Brøndby IF 3:1 Silkeborg IF: xG & match report · Superliga (Denmark)

Monday, 24/08/2026 at 19:00

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Match report · Superliga (Denmark)

Brøndby IF Home 2.14 xG · 17 shots

Silkeborg IF Away 0.99 xG · 13 shots

31 The scoreline reflected the chances

Brøndby IF were the model's likeliest winner before kick-off at 56%. They won 3–1. The biggest difference was Brøndby IF's attack: 2.14 xG against 1.73 projected (+0.41).

Goals

44' Callum McCowatt Silkeborg IF · 0.03 xG chance 0–1
51' Jordi Vanlerberghe Brøndby IF · 0.13 xG chance 1–1
54' Oskar Fenger Brøndby IF · 0.89 xG chance 2–1
87' Luis Binks Brøndby IF · 0.24 xG chance 3–1

The model against the result

priced before kick-off

Brøndby IF: 56% What happened
Draw: 27%
Silkeborg IF: 16%

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

Projected vs produced

Expected goals

Brøndby IF 1.73 2.14 +0.41

Silkeborg IF 0.89 0.99 +0.10

Brøndby IF produced 0.41 xG more than projected

Projected before kick-off Produced on the night

The shots behind it

Brøndby IF Silkeborg IF

Shots: 17; 13
On target: 5; 4
Inside the box: 11; 8
xG per shot: 0.12; 0.07
Open play xG: 1.47; 0.63
Set-piece xG: 0.64; 0.22
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: 2.15 for Brøndby IF and 0.87 for Silkeborg IF.

Shot map

Both teams shown attacking the same goal for comparison.

All shots

30 shots · 2.96 xG

Hover, focus or tap a shot to read it.

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

Recent form

Last 6 · xG per match

Brøndby IF

1.25 xG created 1.47 xGA

W 2.09 created, 1.95 conceded against FC Midtjylland
D 1.02 created, 1.59 conceded against FC København
D 0.81 created, 1.91 conceded against AGF
W 1.34 created, 1.95 conceded against Viborg FF
W 0.63 created, 0.49 conceded against AC Horsens
W 1.63 created, 0.92 conceded against Sønderjyske Fodbold

Silkeborg IF

1.22 xG created 1.89 xGA

L 1.13 created, 2.90 conceded against FC København
L 1.46 created, 2.78 conceded against FC Fredericia
D 1.09 created, 0.60 conceded against Randers FC
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

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

Head to head

Brøndby IF: 2 won · 0 drawn · 0 lost

Pre-match model & market record

7 opportunities flagged1 won6 lost

Lost
Lost
Lost
Lost
Lost
Lost
Won

View pre-match record

The outcomes the model flagged on Brøndby IF against Silkeborg IF before kick-off, in the order they ranked, with the price, the edge and what became of each.
Selection	Price	Edge	Result
Brøndby IF not to score	9.00	+39.4%	Lost
Draw	4.75	+29.7%	Lost
Brøndby IF at most 1 goal	2.75	+28.5%	Lost
Under 2.5 goals	2.50	+25.6%	Lost
Under 1.5 goals	5.50	+23.3%	Lost
Silkeborg IF to win	6.50	+5.4%	Lost
Silkeborg IF at most 1 goal	1.29	+0.4%	Won

Pre-match model vs market

Outcome	Model	Market	Difference	Fair odds
Brøndby IF	56.5%	65.5%	−9.1 pp	1.77
Draw	27.3%	19.9%	+7.4 pp	3.66
Silkeborg IF	16.2%	14.6%	+1.7 pp	6.17

Other markets

Outcome	Model	Market	Difference	Fair odds
Brøndby IF to score	84.5%	89.4%	−4.9 pp	1.18
Brøndby IF not to score	15.5%	10.6%	+4.9 pp	6.46
Silkeborg IF to score	61.8%	62.5%	−0.7 pp	1.62
Silkeborg IF not to score	38.2%	37.5%	+0.7 pp	2.62
Both teams to score	53.8%	55.7%	−1.9 pp	1.86
Both teams not to score	46.2%	44.3%	+1.9 pp	2.17
Brøndby IF 2+ goals	53.3%	66.3%	−13.0 pp	1.88
Brøndby IF at most 1 goal	46.7%	33.7%	+13.0 pp	2.14
Silkeborg IF 2+ goals	21.9%	26.9%	−5.0 pp	4.56
Silkeborg IF at most 1 goal	78.1%	73.1%	+5.0 pp	1.28
Over 1.5 goals	77.6%	82.8%	−5.2 pp	1.29
Under 1.5 goals	22.4%	17.2%	+5.2 pp	4.46
Over 2.5 goals	49.8%	62.5%	−12.7 pp	2.01
Under 2.5 goals	50.2%	37.5%	+12.7 pp	1.99

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)
Brøndby IF sample: 20 matches
Silkeborg IF sample: 20 matches
Computed: 5 hours before kick-off
Prices taken: 5 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.