Sunday, 25/10/2026 at 16:30
Full timeFC Sion 1:0 FC Lausanne-Sport
FC Sion were the model's likeliest winner before kick-off at 54%. They won 1–0. The biggest difference was FC Sion's attack: 2.03 xG against 1.64 projected (+0.39). FC Lausanne-Sport produced 1.15 xG against 0.88 projected (+0.27).
Goals
- 33' Théo Berdayes FC Sion · 0.29 xG chance 1–0
The model against the result
- FC Sion
- 54% What happened
- Draw
- 28%
- FC Lausanne-Sport
- 17%
Data coverage Both teams have the full 20-match model window available.
Projected vs produced
FC Sion produced 0.39 xG more than projected
Projected before kick-off Produced on the night
The shots behind it
- Shots
- 16
- 15
- On target
- 2
- 3
- Inside the box
- 11
- 10
- xG per shot
- 0.12
- 0.08
- Open play xG
- 1.84
- 0.92
- Set-piece xG
- 0.16
- 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: 2.03 for FC Sion and 1.15 for FC Lausanne-Sport.
Shot map
Both teams shown attacking the same goal for comparison.
All shots
31 shots · 3.13 xG
Hover or tap a shot, or step through them with the arrows.
- FC Sion
- FC Lausanne-Sport
- Filled = goal
- Dot area = xG (the smallest chances drawn at a minimum size)
Recent form
2.11 xG created 1.56 xGA
- W 1.80 created, 0.94 conceded against Basel
- W 2.78 created, 2.33 conceded against FC Thun
- W 1.26 created, 1.29 conceded against FC St. Gallen 1879
- W 3.48 created, 1.10 conceded against Grasshopper Club Zürich
- D 2.28 created, 2.22 conceded against FC Zürich
- L 1.07 created, 1.46 conceded against Servette FC
0.86 xG created 1.68 xGA
xG created xG conceded (xGA) W / D / L: the match result
Head to head
Pre-match model & market record
8 qualified edges flagged6 won2 lost
- Lost
- Won
- Won
- Won
- Lost
- Won
- Won
- Won
View pre-match record Hide pre-match record
| Selection | Price | Edge | Result |
|---|---|---|---|
| FC Sion not to score | 8.00 | +36.2% | Lost |
| Under 1.5 goals | 5.50 | +33.3% | Won |
| Under 2.5 goals | 2.50 | +32.2% | Won |
| FC Sion at most 1 goal | 2.63 | +30.5% | Won |
| Draw | 4.33 | +23.4% | Lost |
| Both teams not to score | 2.25 | +6.4% | Won |
| FC Lausanne-Sport at most 1 goal | 1.33 | +4.4% | Won |
| FC Lausanne-Sport not to score | 2.63 | +1.1% | Won |
Pre-match model vs market
| Outcome | Model | Market | Difference | Fair odds |
|---|---|---|---|---|
| FC Sion | 54.3% | 62.9% | −8.6 pp | 1.84 |
| Draw | 28.5% | 21.2% | +7.3 pp | 3.51 |
| FC Lausanne-Sport | 17.2% | 16.0% | +1.3 pp | 5.81 |
Other markets
| Outcome | Model | Market | Difference | Fair odds |
|---|---|---|---|---|
| FC Sion to score | 83.0% | 88.1% | −5.1 pp | 1.21 |
| FC Sion not to score | 17.0% | 11.9% | +5.1 pp | 5.87 |
| FC Lausanne-Sport to score | 61.5% | 64.5% | −3.0 pp | 1.63 |
| FC Lausanne-Sport not to score | 38.5% | 35.5% | +3.0 pp | 2.60 |
| Both teams to score | 52.7% | 58.9% | −6.2 pp | 1.90 |
| Both teams not to score | 47.3% | 41.1% | +6.2 pp | 2.12 |
| FC Sion 2+ goals | 50.3% | 64.5% | −14.2 pp | 1.99 |
| FC Sion at most 1 goal | 49.7% | 35.5% | +14.2 pp | 2.01 |
| FC Lausanne-Sport 2+ goals | 21.7% | 29.1% | −7.4 pp | 4.62 |
| FC Lausanne-Sport at most 1 goal | 78.3% | 70.9% | +7.4 pp | 1.28 |
| Over 1.5 goals | 75.8% | 82.8% | −7.0 pp | 1.32 |
| Under 1.5 goals | 24.2% | 17.2% | +7.0 pp | 4.13 |
| Over 2.5 goals | 47.1% | 62.5% | −15.4 pp | 2.12 |
| Under 2.5 goals | 52.9% | 37.5% | +15.4 pp | 1.89 |
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)
- FC Sion sample
- 20 matches
- FC Lausanne-Sport sample
- 20 matches
- Computed
- 59 minutes before kick-off
- Prices taken
- 4 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.