Bayer 04 Leverkusen 1:2 Borussia Dortmund: xG & match report · Bundesliga

Saturday, 29/11/2025 at 18:30

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Match report · Bundesliga

Bayer 04 Leverkusen Home 0.82 xG · 14 shots

Borussia Dortmund Away 0.99 xG · 7 shots

12 The chances were evenly matched

Goals

41' Aarón Anselmino Borussia Dortmund · 0.08 xG chance 0–1
65' Karim Adeyemi Borussia Dortmund · 0.12 xG chance 0–2
83' Christian Kofane Bayer 04 Leverkusen · 0.09 xG chance 1–2

The shots behind it

Bayer 04 Leverkusen Borussia Dortmund

Shots: 14; 7
On target: 4; 4
Inside the box: 9; 6
xG per shot: 0.06; 0.16
Open play xG: 0.54; 0.71
Set-piece xG: 0.30; 0.42
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: 0.82 for Bayer 04 Leverkusen and 1.13 for Borussia Dortmund.

Shot map

Both teams shown attacking the same goal for comparison.

All shots

21 shots · 1.97 xG

Hover, focus or tap a shot to read it.

Bayer 04 Leverkusen
Borussia Dortmund
Filled = goal
Dot area = xG (the smallest chances drawn at a minimum size)

Recent form

Last 6 · xG per match

Bayer 04 Leverkusen

2.12 xG created 1.23 xGA

W 2.87 created, 0.74 conceded against 1. FC Union Berlin
W 3.48 created, 1.66 conceded against 1. FSV Mainz 05
W 1.71 created, 0.72 conceded against SC Freiburg
L 0.23 created, 2.03 conceded against FC Bayern München
W 3.31 created, 0.12 conceded against 1. FC Heidenheim
W 1.10 created, 2.13 conceded against VfL Wolfsburg

Borussia Dortmund

1.45 xG created 1.15 xGA

D 0.89 created, 1.09 conceded against RB Leipzig
L 1.58 created, 2.48 conceded against FC Bayern München
W 1.90 created, 0.39 conceded against 1. FC Köln
W 0.32 created, 0.83 conceded against FC Augsburg
D 1.03 created, 0.57 conceded against Hamburger SV
D 2.99 created, 1.55 conceded against VfB Stuttgart

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

Model details

Show

The model never priced this match before kick-off, so there is no projection to read the result against.

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.