Friday, 04/09/2026 at 20:45
Full timeLommel SK 0:1 Club Brugge KV
Club Brugge KV were the model's likeliest winner before kick-off at 53%. They won 1–0. The biggest difference was Club Brugge KV's attack: 0.80 xG against 1.96 projected (−1.16). Lommel SK produced 0.65 xG against 1.26 projected (−0.61).
Goals
- 45' Timothy Eyoma (o.g.) Club Brugge KV · 0.32 xG chance 0–1
The model against the result
- Lommel SK
- 22%
- Draw
- 25%
- Club Brugge KV
- 53% What happened
Data coverage One of these teams has only 4 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
Club Brugge KV produced 1.16 xG less than projected
Projected before kick-off Produced on the night
The shots behind it
- Shots
- 7
- 14
- On target
- 2
- 4
- Inside the box
- 5
- 10
- xG per shot
- 0.09
- 0.08
- Open play xG
- 0.59
- 0.91
- Set-piece xG
- 0.05
- 0.21
- Penalties
- —
- —
Lommel SK's shots add up to 0.64 xG and Club Brugge KV's to 1.12; the published figures are 0.65 and 0.80.
Shot map
Both teams shown attacking the same goal for comparison.
All shots
21 shots · 1.76 xG
Hover, focus or tap a shot to read it.
- Lommel SK
- Club Brugge KV
- Filled = goal
- Dot area = xG (the smallest chances drawn at a minimum size)
Recent form
1.20 xG created 1.29 xGA
2.31 xG created 1.00 xGA
- D 1.69 created, 0.83 conceded against KV Mechelen
- W 2.91 created, 1.42 conceded against KAA Gent
- W 3.85 created, 0.86 conceded against KV Kortrijk
- W 2.92 created, 0.72 conceded against Oud-Heverlee Leuven
- W 1.83 created, 0.76 conceded against Cercle Brugge
- L 0.65 created, 1.38 conceded against KAA Gent
xG created xG conceded (xGA) W / D / L: the match result
Pre-match model & market record
9 opportunities flagged3 won6 lost
- Lost
- Won
- Lost
- Lost
- Lost
- Won
- Lost
- Won
- Lost
View pre-match record Hide pre-match record
| Selection | Price | Edge | Result |
|---|---|---|---|
| Lommel SK to win | 8.50 | +83.3% | Lost |
| Club Brugge KV at most 1 goal | 4.00 | +57.9% | Won |
| Club Brugge KV not to score | 13.00 | +55.1% | Lost |
| Draw | 5.25 | +33.7% | Lost |
| Lommel SK 2+ goals | 3.50 | +27.9% | Lost |
| Under 2.5 goals | 3.50 | +24.2% | Won |
| Lommel SK to score | 1.50 | +11.8% | Lost |
| Under 1.5 goals | 8.00 | +5.8% | Won |
| Both teams to score | 1.57 | +5.3% | Lost |
Pre-match model vs market
| Outcome | Model | Market | Difference | Fair odds |
|---|---|---|---|---|
| Lommel SK | 21.6% | 10.8% | +10.7 pp | 4.64 |
| Draw | 25.5% | 17.5% | +7.9 pp | 3.93 |
| Club Brugge KV | 53.0% | 71.6% | −18.7 pp | 1.89 |
Other markets
| Outcome | Model | Market | Difference | Fair odds |
|---|---|---|---|---|
| Lommel SK to score | 74.5% | 62.5% | +12.0 pp | 1.34 |
| Lommel SK not to score | 25.5% | 37.5% | −12.0 pp | 3.93 |
| Club Brugge KV to score | 88.1% | 92.6% | −4.5 pp | 1.14 |
| Club Brugge KV not to score | 11.9% | 7.4% | +4.5 pp | 8.38 |
| Both teams to score | 67.0% | 58.9% | +8.1 pp | 1.49 |
| Both teams not to score | 33.0% | 41.1% | −8.1 pp | 3.03 |
| Lommel SK 2+ goals | 36.5% | 26.9% | +9.7 pp | 2.74 |
| Lommel SK at most 1 goal | 63.5% | 73.1% | −9.7 pp | 1.58 |
| Club Brugge KV 2+ goals | 60.5% | 76.6% | −16.1 pp | 1.65 |
| Club Brugge KV at most 1 goal | 39.5% | 23.4% | +16.1 pp | 2.53 |
| Over 1.5 goals | 86.8% | 88.1% | −1.3 pp | 1.15 |
| Under 1.5 goals | 13.2% | 11.9% | +1.3 pp | 7.56 |
| Over 2.5 goals | 64.5% | 72.9% | −8.4 pp | 1.55 |
| Under 2.5 goals | 35.5% | 27.1% | +8.4 pp | 2.82 |
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)
- Lommel SK sample
- 4 matches
- Club Brugge KV sample
- 20 matches
- Computed
- 6 hours before kick-off
- Prices taken
- 6 hours before kick-off
Warnings
- Lommel SK has only 4 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.