xgEdge

Sunday, 06/09/2026 at 20:45

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Match report · Serie A

Juventus 1:1 Milan

Juventus Home 1.59 xG · 14 shots
Milan Away 0.11 xG · 3 shots
11 Juventus had the better chances, but it finished level

Juventus were the model's likeliest winner before kick-off at 54%. It finished 1–1. The biggest difference was Milan's attack: 0.11 xG against 0.85 projected (−0.74).

Goals

  1. 68' Alphadjo Cissè Milan · 0.04 xG chance 0–1
  2. 90' Federico Gatti Juventus · 0.29 xG chance 1–1

The model against the result

priced before kick-off
Juventus
54%
Draw
29% What happened
Milan
17%

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

Projected vs produced

Expected goals
Juventus The model projected 1.57 Produced 1.59 Difference +0.02
Milan The model projected 0.85 Produced 0.11 Difference -0.74

Milan produced 0.74 xG less than projected

Projected before kick-off Produced on the night

The shots behind it

Juventus Milan
Shots
14
3
On target
5
1
Inside the box
6
1
xG per shot
0.12
0.03
Open play xG
1.18
0.10
Set-piece xG
0.49
0.00
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: 1.61 for Juventus and 0.09 for Milan.

Shot map

Both teams shown attacking the same goal for comparison.

Juventus · Manuel Locatelli · 25' · No goal · 5 m · 0.62 xG Juventus · Federico Gatti · 90' · Goal · 6 m · 0.29 xG Juventus · Randal Kolo Muani · 90' · No goal · 6 m · 0.18 xG Juventus · Francisco Conceição · 38' · No goal · 11 m · 0.13 xG Juventus · Nick Woltemade · 85' · No goal · 13 m · 0.09 xG Juventus · Francisco Conceição · 25' · No goal · 8 m · 0.08 xG Juventus · Nicolás González · 12' · No goal · 22 m · 0.06 xG Juventus · Manuel Locatelli · 90' · No goal · 20 m · 0.06 xG Milan · Adrien Rabiot · 13' · No goal · 22 m · 0.05 xG Juventus · Francisco Conceição · 55' · No goal · 23 m · 0.04 xG Milan · Alphadjo Cissè · 68' · Goal · 11 m · 0.04 xG Juventus · Teun Koopmeiners · 84' · No goal · 26 m · 0.04 xG Juventus · Jérémie Boga · 90' · No goal · 22 m · 0.03 xG Juventus · Kerim Alajbegović · 2' · No goal · 24 m · 0.02 xG Juventus · Douglas Luiz · 15' · No goal · 28 m · 0.02 xG Milan · Pervis Estupiñán · 4' · No goal · 20 m · 0.01 xG Juventus · Kerim Alajbegović · 45' · No goal · 23 m · 0.01 xG

All shots

17 shots · 1.77 xG

Hover, focus or tap a shot to read it.

  • Juventus
  • Milan
  • Filled = goal
  • Dot area = xG (the smallest chances drawn at a minimum size)

Recent form

Last 6 · xG per match
Juventus

2.09 xG created 0.53 xGA

  • D 2.60 created, 0.30 conceded against Hellas Verona
  • W 2.29 created, 0.88 conceded against Lecce
  • L 1.98 created, 0.47 conceded against Fiorentina
  • D 1.92 created, 0.85 conceded against Torino
  • W 2.18 created, 0.41 conceded against Frosinone
  • W 1.58 created, 0.25 conceded against Parma
Milan

1.72 xG created 1.53 xGA

  • L 0.24 created, 1.58 conceded against Sassuolo
  • L 2.21 created, 1.38 conceded against Atalanta
  • W 1.75 created, 1.32 conceded against Genoa
  • L 1.74 created, 2.78 conceded against Cagliari
  • W 2.15 created, 1.29 conceded against Torino
  • W 2.21 created, 0.80 conceded against Venezia

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

Head to head

Juventus: 0 won · 2 drawn · 0 lost

Pre-match model & market record

2 opportunities flagged1 won1 lost

  • Lost
  • Won
View pre-match record
The outcomes the model flagged on Juventus against Milan before kick-off, in the order they ranked, with the price, the edge and what became of each.
Selection Price Edge Result
Juventus to win 2.15 +15.4% Lost
Over 1.5 goals 1.36 +0.6% Won

Pre-match model vs market

Outcome Model Market Difference Fair odds
Juventus 53.7% 44.5% +9.1 pp 1.86
Draw 29.2% 29.9% −0.7 pp 3.42
Milan 17.1% 25.5% −8.4 pp 5.84

Other markets

Outcome Model Market Difference Fair odds
Both teams to score 50.7% 50.0% +0.7 pp 1.97
Both teams not to score 49.3% 50.0% −0.7 pp 2.03
Over 1.5 goals 73.7% 70.1% +3.6 pp 1.36
Under 1.5 goals 26.3% 29.9% −3.6 pp 3.81
Over 2.5 goals 44.4% 45.1% −0.8 pp 2.25
Under 2.5 goals 55.6% 54.9% +0.8 pp 1.80

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)
Juventus sample
20 matches
Milan sample
20 matches
Computed
6 hours before kick-off
Prices taken
6 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.