UPCOMING • 5/17/2026

Santos FC

VS

Coritiba FBC

💡 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 +2.2%
Match Result (1X2)
Home Win
Model: 29.9% • Implied: 30.4%
-1.7%
⚖️ FAIR
Draw
Model: 31.2% • Implied: 32.6%
-4.4%
— NO EDGE
Away Win
Model: 38.9% • Implied: 39.0%
-0.1%
⚖️ FAIR
📊 Over/Under 2.5
Over 2.5
Model: 30.9% • Implied: 31.4%
-1.5%
⚖️ FAIR
Under 2.5
Model: 69.1% • Implied: 67.6%
+2.2%
✅ VALUE
🎯 Both Teams to Score
Yes
Model: 38.5% • Implied: 38.6%
-0.2%
⚖️ FAIR
No
Model: 61.5% • Implied: 60.4%
+1.8%
✅ VALUE
💡 +EV Detected: Optimize Your Market Edge

Our model identified a +2.2% 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 CONFIDENCE91%
📈 7 matches analyzedStrong data foundation: 7 matches analyzed with xG metrics.

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📖 Match Preview & Analysis

The Campeonato Brasileiro Série A clash between Santos FC and Coritiba FBC arrives with a clear statistical narrative. Our Poisson regression model projects Coritiba FBC as a slight edge, assigning them a 38.9% probability of winning, versus 29.9% for Santos FC. A draw sits at 31.2%.

Recent form favors Coritiba FBC. Santos FC has 1 wins and 2 losses in their last 5 fixtures, while Coritiba FBC 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 Santos FC & Coritiba FBC stand in Campeonato Brasileiro Série A
Campeonato Brasileiro Série A Table →More Fixtures

💬 Match Discussion(0)

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🧮 How was this prediction calculated?

Win probabilities for Santos FC vs Coritiba FBC 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 · 91%
Matches Analysed
7
xG Trend
0.90
H2H Avg Goals
2.1
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