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Sunday, 20/09/2026 at 14:00

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Match report · Swiss Super League

FC Vaduz 1:2 FC Thun

FC Vaduz Home 2.77 xG · 17 shots
FC Thun Away 1.70 xG · 15 shots
12 The result went against the chances

FC Vaduz were the model's likeliest winner before kick-off at 39%. FC Thun won 2–1. The biggest difference was FC Vaduz's attack: 2.77 xG against 1.79 projected (+0.98).

Goals

  1. 33' Furkan Dursun FC Thun · 0.08 xG chance 0–1
  2. 49' Nils Reichmuth FC Thun · 0.24 xG chance 0–2
  3. 73' Marcel Monsberger FC Vaduz · 0.58 xG chance 1–2

The model against the result

priced before kick-off
FC Vaduz
39%
Draw
26%
FC Thun
34% What happened

Data coverage One of these teams has only 8 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

Expected goals
FC Vaduz The model projected 1.79 Produced 2.77 Difference +0.98
FC Thun The model projected 1.67 Produced 1.70 Difference +0.03

FC Vaduz produced 0.98 xG more than projected

Projected before kick-off Produced on the night

The shots behind it

FC Vaduz FC Thun
Shots
17
15
On target
3
5
Inside the box
14
10
xG per shot
0.16
0.13
Open play xG
2.00
1.70
Set-piece xG
0.66
0.20
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: 2.64 for FC Vaduz and 1.87 for FC Thun.

Shot map

Both teams shown attacking the same goal for comparison.

FC Vaduz · Marcel Monsberger · 73' · Goal · 5 m · 0.58 xG FC Thun · Noah Christoffersson · 71' · No goal · 5 m · 0.55 xG FC Vaduz · Niklas Lang · 54' · No goal · 5 m · 0.44 xG FC Vaduz · Niklas Lang · 28' · No goal · 4 m · 0.30 xG FC Thun · Nils Reichmuth · 49' · Goal · 14 m · 0.24 xG FC Vaduz · Niklas Lang · 28' · No goal · 3 m · 0.22 xG FC Vaduz · Miloš Cocić · 90' · No goal · 12 m · 0.21 xG FC Thun · Nils Reichmuth · 71' · No goal · 4 m · 0.20 xG FC Thun · Fabio Saiz · 17' · No goal · 10 m · 0.19 xG FC Vaduz · Marcel Monsberger · 84' · No goal · 7 m · 0.16 xG FC Vaduz · Julian Stark · 28' · No goal · 12 m · 0.15 xG FC Vaduz · Lutfi Dalipi · 23' · No goal · 8 m · 0.12 xG FC Vaduz · Marcel Monsberger · 28' · No goal · 7 m · 0.12 xG FC Thun · Fabio Fehr · 90' · No goal · 14 m · 0.12 xG FC Thun · Nils Reichmuth · 45' · No goal · 12 m · 0.11 xG FC Thun · Nils Reichmuth · 55' · No goal · 17 m · 0.10 xG FC Vaduz · Julian Stark · 28' · No goal · 9 m · 0.09 xG FC Vaduz · Denis Simani · 9' · No goal · 6 m · 0.08 xG FC Thun · Furkan Dursun · 33' · Goal · 8 m · 0.08 xG FC Thun · Nico Maier · 78' · No goal · 19 m · 0.08 xG FC Thun · Nils Reichmuth · 59' · No goal · 15 m · 0.07 xG FC Vaduz · Luca Mack · 25' · No goal · 17 m · 0.06 xG FC Vaduz · Marcel Monsberger · 45' · No goal · 8 m · 0.05 xG FC Thun · Nils Reichmuth · 62' · No goal · 15 m · 0.05 xG FC Thun · Nils Reichmuth · 44' · No goal · 18 m · 0.04 xG FC Vaduz · Marcel Monsberger · 63' · No goal · 6 m · 0.04 xG FC Thun · Nico Maier · 86' · No goal · 19 m · 0.04 xG FC Thun · Nils Reichmuth · 18' · No goal · 29 m · 0.02 xG FC Vaduz · Lutfi Dalipi · 27' · No goal · 24 m · 0.02 xG FC Vaduz · Juan Cabrera · 37' · No goal · 26 m · 0.01 xG FC Vaduz · Nicolas Hasler · 54' · No goal · 22 m · 0.01 xG FC Thun · Fabio Saiz · 90' · No goal · 29 m · 0.01 xG

All shots

32 shots · 4.56 xG

Hover, focus or tap a shot to read it.

  • FC Vaduz
  • FC Thun
  • Filled = goal
  • Dot area = xG (the smallest chances drawn at a minimum size)

Recent form

Last 6 · xG per match
FC Vaduz

1.58 xG created 2.02 xGA

  • L 1.75 created, 2.81 conceded against FC Sion
  • L 1.64 created, 2.19 conceded against Young Boys
  • W 2.31 created, 2.99 conceded against Grasshopper Club Zürich
  • L 1.10 created, 2.42 conceded against FC Luzern
  • W 1.65 created, 0.50 conceded against FC Lausanne-Sport
  • L 1.03 created, 1.18 conceded against FC Zürich
FC Thun

1.59 xG created 1.90 xGA

  • L 0.64 created, 1.09 conceded against Basel
  • W 1.26 created, 2.88 conceded against FC St. Gallen 1879
  • D 1.58 created, 0.86 conceded against FC Lausanne-Sport
  • L 2.33 created, 2.78 conceded against FC Sion
  • L 1.67 created, 2.26 conceded against Grasshopper Club Zürich
  • L 2.05 created, 1.52 conceded against Servette FC

xG created xG conceded (xGA) W / D / L: the match result

Pre-match model & market record

2 opportunities flagged0 won2 lost

  • Lost
  • Lost
View pre-match record
The outcomes the model flagged on FC Vaduz against FC Thun before kick-off, in the order they ranked, with the price, the edge and what became of each.
Selection Price Edge Result
Draw 4.00 +4.3% Lost
Under 2.5 goals 3.30 +0.9% Lost

Pre-match model vs market

Outcome Model Market Difference Fair odds
FC Vaduz 39.4% 39.9% −0.4 pp 2.54
Draw 26.1% 23.4% +2.7 pp 3.83
FC Thun 34.5% 36.7% −2.2 pp 2.90

Other markets

Outcome Model Market Difference Fair odds
FC Vaduz to score 85.6% 82.8% +2.8 pp 1.17
FC Vaduz not to score 14.4% 17.2% −2.8 pp 6.92
FC Thun to score 83.7% 82.8% +0.9 pp 1.19
FC Thun not to score 16.3% 17.2% −0.9 pp 6.15
Both teams to score 72.9% 68.7% +4.2 pp 1.37
Both teams not to score 27.1% 31.3% −4.2 pp 3.69
FC Vaduz 2+ goals 55.2% 53.7% +1.6 pp 1.81
FC Vaduz at most 1 goal 44.8% 46.3% −1.6 pp 2.23
FC Thun 2+ goals 51.6% 53.7% −2.1 pp 1.94
FC Thun at most 1 goal 48.4% 46.3% +2.1 pp 2.07
Over 1.5 goals 89.3% 87.7% +1.7 pp 1.12
Under 1.5 goals 10.7% 12.3% −1.7 pp 9.38
Over 2.5 goals 69.4% 72.0% −2.5 pp 1.44
Under 2.5 goals 30.6% 28.0% +2.5 pp 3.27

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 warning
Show
Fit window
the last 20 matches, recency weighted (a match 107 days old counts half)
FC Vaduz sample
8 matches
FC Thun sample
20 matches
Computed
1 day before kick-off
Prices taken
1 day before kick-off

Warnings

  • FC Vaduz has only 8 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.