Saturday, 05/09/2026 at 18:30
Full timeHull City 0:0 Aston Villa
Hull City were the model's likeliest winner before kick-off at 39%. It finished 0–0. The biggest difference was Hull City's attack: 0.57 xG against 1.44 projected (−0.87). Aston Villa produced 1.93 xG against 1.25 projected (+0.68).
The model against the result
- Hull City
- 39%
- Draw
- 30% What happened
- Aston Villa
- 30%
Data coverage One of these teams has only 2 matches in the model window, short of the 10 the model wants. Read the projection as a direction rather than as a number.
Projected vs produced
Hull City produced 0.87 xG less than projected
Projected before kick-off Produced on the night
The shots behind it
- Shots
- 11
- 13
- On target
- 4
- 1
- Inside the box
- 4
- 10
- xG per shot
- 0.05
- 0.14
- Open play xG
- 0.54
- 1.55
- Set-piece xG
- 0.06
- 0.21
- 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: 0.59 for Hull City and 1.74 for Aston Villa.
Shot map
Both teams shown attacking the same goal for comparison.
All shots
24 shots · 2.36 xG
Hover, focus or tap a shot to read it.
- Hull City
- Aston Villa
- Filled = goal
- Dot area = xG (the smallest chances drawn at a minimum size)
Recent form
0.99 xG created 1.55 xGA
1.00 xG created 1.73 xGA
- L 0.32 created, 0.99 conceded against Tottenham Hotspur
- D 1.44 created, 1.79 conceded against Burnley
- W 1.85 created, 1.43 conceded against Liverpool
- W 1.77 created, 1.34 conceded against Manchester City
- L 0.29 created, 3.77 conceded against Brighton & Hove Albion
- L 0.33 created, 1.04 conceded against Arsenal
xG created xG conceded (xGA) W / D / L: the match result
Pre-match model & market record
8 opportunities flagged3 won5 lost
- Lost
- Lost
- Won
- Won
- Lost
- Won
- Lost
- Lost
View pre-match record Hide pre-match record
| Selection | Price | Edge | Result |
|---|---|---|---|
| Hull City to win | 4.10 | +61.2% | Lost |
| Hull City 2+ goals | 3.25 | +40.3% | Lost |
| Aston Villa at most 1 goal | 1.83 | +16.7% | Won |
| Aston Villa not to score | 4.50 | +15.4% | Won |
| Hull City to score | 1.44 | +13.7% | Lost |
| Draw | 3.60 | +9.1% | Won |
| Both teams to score | 1.75 | +5.6% | Lost |
| Over 1.5 goals | 1.29 | +1.7% | Lost |
Pre-match model vs market
| Outcome | Model | Market | Difference | Fair odds |
|---|---|---|---|---|
| Hull City | 39.3% | 23.0% | +16.3 pp | 2.54 |
| Draw | 30.3% | 26.2% | +4.2 pp | 3.30 |
| Aston Villa | 30.4% | 50.9% | −20.5 pp | 3.29 |
Other markets
| Outcome | Model | Market | Difference | Fair odds |
|---|---|---|---|---|
| Hull City to score | 78.8% | 64.5% | +14.3 pp | 1.27 |
| Hull City not to score | 21.2% | 35.5% | −14.3 pp | 4.71 |
| Aston Villa to score | 74.4% | 79.2% | −4.8 pp | 1.34 |
| Aston Villa not to score | 25.6% | 20.8% | +4.8 pp | 3.90 |
| Both teams to score | 60.3% | 53.3% | +7.0 pp | 1.66 |
| Both teams not to score | 39.7% | 46.7% | −7.0 pp | 2.52 |
| Hull City 2+ goals | 43.2% | 29.1% | +14.1 pp | 2.32 |
| Hull City at most 1 goal | 56.8% | 70.9% | −14.1 pp | 1.76 |
| Aston Villa 2+ goals | 36.3% | 50.0% | −13.7 pp | 2.75 |
| Aston Villa at most 1 goal | 63.7% | 50.0% | +13.7 pp | 1.57 |
| Over 1.5 goals | 79.1% | 74.5% | +4.7 pp | 1.26 |
| Under 1.5 goals | 20.9% | 25.5% | −4.7 pp | 4.79 |
| Over 2.5 goals | 51.7% | 50.0% | +1.7 pp | 1.93 |
| Under 2.5 goals | 48.3% | 50.0% | −1.7 pp | 2.07 |
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
· 1 warningShow Hide
- Fit window
- the last 20 matches, recency weighted (a match 107 days old counts half)
- Hull City sample
- 2 matches
- Aston Villa sample
- 20 matches
- Computed
- 3 hours before kick-off
- Prices taken
- 3 hours before kick-off
Warnings
- Hull City has only 2 matches in the database. Below 10 matches the estimate is very unreliable.
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.