Statistics / Football / Spain. La Liga / Villarreal vs Sevilla

Villarreal vs Sevilla Statistics & Analysis

Villarreal Villarreal
May 13, 2026 - 17:00
2 1.64
3 0.77
xG Accuracy: 49%
Sevilla Sevilla
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Tracked markets vs full-time result

Each row compares the model’s highlighted side (or lean) to what happened at full time.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Over 2.5 (5 goals) ✖ Incorrect
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 Villarreal Sevilla ✖ Incorrect
  • Correct Score Insights 1-0 2-3 ✖ Incorrect

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: La Liga
  • Fixture: Villarreal vs Sevilla
  • Kickoff: 2026-05-13 16:00:00
  • 1X2 (model): Home 56.7% · Draw 27.4% · Away 15.9%
  • xG (showing): Villarreal 1.64 — Sevilla 0.77 (total xG ≈ 2.41)
  • Primary / headline line (Betting Primary Pick when shown): BTTS No
  • Model: 55.2% · Implied: 44.2% · Probability edge: +11.0 pts · Est. EV: +21.4%
  • BTTS (model): Yes 44.8% · No 55.2%
  • Correct score (top bin): 1-0 (14.7%)

Totals and BTTS are evaluated against current market prices where available.

Early match state can move realised goals away from pre-kick projections.

Best Bet + Reason

Primary angle highlighted on the page: BTTS No.

We separate probability edge (model minus implied, in points of probability) from estimated EV (economic edge at the best price shown on the page).

When several markets sit near +EV, keep stakes small — correlation means edges do not add cleanly.

FAQ

Is the most likely correct score a good bet?

Usually no as a standalone bet: the “most likely” scoreline is still a low absolute probability tail event (often single digits, sometimes low teens). Use it as context; keep any correct-score stake in the “fun / small” bucket.

Why might 1X2 look unattractive while totals do not?

Tight 1X2 prices often embed a fair three-way split, so EV on match-winner can sit negative even when Over/Under or BTTS still diverges from the model — compare the 1X2 row on the market cards to O/U and BTTS.

Who has the edge in the match-winner market?

Use the 1X2 model percentages in the summary and the 1X2 market card: the side with the highest model % is the model lean, but check EV — a lean can still be -EV after prices.

What changes first if odds move?

Implied probabilities and EV move immediately with price; model probabilities in this snapshot do not update until the pipeline is re-run. Refresh after material line moves.

Risk Factors

  • Price movement: implied probabilities and EV move with odds.
  • Sample / data gaps: low-information leagues widen forecast bands.
  • In-play state: goals and red cards are not modelled here.
  • Scoreline variance: the most likely scoreline is still usually a low absolute probability outcome (often well below 20%).

Methodology

  • Inputs: Same structured facts bundle as the public prediction page (xG / Poisson snapshot, market EV where available, decision engine v2).
  • Compliance: Educational framing only; not personalised advice.

Last Updated

May 17, 2026 (UTC)

How to use this
  • Focus on the Primary line when you want one actionable idea.
  • Do not parlay many thin-edge picks together; edges do not add reliably.
  • Treat longshots as optional, high-stake-sizing plays only.

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Back to Statistics
La Liga La Liga — Standings
# TEAM MP W D L PTS
1 Barcelona 36 30 1 5 91
2 Real Madrid 36 25 5 6 80
3 Villarreal 36 21 6 9 69
4 Atletico Madrid 36 20 6 10 66
5 Real Betis 36 14 15 7 57
6 Celta Vigo 36 13 11 12 50
7 Getafe 36 14 6 16 48
8 Real Sociedad 36 11 12 13 45
9 Athletic Club 36 13 5 18 44
10 Rayo Vallecano 36 10 14 12 44
11 Valencia 36 11 10 15 43
12 Sevilla 36 12 7 17 43
13 Osasuna 36 11 9 16 42
14 Espanyol 36 11 9 16 42
15 Girona 36 9 13 14 40
16 Alaves 36 10 10 16 40
17 Elche 36 9 12 15 39
18 Mallorca 36 10 9 17 39
19 Levante 36 10 9 17 39
20 Oviedo 36 6 11 19 29
# TEAM MP GS GC +/- PTS
1 Barcelona 36 91 32 +59 91
2 Real Madrid 36 72 33 +39 80
3 Villarreal 36 67 43 +24 69
4 Atletico Madrid 36 60 39 +21 66
5 Real Betis 36 56 44 +12 57
6 Real Sociedad 36 55 56 -1 45
7 Celta Vigo 36 51 47 +4 50
8 Elche 36 47 56 -9 39
9 Sevilla 36 46 58 -12 43
10 Mallorca 36 44 55 -11 39
11 Levante 36 44 59 -15 39
12 Osasuna 36 43 47 -4 42
13 Alaves 36 42 54 -12 40
14 Athletic Club 36 40 53 -13 44
15 Espanyol 36 40 53 -13 42
16 Valencia 36 39 51 -12 43
17 Girona 36 38 53 -15 40
18 Rayo Vallecano 36 37 43 -6 44
19 Getafe 36 31 37 -6 48
20 Oviedo 36 26 56 -30 29
# TEAM MP xG xGC +/- PTS
1 Barcelona 36 84.0 43.1 +40.9 91
2 Real Madrid 36 71.8 38.5 +33.3 80
3 Villarreal 36 54.3 42.3 +12.0 69
4 Atletico Madrid 36 54.9 43.9 +11.0 66
5 Real Betis 36 52.2 42.1 +10.1 57
6 Athletic Club 36 46.0 38.4 +7.6 44
7 Valencia 36 46.2 43.7 +2.5 43
8 Celta Vigo 36 48.0 46.0 +2.0 50
9 Rayo Vallecano 36 47.2 45.4 +1.8 44
10 Alaves 36 43.0 45.7 -2.7 40
11 Real Sociedad 36 46.4 50.7 -4.3 45
12 Osasuna 36 43.4 48.1 -4.7 42
13 Espanyol 36 45.2 50.8 -5.6 42
14 Getafe 36 29.9 39.8 -9.9 48
15 Levante 36 47.0 57.4 -10.4 39
16 Girona 36 42.8 53.3 -10.5 40
17 Sevilla 36 36.5 51.4 -14.9 43
18 Mallorca 36 40.1 59.4 -19.3 39
19 Oviedo 36 33.7 53.2 -19.5 29
20 Elche 36 39.8 59.4 -19.6 39
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