Viborg FF 4:1 FC Nordsjælland: xG & match report · Superliga (Denmark)

Sunday, 20/09/2026 at 18:00

Full time

Match report · Superliga (Denmark)

Viborg FF Home 2.60 xG · 18 shots

FC Nordsjælland Away 1.32 xG · 14 shots

41 The scoreline reflected the chances

FC Nordsjælland were the model's likeliest winner before kick-off at 37%. Viborg FF won 4–1. The biggest difference was Viborg FF's attack: 2.60 xG against 1.50 projected (+1.10).

Goals

16' Mads Søndergaard Viborg FF · 0.05 xG chance 1–0
26' Alexander Lind FC Nordsjælland · 0.29 xG chance 1–1
33' Dorian Hanza Viborg FF · 0.18 xG chance 2–1
41' Charly Nouck Viborg FF · 0.15 xG chance 3–1
81' Adam Kleis-Kristoffersen Viborg FF · 0.38 xG chance 4–1

The model against the result

priced before kick-off

Viborg FF: 35% What happened
Draw: 28%
FC Nordsjælland: 37%

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

Projected vs produced

Expected goals

Viborg FF 1.50 2.60 +1.10

FC Nordsjælland 1.53 1.32 -0.21

Viborg FF produced 1.10 xG more than projected

Projected before kick-off Produced on the night

The shots behind it

Viborg FF FC Nordsjælland

Shots: 18; 14
On target: 6; 2
Inside the box: 17; 10
xG per shot: 0.12; 0.10
Open play xG: 1.36; 1.32
Set-piece xG: 0.71; 0.07
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: 2.06 for Viborg FF and 1.40 for FC Nordsjælland.

Shot map

Both teams shown attacking the same goal for comparison.

All shots

32 shots · 3.46 xG

Hover, focus or tap a shot to read it.

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

Recent form

Last 6 · xG per match

Viborg FF

1.31 xG created 1.03 xGA

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
D 0.71 created, 0.91 conceded against Silkeborg IF

FC Nordsjælland

2.25 xG created 1.34 xGA

W 2.70 created, 0.22 conceded against Silkeborg IF
W 1.97 created, 1.28 conceded against Sønderjyske Fodbold
W 3.32 created, 1.76 conceded against Brøndby IF
L 0.63 created, 1.62 conceded against FC København
D 2.10 created, 1.88 conceded against FC Midtjylland
W 2.79 created, 1.26 conceded against AGF

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

Head to head

Viborg FF: 2 won · 0 drawn · 2 lost

Pre-match model & market record

2 opportunities flagged1 won1 lost

Lost
Won

View pre-match record

The outcomes the model flagged on Viborg FF against FC Nordsjælland before kick-off, in the order they ranked, with the price, the edge and what became of each.
Selection	Price	Edge	Result
Draw	3.80	+7.8%	Lost
Viborg FF to score	1.25	+0.4%	Won

Pre-match model vs market

Outcome	Model	Market	Difference	Fair odds
Viborg FF	35.0%	33.9%	+1.0 pp	2.86
Draw	28.4%	24.6%	+3.8 pp	3.52
FC Nordsjælland	36.7%	41.5%	−4.8 pp	2.73

Other markets

Outcome	Model	Market	Difference	Fair odds
Viborg FF to score	80.3%	75.0%	+5.3 pp	1.25
Viborg FF not to score	19.7%	25.0%	−5.3 pp	5.07
FC Nordsjælland to score	81.1%	79.2%	+1.9 pp	1.23
FC Nordsjælland not to score	18.9%	20.8%	−1.9 pp	5.29
Both teams to score	66.7%	64.5%	+2.1 pp	1.50
Both teams not to score	33.3%	35.5%	−2.1 pp	3.00
Viborg FF 2+ goals	45.5%	44.3%	+1.3 pp	2.20
Viborg FF at most 1 goal	54.5%	55.7%	−1.3 pp	1.84
FC Nordsjælland 2+ goals	46.8%	50.0%	−3.2 pp	2.14
FC Nordsjælland at most 1 goal	53.2%	50.0%	+3.2 pp	1.88
Over 1.5 goals	84.5%	82.8%	+1.7 pp	1.18
Under 1.5 goals	15.5%	17.2%	−1.7 pp	6.45
Over 2.5 goals	60.3%	61.0%	−0.7 pp	1.66
Under 2.5 goals	39.7%	39.0%	+0.7 pp	2.52

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)
Viborg FF sample: 20 matches
FC Nordsjælland sample: 20 matches
Computed: 1 day before kick-off
Prices taken: 1 day 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.