Silkeborg IF 1:1 Viborg FF: xG & match report · Superliga (Denmark)

Sunday, 13/09/2026 at 14:00

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Match report · Superliga (Denmark)

Silkeborg IF Home 0.91 xG · 13 shots

Viborg FF Away 0.71 xG · 10 shots

11 The chances were evenly matched

Viborg FF were the model's likeliest winner before kick-off at 47%. It finished 1–1. The biggest difference was Viborg FF's attack: 0.71 xG against 1.58 projected (−0.87).

Goals

11' Lucas Riisgaard Silkeborg IF · 0.12 xG chance 1–0
56' Asker Beck Viborg FF · 0.10 xG chance 1–1

The model against the result

priced before kick-off

Silkeborg IF: 24%
Draw: 29% What happened
Viborg FF: 47%

Data coverage Both teams have the full 20-match model window available.

Projected vs produced

Expected goals

Silkeborg IF 1.11 0.91 -0.20

Viborg FF 1.58 0.71 -0.87

Viborg FF produced 0.87 xG less than projected

Projected before kick-off Produced on the night

The shots behind it

Silkeborg IF Viborg FF

Shots: 13; 10
On target: 5; 4
Inside the box: 9; 5
xG per shot: 0.08; 0.07
Open play xG: 0.63; 0.52
Set-piece xG: 0.47; 0.14
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: 1.09 for Silkeborg IF and 0.66 for Viborg FF.

Shot map

Both teams shown attacking the same goal for comparison.

All shots

23 shots · 1.76 xG

Hover, focus or tap a shot to read it.

Silkeborg IF
Viborg FF
Filled = goal
Dot area = xG (the smallest chances drawn at a minimum size)

Recent form

Last 6 · xG per match

Silkeborg IF

1.17 xG created 1.93 xGA

L 1.52 created, 1.20 conceded against FC København
W 1.92 created, 1.14 conceded against Odense Boldklub
L 0.22 created, 2.70 conceded against FC Nordsjælland
L 0.99 created, 2.14 conceded against Brøndby IF
D 1.11 created, 2.50 conceded against FC Midtjylland
D 1.23 created, 1.92 conceded against AGF

Viborg FF

1.51 xG created 1.10 xGA

L 1.95 created, 1.34 conceded against Brøndby IF
D 1.47 created, 0.62 conceded against Sønderjyske Fodbold
W 1.03 created, 1.92 conceded against AGF
W 1.19 created, 0.34 conceded against FC København
W 1.92 created, 0.83 conceded against AC Horsens
L 1.52 created, 1.55 conceded against Lyngby

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

Head to head

Silkeborg IF: 1 won · 0 drawn · 1 lost

Pre-match model & market record

7 opportunities flagged4 won3 lost

Won
Won
Lost
Won
Lost
Lost
Won

View pre-match record

The outcomes the model flagged on Silkeborg IF against Viborg FF 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	+17.5%	Won
Under 2.5 goals	2.40	+15.9%	Won
Under 1.5 goals	5.50	+15.1%	Lost
Viborg FF at most 1 goal	2.20	+13.8%	Won
Viborg FF not to score	6.00	+9.1%	Lost
Both teams not to score	2.50	+2.4%	Lost
Silkeborg IF at most 1 goal	1.44	+0.1%	Won

Pre-match model vs market

Outcome	Model	Market	Difference	Fair odds
Silkeborg IF	23.9%	24.1%	−0.3 pp	4.19
Draw	29.4%	23.5%	+5.8 pp	3.40
Viborg FF	46.7%	52.3%	−5.6 pp	2.14

Other markets

Outcome	Model	Market	Difference	Fair odds
Silkeborg IF to score	70.1%	70.9%	−0.8 pp	1.43
Silkeborg IF not to score	29.9%	29.1%	+0.8 pp	3.34
Viborg FF to score	81.8%	84.2%	−2.4 pp	1.22
Viborg FF not to score	18.2%	15.8%	+2.4 pp	5.50
Both teams to score	59.0%	62.5%	−3.5 pp	1.69
Both teams not to score	41.0%	37.5%	+3.5 pp	2.44
Silkeborg IF 2+ goals	30.7%	35.5%	−4.8 pp	3.26
Silkeborg IF at most 1 goal	69.3%	64.5%	+4.8 pp	1.44
Viborg FF 2+ goals	48.3%	57.7%	−9.4 pp	2.07
Viborg FF at most 1 goal	51.7%	42.3%	+9.4 pp	1.93
Over 1.5 goals	79.1%	82.8%	−3.7 pp	1.26
Under 1.5 goals	20.9%	17.2%	+3.7 pp	4.78
Over 2.5 goals	51.7%	61.0%	−9.3 pp	1.93
Under 2.5 goals	48.3%	39.0%	+9.3 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

Show

Fit window: the last 20 matches, recency weighted (a match 107 days old counts half)
Silkeborg IF sample: 20 matches
Viborg FF sample: 20 matches
Computed: 4 hours 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.