Bayer Leverkusen's defensive numbers are sliding

Defense ▼ Limited evidence Bundesliga Insight date · 2026-10-27 2026-09-05 ~ 2026-10-25

Is the defense really breaking down?

Over the last 3 matches xGA per match moved from 0.67 to 2.19 (+225%); the previous-season baseline is 1.50; 3 of 3 matches moved the same way.

Primary driver

Primary driver Shots faced -0.78 Share 52% Attribution confidence Limited evidence

Over the last 3 matches, expected goals conceded per game moved 0.67 → 2.19. Shots faced per game moved 8.33 → 18.00; at last window's concession rate this changes goal difference by -0.78 per game.

Current season: last 3 vs previous 3; baseline: previous season

Result layer

MetricPrevious RecentChange Change %
Goals conceded per game 0.67 2.33 +1.67 +250.0%
xGA per game 0.67 2.19 +1.52 +225.1%
Goal difference per game 2.0 -0.33 -2.33 -116.7%
Expected points per game 2.48 1.13 -1.35 -54.5%
xG per game 2.61 1.52 -1.09 -41.7%
Goals per game 2.67 2.0 -0.67 -25.0%
Points per game 2.33 2.0 -0.33 -14.3%

Before → after at the result level; all values are per-game averages. Change % = change ÷ |previous|; shown as — when the previous value is 0. Rows are ordered by absolute change %.

Attack: where the change came from

Factor Previous → current Change % Impact on goal difference Share
Finishing
Goals minus expected goals moved +0.06 → +0.48; finishing adds +0.42 goals per game.
0.06 → 0.48
goals above expected per game
+713.6% +0.42 24%
Shot volume
Shots per game moved 23.00 → 12.33; at last window's output per shot this adds -1.21 goals per game.
23.0 → 12.33
shots per game
-46.4% -1.21 69%
Shot quality
Expected goals per shot moved 0.11 → 0.12; at the current shot volume this adds +0.12 goals per game.
0.11 → 0.12
expected goals per shot
+8.7% +0.12 7%

Decomposition uses 3/3 current and 3/3 comparison matches with shot data. Change % = change ÷ |previous|; shown as — when the previous value is 0. Rows are ordered by absolute change %.

Defense: where the change came from

Factor Previous → current Change % Impact on goal difference Share
Goalkeeping & opponent finishing
Expected goals conceded minus goals conceded moved +0.01 → -0.14; goalkeeping and opponent finishing add -0.15 goals of goal difference per game. Split: goalkeeping -0.88, opponent on-target quality +0.73.
0.01 → -0.14
expected goals minus goals conceded per game
-1943.5% -0.15 9%
Shots faced
Shots faced per game moved 8.33 → 18.00; at last window's concession rate this changes goal difference by -0.78 per game.
8.33 → 18.0
shots faced per game
+116.0% -0.78 47%
Shot quality faced
Expected goals per shot faced moved 0.08 → 0.12; at the current volume this changes goal difference by -0.74 per game.
0.08 → 0.12
expected goals per shot faced
+50.5% -0.73 44%

Decomposition uses 3/3 current and 3/3 comparison matches with shot data. All impacts are from the team's goal-difference perspective (positive = better). Change % = change ÷ |previous|; shown as — when the previous value is 0. Rows are ordered by absolute change %.

Context factors

FactorPrevious RecentChange Change %
Opponent strength
Opponents' season goal difference per game (expected goals for minus against); positive means stronger. This is a harder schedule. Coverage 3/3 vs 3/3.
-0.26 0.53 +0.79 +305.8%
Deep completions allowed
Deep completions allowed per game.
3.0 7.0 +4.0 +133.3%
Set-piece threat
Set-piece expected goals per game. It accounts for +51% of the change in attacking expected goals.
0.67 0.11 -0.56 -83.8%
Deep completions
Deep completions per game (attacking progression).
15.67 8.33 -7.33 -46.8%
Open-play threat
Open-play expected goals per game (regular play, fast breaks, individual play).
2.01 1.2 -0.82 -40.6%
Big chances
Big chances created per game.
3.67 3.0 -0.67 -18.2%
Pressing intensity
Lower is more aggressive. This window: more aggressive pressing.
19.67 17.67 -2.0 -10.2%
Possession
Average possession share.
59.33 53.33 -6.0 -10.1%

Context only — not added into the primary-driver calculation, to avoid double counting. Change % = change ÷ |previous|; shown as — when the previous value is 0. Rows are ordered by absolute change %.

Data gaps

  • Current-season sample is only 6 matches; using a 3-match window. Factor shares are unstable at this size.
  • Earlier current-season matches were fewer than five, so the baseline uses last season.
  • Running and sprint data are only available for the Premier League; running did not enter this attribution.
  • The six additive factors explain goal difference within the shot-data sample; points also depend on draw/win margins, game state and match randomness.
  • Injuries, rotation and fixture congestion are not included in the attribution.

The evidence

MetricRecent 3 Previous 3Change
xGA per match 2.19 0.67 +225%

What doesn't move in step

MetricRecent 5 Previous 5Change
xG per match 1.52 2.61 -42%
Non-penalty xG per match 1.52 2.61 -42%
Deep completions per match 8.33 15.67 -47%
Goals per match 2.0 2.67 -25%
Expected points per game 1.13 2.48 -54%
Points per game 2.0 2.33 -14%

Possible explanations

  • Opponents faced over the last 3 matches average 2.07 xG created this season, versus 1.97 in the previous 3.

Limitations

Based on 6 recent matches (6 with expected-goals data).

  • League matches only (415 games analysed); domestic cups and Europe are not included.

Was this useful?

Feedback is linked to this article only. Contact details are not required.