UPCOMING • 5/16/2026

CD Nacional

VS

Vitória SC

💡 Engine Insight

Statistical models project a highly competitive encounter. Neither side holds a clear edge, suggesting potential value in draw or BTTS markets.

TIGHT CONTEST
⚡ SpinBonus EV Engine™
BEST: Yes +1.7%
Match Result (1X2)
Home Win
Model: 39.5% • Implied: 39.5%
-0.1%
⚖️ FAIR
Draw
Model: 24.2% • Implied: 26.0%
-6.9%
— NO EDGE
Away Win
Model: 36.3% • Implied: 36.5%
-0.5%
⚖️ FAIR
📊 Over/Under 2.5
Over 2.5
Model: 58.3% • Implied: 57.4%
+1.6%
✅ VALUE
Under 2.5
Model: 41.7% • Implied: 41.6%
+0.2%
⚖️ FAIR
🎯 Both Teams to Score
Yes
Model: 60.8% • Implied: 59.8%
+1.7%
✅ VALUE
No
Model: 39.2% • Implied: 39.2%
-0.1%
⚖️ FAIR
💡 +EV Detected: Optimize Your Market Edge

Our model identified a +1.7% edge on Yes. 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 CONFIDENCE85%
📈 5 matches analyzedStrong data foundation: 5 matches analyzed with xG metrics.

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📖 Match Preview & Analysis

The Primeira Liga clash between CD Nacional and Vitória SC arrives with a clear statistical narrative. Our Poisson regression model projects CD Nacional as a slight edge, assigning them a 39.5% probability of winning, versus 36.3% for Vitória SC. A draw sits at 24.2%.

Recent form favors CD Nacional. CD Nacional has 2 wins and 2 losses in their last 5 fixtures, while Vitória SC records 1 wins and 2 losses over a similar span.

Model Insight: Statistical models project a highly competitive encounter. Neither side holds a clear edge, suggesting potential value in draw or BTTS 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 CD Nacional & Vitória SC stand in Primeira Liga
Primeira Liga Table →More Fixtures

💬 Match Discussion(0)

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🧮 How was this prediction calculated?

Win probabilities for CD Nacional vs Vitória SC 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 · 85%
Matches Analysed
5
xG Trend
1.60
H2H Avg Goals
4.6
📊
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