Saturday, 05/09/2026 at 20:45
Full timeRoma 2:1 Atalanta
Roma were the model's likeliest winner before kick-off at 54%. They won 2–1. The biggest difference was Roma's attack: 2.97 xG against 1.67 projected (+1.30).
Goals
- 47' Éderson Atalanta · 0.08 xG chance 0–1
- 89' Mario Hermoso Roma · 0.07 xG chance 1–1
- 90' Matías Soulé Roma · 0.02 xG chance 2–1
The model against the result
- Roma
- 54% What happened
- Draw
- 28%
- Atalanta
- 17%
Data coverage Both teams have the full 20-match model window available.
Projected vs produced
Roma produced 1.30 xG more than projected
Projected before kick-off Produced on the night
The shots behind it
- Shots
- 39
- 6
- On target
- 10
- 2
- Inside the box
- 28
- 6
- xG per shot
- 0.08
- 0.13
- Open play xG
- 2.75
- 0.76
- Set-piece xG
- 0.45
- 0.03
- Penalties
- —
- —
Shot-level xG may differ from the published match total
The provider publishes the match total separately from its shot-by-shot values. Those values are rounded to two decimals and, leaving out penalties and own goals, add up to its non-penalty xG: 3.24 for Roma and 0.77 for Atalanta.
Shot map
Both teams shown attacking the same goal for comparison.
All shots
45 shots · 3.99 xG
Hover, focus or tap a shot to read it.
- Roma
- Atalanta
- Filled = goal
- Dot area = xG (the smallest chances drawn at a minimum size)
Recent form
xG created xG conceded (xGA) W / D / L: the match result
Head to head
Pre-match model & market record
2 opportunities flagged0 won2 lost
- Lost
- Lost
View pre-match record Hide pre-match record
| Selection | Price | Edge | Result |
|---|---|---|---|
| Draw | 4.00 | +12.5% | Lost |
| Under 2.5 goals | 2.20 | +12.4% | Lost |
Pre-match model vs market
| Outcome | Model | Market | Difference | Fair odds |
|---|---|---|---|---|
| Roma | 54.5% | 56.6% | −2.1 pp | 1.84 |
| Draw | 28.1% | 23.6% | +4.5 pp | 3.56 |
| Atalanta | 17.4% | 19.9% | −2.5 pp | 5.75 |
Other markets
| Outcome | Model | Market | Difference | Fair odds |
|---|---|---|---|---|
| Roma to score | 83.7% | 82.8% | +0.9 pp | 1.19 |
| Roma not to score | 16.3% | 17.2% | −0.9 pp | 6.13 |
| Atalanta to score | 62.8% | 60.8% | +2.0 pp | 1.59 |
| Atalanta not to score | 37.2% | 39.2% | −2.0 pp | 2.69 |
| Both teams to score | 54.2% | 54.7% | −0.5 pp | 1.85 |
| Both teams not to score | 45.8% | 45.3% | +0.5 pp | 2.18 |
| Roma 2+ goals | 51.5% | 51.5% | +0.1 pp | 1.94 |
| Roma at most 1 goal | 48.5% | 48.5% | −0.1 pp | 2.06 |
| Atalanta 2+ goals | 22.8% | 25.0% | −2.2 pp | 4.39 |
| Atalanta at most 1 goal | 77.2% | 75.0% | +2.2 pp | 1.29 |
| Over 1.5 goals | 77.1% | 78.0% | −0.9 pp | 1.30 |
| Under 1.5 goals | 22.9% | 22.0% | +0.9 pp | 4.37 |
| Over 2.5 goals | 48.9% | 56.9% | −8.0 pp | 2.04 |
| Under 2.5 goals | 51.1% | 43.1% | +8.0 pp | 1.96 |
Prices and probabilities are the ones stored before kick-off; nothing here is recalculated. Edge is the model's probability times the price, minus one, so a flagged outcome that lost is the ordinary case rather than a contradiction.
Model details
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- Fit window
- the last 20 matches, recency weighted (a match 107 days old counts half)
- Roma sample
- 20 matches
- Atalanta sample
- 20 matches
- Computed
- 5 hours before kick-off
- Prices taken
- 5 hours before kick-off
Limitations
The model reads expected goals and nothing else. It does not know the lineups, who is injured or suspended, what either side has to play for, the weather, or how congested the schedule around this match is.