UPCOMING • 5/13/2026

Getafe CF

VS

RCD Mallorca

💡 Engine Insight

Model projects a balanced fixture with moderate goal expectancy. No extreme value detected across primary markets.

DRAW RISK
⚡ SpinBonus EV Engine™
BEST: Under 2.5 +1.9%
Match Result (1X2)
Home Win
Model: 30.7% • Implied: 31.2%
-1.5%
⚖️ FAIR
Draw
Model: 29.5% • Implied: 31.0%
-4.9%
— NO EDGE
Away Win
Model: 39.8% • Implied: 39.8%
0%
⚖️ FAIR
📊 Over/Under 2.5
Over 2.5
Model: 35.9% • Implied: 36.1%
-0.6%
⚖️ FAIR
Under 2.5
Model: 64.1% • Implied: 62.9%
+1.9%
✅ VALUE
🎯 Both Teams to Score
Yes
Model: 42.7% • Implied: 42.6%
+0.3%
⚖️ FAIR
No
Model: 57.3% • Implied: 56.4%
+1.5%
✅ VALUE
💡 +EV Detected: Optimize Your Market Edge

Our model identified a +1.9% edge on Under 2.5. To effectively capture this mathematical value without losing returns to bookmaker margins (vig), this transaction should strictly be executed on a low-commission exchange.

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🟢 HIGH CONFIDENCE76%
📈 7 matches analyzedStrong data foundation: 7 matches analyzed with xG metrics.

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📖 Match Preview & Analysis

The Primera Division clash between Getafe CF and RCD Mallorca arrives with a clear statistical narrative. Our Poisson regression model projects RCD Mallorca as a slight edge, assigning them a 39.8% probability of winning, versus 30.7% for Getafe CF. A draw sits at 29.5%.

Recent form favors RCD Mallorca. Getafe CF has 1 wins and 2 losses in their last 5 fixtures, while RCD Mallorca records 2 wins and 1 losses over a similar span.

Model Insight: Model projects a balanced fixture with moderate goal expectancy. No extreme value detected across primary markets.

This match profiles as a true toss-up. Double chance and BTTS markets often yield better Expected Value than 1X2 in matches with this probability spread.

Explore More
See where Getafe CF & RCD Mallorca stand in Primera Division
Primera Division Table →More Fixtures

💬 Match Discussion(0)

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🧮 How was this prediction calculated?

Win probabilities for Getafe CF vs RCD Mallorca are produced by a Poisson regression model using each side's attack and defence rates against league average. The expected goal counts (λ values) feed a 7×7 score matrix; we then sum the cells to get 1X2, Over/Under and BTTS probabilities. Expected Value is calculated by comparing model probability to the bookmaker implied probability after stripping the overround.

# Poisson per-team expected goals
λ_home = avg_home_goals × home_attack × away_defence
λ_away = avg_away_goals × away_attack × home_defence
# Probability of exact score (h, a)
P(h, a) = (e^-λ_home · λ_home^h / h!) · (e^-λ_away · λ_away^a / a!)
# Expected Value
EV % = (model_probability × decimal_odds − 1) × 100
Confidence
HIGH · 76%
Matches Analysed
7
xG Trend
1.00
H2H Avg Goals
2.3
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