Fiorentina vs AS Roma prediction for May 4, 2026: Our Monte Carlo simulation ran 5,000 game iterations and projects AS Roma 1.67 - Fiorentina 1.4. AS Roma is favored with a 65.0% win probability. Expected total goals: 3.1..
AS Roma
1.67
Projected Goals
VS
3.1 total
Fiorentina
1.4
Projected Goals
Match Outcome Probabilities
AS RomaDrawFiorentina
Calibrated accuracy at this confidence: 75.5% (1,051 games)
Projected Goals Range 10th – 90th percentile
Fiorentina
0.61.42.2
AS Roma
0.91.72.4
Projected
AS Roma 1.67 — Fiorentina 1.4
Actual
AS Roma 4 — Fiorentina 0
Expected Goals (xG)
AS Roma1.66
Fiorentina1.35
17.3Shots15.3
6.4On Target5.5
5.7Corners5.6
Goal Probabilities
Over 0.5
96.3%
Over 1.5
81.1%
Over 2.5
49.1%
Over 3.5
28.2%
Under 2.5
50.9%
BTTS
32.0%
Most Likely Scores
1-1
12.8%
1-0
9.8%
2-1
9.4%
2-0
8.2%
0-0
7.5%
Match Context
SERMedium
AS Roma
1.54
Draw
4.23
Fiorentina
6.65
AI Intelligence Analysis
NEUTRALRED ZONE42.2% WR (n=71)
Market and model are perfectly aligned (64.95% vs 64.94% home prob), indicating no independent edge; home ML in RED zone (42.2% WR) regardless of team quality advantage.
Key Factors
- Perfect market alignment: Model 64.95% vs market 64.94% home probability (0.01% edge, statistical rounding error)
- Form gap: Roma W-W-L-W-W (3W-2L) vs Fiorentina W-W-L-L-L (1W-4L) suggests Roma momentum advantage
- Home ML RED zone: 42.2% WR historical (n=71), rendering home favorite a structural losing bet
- xG quality: Roma 1.66 vs Fiorentina 1.35 (0.31 gap, modest not dominant) reflects mid-range quality advantage
- Draw risk: 16.69% draw probability kills ~17% of ML outcomes
Risk Factors
- No edge: Zero probability advantage (0.01%) means market has correctly priced game
- Home ML curse: RED zone classification applies regardless of team quality; draws structural killer
- Fiorentina resilience: 15th-place team but with potential to spring upset at home-opponent-level teams
RED ZONEDRAW RISKNEUTRALMARKET ALIGNED
Edge Analysis
Moneyline
AS Roma 65.0%
--
Total
3.1
--
How this prediction was generated: This page shows output from the Olympus Bets Soccer Monte Carlo engine. Each game is simulated 5,000 times using real-time team data, injury reports, and current odds. Probabilities are calibrated using Bayesian methods and sized via the Kelly Criterion. Full methodology →