FC Nordsjælland 2:0 AGF: xG & match report · Superliga (Denmark)

Sunday, 13/09/2026 at 18:00

Full time

Match report · Superliga (Denmark)

FC Nordsjælland Home 2.79 xG · 19 shots

AGF Away 1.26 xG · 13 shots

20 The scoreline reflected the chances

FC Nordsjælland were the model's likeliest winner before kick-off at 43%. They won 2–0. The biggest difference was FC Nordsjælland's attack: 2.79 xG against 1.65 projected (+1.14).

Goals

76' Alexander Lind FC Nordsjælland · 0.72 xG chance 1–0
90' Hjalte Boe Rasmussen FC Nordsjælland · 0.62 xG chance 2–0

The model against the result

priced before kick-off

FC Nordsjælland: 43% What happened
Draw: 28%
AGF: 29%

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

Projected vs produced

Expected goals

FC Nordsjælland 1.65 2.79 +1.14

AGF 1.36 1.26 -0.10

FC Nordsjælland produced 1.14 xG more than projected

Projected before kick-off Produced on the night

The shots behind it

FC Nordsjælland AGF

Shots: 19; 13
On target: 3; 2
Inside the box: 14; 8
xG per shot: 0.13; 0.10
Open play xG: 2.36; 1.12
Set-piece xG: 0.03; 0.19
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: 2.42 for FC Nordsjælland and 1.29 for AGF.

Shot map

Both teams shown attacking the same goal for comparison.

All shots

32 shots · 3.70 xG

Hover, focus or tap a shot to read it.

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

Recent form

Last 6 · xG per match

FC Nordsjælland

2.40 xG created 1.25 xGA

W 3.70 created, 0.74 conceded against Randers FC
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

AGF

1.71 xG created 1.54 xGA

D 1.35 created, 3.37 conceded against Lyngby
L 1.92 created, 1.03 conceded against Viborg FF
D 1.88 created, 0.81 conceded against Odense Boldklub
L 1.97 created, 1.10 conceded against Randers FC
L 1.21 created, 1.71 conceded against FC Midtjylland
D 1.92 created, 1.23 conceded against Silkeborg IF

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

Head to head

FC Nordsjælland: 0 won · 2 drawn · 2 lost

Pre-match model & market record

7 opportunities flagged1 won6 lost

Lost
Lost
Lost
Lost
Won
Lost
Lost

View pre-match record

The outcomes the model flagged on FC Nordsjælland against AGF before kick-off, in the order they ranked, with the price, the edge and what became of each.
Selection	Price	Edge	Result
FC Nordsjælland not to score	7.00	+17.5%	Lost
FC Nordsjælland at most 1 goal	2.38	+17.1%	Lost
AGF to win	3.90	+13.6%	Lost
Draw	3.90	+9.8%	Lost
Under 2.5 goals	2.60	+5.0%	Won
AGF 2+ goals	2.50	+0.8%	Lost
AGF to score	1.30	+0.1%	Lost

Pre-match model vs market

Outcome	Model	Market	Difference	Fair odds
FC Nordsjælland	42.7%	52.0%	−9.3 pp	2.34
Draw	28.2%	24.0%	+4.2 pp	3.55
AGF	29.1%	24.0%	+5.1 pp	3.43

Other markets

Outcome	Model	Market	Difference	Fair odds
FC Nordsjælland to score	83.2%	86.4%	−3.2 pp	1.20
FC Nordsjælland not to score	16.8%	13.6%	+3.2 pp	5.96
AGF to score	77.0%	72.3%	+4.7 pp	1.30
AGF not to score	23.0%	27.7%	−4.7 pp	4.35
Both teams to score	65.7%	64.5%	+1.1 pp	1.52
Both teams not to score	34.3%	35.5%	−1.1 pp	2.91
FC Nordsjælland 2+ goals	50.7%	60.8%	−10.1 pp	1.97
FC Nordsjælland at most 1 goal	49.3%	39.2%	+10.1 pp	2.03
AGF 2+ goals	40.3%	37.5%	+2.8 pp	2.48
AGF at most 1 goal	59.7%	62.5%	−2.8 pp	1.68
Over 1.5 goals	84.1%	84.2%	−0.1 pp	1.19
Under 1.5 goals	15.9%	15.8%	+0.1 pp	6.28
Over 2.5 goals	59.6%	63.8%	−4.2 pp	1.68
Under 2.5 goals	40.4%	36.2%	+4.2 pp	2.48

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)
FC Nordsjælland sample: 20 matches
AGF sample: 20 matches
Computed: 8 hours before kick-off
Prices taken: 8 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.