full 20-match model window available.
Projected vs produced
Valencia produced 0.79 xG less than projected
Projected before kick-off Produced on the night
The shots behind it
- Shots
- 13
- 3
- On target
- 4
- 0
- Inside the box
- 9
- 1
- xG per shot
- 0.09
- 0.02
- Open play xG
- 0.17
- 0.07
- Set-piece xG
- 1.01
- 0.00
- Penalties
- —
- —
Shot-level xG may differ from the published match total
The provider publishes the match total separately from its shot-by-shot values. Those values are rounded to two decimals and, leaving out penalties and own goals, add up to its non-penalty xG: 1.21 for Sevilla and 0.08 for Valencia.
Shot map
Both teams shown attacking the same goal for comparison.
All shots
16 shots · 1.25 xG
Hover, focus or tap a shot to read it.
- Sevilla
- Valencia
- Filled = goal
- Dot area = xG (the smallest chances drawn at a minimum size)
Recent form
1.07 xG created 1.34 xGA
- L 0.72 created, 1.00 conceded against Real Madrid
- L 0.80 created, 1.59 conceded against Celta Vigo
- W 2.19 created, 1.89 conceded against Rayo Vallecano
- W 1.26 created, 1.37 conceded against Athletic Club
- L 0.90 created, 0.93 conceded against Atlético Madrid
- D 0.53 created, 1.23 conceded against Espanyol
1.15 xG created 1.59 xGA
- W 1.67 created, 1.15 conceded against Real Sociedad
- W 1.48 created, 1.52 conceded against Barcelona
- D 0.58 created, 0.66 conceded against Celta Vigo
- L 1.12 created, 0.71 conceded against Real Betis
- L 1.40 created, 1.42 conceded against Deportivo La Coruña
- L 0.66 created, 4.08 conceded against Barcelona
xG created xG conceded (xGA) W / D / L: the match result
Head to head
Pre-match model & market record
6 opportunities flagged3 won3 lost
- Lost
- Won
- Lost
- Won
- Won
- Lost
View pre-match record Hide pre-match record
| Selection | Price | Edge | Result |
|---|---|---|---|
| Draw | 3.40 | +18.6% | Lost |
| Sevilla at most 1 goal | 1.62 | +9.8% | Won |
| Sevilla not to score | 3.75 | +9.2% | Lost |
| Under 2.5 goals | 1.62 | +8.0% | Won |
| Under 1.5 goals | 3.00 | +6.9% | Won |
| Valencia to win | 4.00 | +2.0% | Lost |
Pre-match model vs market
| Outcome | Model | Market | Difference | Fair odds |
|---|---|---|---|---|
| Sevilla | 39.6% | 48.5% | −8.9 pp | 2.53 |
| Draw | 34.9% | 27.8% | +7.1 pp | 2.87 |
| Valencia | 25.5% | 23.7% | +1.9 pp | 3.92 |
Other markets
| Outcome | Model | Market | Difference | Fair odds |
|---|---|---|---|---|
| Sevilla to score | 70.9% | 75.0% | −4.1 pp | 1.41 |
| Sevilla not to score | 29.1% | 25.0% | +4.1 pp | 3.43 |
| Valencia to score | 61.7% | 58.9% | +2.8 pp | 1.62 |
| Valencia not to score | 38.3% | 41.1% | −2.8 pp | 2.61 |
| Both teams to score | 45.7% | 46.7% | −0.9 pp | 2.19 |
| Both teams not to score | 54.3% | 53.3% | +0.9 pp | 1.84 |
| Sevilla 2+ goals | 32.0% | 42.3% | −10.3 pp | 3.12 |
| Sevilla at most 1 goal | 68.0% | 57.7% | +10.3 pp | 1.47 |
| Valencia 2+ goals | 21.8% | 23.4% | −1.6 pp | 4.58 |
| Valencia at most 1 goal | 78.2% | 76.6% | +1.6 pp | 1.28 |
| Over 1.5 goals | 64.4% | 68.2% | −3.8 pp | 1.55 |
| Under 1.5 goals | 35.6% | 31.8% | +3.8 pp | 2.81 |
| Over 2.5 goals | 33.1% | 41.3% | −8.1 pp | 3.02 |
| Under 2.5 goals | 66.9% | 58.7% | +8.1 pp | 1.50 |
Prices and probabilities are the ones stored before kick-off; nothing here is recalculated. Edge is the model's probability times the price, minus one, so a flagged outcome that lost is the ordinary case rather than a contradiction.
Model details
Show Hide
- Fit window
- the last 20 matches, recency weighted (a match 107 days old counts half)
- Sevilla sample
- 20 matches
- Valencia sample
- 20 matches
- Computed
- 10 hours before kick-off
- Prices taken
- 10 hours before kick-off
Limitations
The model reads expected goals and nothing else. It does not know the lineups, who is injured or suspended, what either side has to play for, the weather, or how congested the schedule around this match is.