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Bayer Leverkusen vs Borussia Mönchengladbach: statistics and analysis

BUNDESLIGA 2026/27 · PRE-MATCH ANALYSIS

Round 12

· LONDON TIME · BayArena · Referee: not provided

Bayer Leverkusen

Bayer Leverkusen

5 · 7 pts · 4 P · 2 W · 1 D · 1 L · GD 5

VSBorussia Mönchengladbach

Borussia Mönchengladbach

18 · 0 pts · 4 P · 0 W · 0 D · 4 L · GD -10

Statistical engine · radaronze-v1

RadarOnze analysis

Probabilities calculated in advance. The explanatory layer organises existing factors and does not change the model’s numbers.

View in the Betting Centre

Away team to score 1+ goals

61.8%

high
View full analysis
Sample
38 matches/team
Model
radaronze-v1

Model factors

  • League average — goals: 3.37

    Weighted average using only matches played before the fixture.

  • Home/away strength: 2.56 × 0.92

    Separate home and away expectations, shrunk towards the overall average.

  • Opponent strength: 1557 × 1442

    Chronological Elo adjustment with no future matches used.

  • Recency: 120-day half-life

    Exponential weighting with a 0.2 floor; older matches never disappear completely.

  • Historical stability: 64.3

    Index derived from the dispersion of previous outcomes for this market.

  • Sample per team: 38 / 38

    Valid home-team and away-team matches available before kick-off.

  • Historical coverage: 100.0%

    Share of previous matches with complete data for this market.

  • Expected Goals: 2.33 × 1.06

    The xG signal receives 28% of the weight; observed goals receive 72%.

  • Model expected goals: 2.50 × 0.96

    Parameters from the independent Poisson model for the home and away teams.

  • Signal consensus: 98.3

    Agreement between the parametric model and the smoothed empirical frequency.

Understand this analysisStructured analysis

Away team to score 1+ goals has a model probability of 61.8%, high confidence and a sample of 38 matches per team.

League average — goals: 3.37 (Weighted average using only matches played before the fixture.) Home/away strength: 2.56 × 0.92 (Separate home and away expectations, shrunk towards the overall average.) Opponent strength: 1557 × 1442 (Chronological Elo adjustment with no future matches used.)

No current market price is available for this signal.

The explanation organises results that have already been calculated; it does not change probabilities, odds, edge, EV, confidence or value classification.

Double chance 12

82.4%

medium
View full analysis
Sample
38 matches/team
Model
radaronze-v1

Model factors

  • League average — goals: 3.37

    Weighted average using only matches played before the fixture.

  • Home/away strength: 2.56 × 0.92

    Separate home and away expectations, shrunk towards the overall average.

  • Opponent strength: 1557 × 1442

    Chronological Elo adjustment with no future matches used.

  • Recency: 120-day half-life

    Exponential weighting with a 0.2 floor; older matches never disappear completely.

  • Historical stability: 64.3

    Index derived from the dispersion of previous outcomes for this market.

  • Sample per team: 38 / 38

    Valid home-team and away-team matches available before kick-off.

  • Historical coverage: 100.0%

    Share of previous matches with complete data for this market.

  • Expected Goals: 2.33 × 1.06

    The xG signal receives 28% of the weight; observed goals receive 72%.

  • Model expected goals: 2.50 × 0.96

    Parameters from the independent Poisson model for the home and away teams.

  • Score matrix: 0–10 goals per team

    The 1X2 probabilities are normalised to add up to exactly 100%.

  • Signal consensus: 81

    Agreement between the parametric model and the smoothed empirical frequency.

Understand this analysisStructured analysis

Double chance 12 has a model probability of 82.4%, medium confidence and a sample of 38 matches per team.

League average — goals: 3.37 (Weighted average using only matches played before the fixture.) Home/away strength: 2.56 × 0.92 (Separate home and away expectations, shrunk towards the overall average.) Opponent strength: 1557 × 1442 (Chronological Elo adjustment with no future matches used.)

No current market price is available for this signal.

The explanation organises results that have already been calculated; it does not change probabilities, odds, edge, EV, confidence or value classification.

Double chance 1X

86.3%

medium
View full analysis
Sample
38 matches/team
Model
radaronze-v1

Model factors

  • League average — goals: 3.37

    Weighted average using only matches played before the fixture.

  • Home/away strength: 2.56 × 0.92

    Separate home and away expectations, shrunk towards the overall average.

  • Opponent strength: 1557 × 1442

    Chronological Elo adjustment with no future matches used.

  • Recency: 120-day half-life

    Exponential weighting with a 0.2 floor; older matches never disappear completely.

  • Historical stability: 64.3

    Index derived from the dispersion of previous outcomes for this market.

  • Sample per team: 38 / 38

    Valid home-team and away-team matches available before kick-off.

  • Historical coverage: 100.0%

    Share of previous matches with complete data for this market.

  • Expected Goals: 2.33 × 1.06

    The xG signal receives 28% of the weight; observed goals receive 72%.

  • Model expected goals: 2.50 × 0.96

    Parameters from the independent Poisson model for the home and away teams.

  • Score matrix: 0–10 goals per team

    The 1X2 probabilities are normalised to add up to exactly 100%.

  • Signal consensus: 48.5

    Agreement between the parametric model and the smoothed empirical frequency.

Understand this analysisStructured analysis

Double chance 1X has a model probability of 86.3%, medium confidence and a sample of 38 matches per team.

League average — goals: 3.37 (Weighted average using only matches played before the fixture.) Home/away strength: 2.56 × 0.92 (Separate home and away expectations, shrunk towards the overall average.) Opponent strength: 1557 × 1442 (Chronological Elo adjustment with no future matches used.)

No current market price is available for this signal.

The explanation organises results that have already been calculated; it does not change probabilities, odds, edge, EV, confidence or value classification.

Double chance X2

31.3%

medium
View full analysis
Sample
38 matches/team
Model
radaronze-v1

Model factors

  • League average — goals: 3.37

    Weighted average using only matches played before the fixture.

  • Home/away strength: 2.56 × 0.92

    Separate home and away expectations, shrunk towards the overall average.

  • Opponent strength: 1557 × 1442

    Chronological Elo adjustment with no future matches used.

  • Recency: 120-day half-life

    Exponential weighting with a 0.2 floor; older matches never disappear completely.

  • Historical stability: 64.3

    Index derived from the dispersion of previous outcomes for this market.

  • Sample per team: 38 / 38

    Valid home-team and away-team matches available before kick-off.

  • Historical coverage: 100.0%

    Share of previous matches with complete data for this market.

  • Expected Goals: 2.33 × 1.06

    The xG signal receives 28% of the weight; observed goals receive 72%.

  • Model expected goals: 2.50 × 0.96

    Parameters from the independent Poisson model for the home and away teams.

  • Score matrix: 0–10 goals per team

    The 1X2 probabilities are normalised to add up to exactly 100%.

  • Signal consensus: 29.8

    Agreement between the parametric model and the smoothed empirical frequency.

Understand this analysisStructured analysis

Double chance X2 has a model probability of 31.3%, medium confidence and a sample of 38 matches per team.

League average — goals: 3.37 (Weighted average using only matches played before the fixture.) Home/away strength: 2.56 × 0.92 (Separate home and away expectations, shrunk towards the overall average.) Opponent strength: 1557 × 1442 (Chronological Elo adjustment with no future matches used.)

No current market price is available for this signal.

The explanation organises results that have already been calculated; it does not change probabilities, odds, edge, EV, confidence or value classification.

Over 0.5 goals

96.4%

high
View full analysis
Sample
38 matches/team
Model
radaronze-v1

Model factors

  • League average — goals: 3.37

    Weighted average using only matches played before the fixture.

  • Home/away strength: 2.56 × 0.92

    Separate home and away expectations, shrunk towards the overall average.

  • Opponent strength: 1557 × 1442

    Chronological Elo adjustment with no future matches used.

  • Recency: 120-day half-life

    Exponential weighting with a 0.2 floor; older matches never disappear completely.

  • Historical stability: 64.3

    Index derived from the dispersion of previous outcomes for this market.

  • Sample per team: 38 / 38

    Valid home-team and away-team matches available before kick-off.

  • Historical coverage: 100.0%

    Share of previous matches with complete data for this market.

  • Expected Goals: 2.33 × 1.06

    The xG signal receives 28% of the weight; observed goals receive 72%.

  • Model expected goals: 2.50 × 0.96

    Parameters from the independent Poisson model for the home and away teams.

  • Signal consensus: 94

    Agreement between the parametric model and the smoothed empirical frequency.

Understand this analysisStructured analysis

Over 0.5 goals has a model probability of 96.4%, high confidence and a sample of 38 matches per team.

League average — goals: 3.37 (Weighted average using only matches played before the fixture.) Home/away strength: 2.56 × 0.92 (Separate home and away expectations, shrunk towards the overall average.) Opponent strength: 1557 × 1442 (Chronological Elo adjustment with no future matches used.)

No current market price is available for this signal.

The explanation organises results that have already been calculated; it does not change probabilities, odds, edge, EV, confidence or value classification.

Home team to score 2+ goals

68.7%

medium
View full analysis
Sample
38 matches/team
Model
radaronze-v1

Model factors

  • League average — goals: 3.37

    Weighted average using only matches played before the fixture.

  • Home/away strength: 2.56 × 0.92

    Separate home and away expectations, shrunk towards the overall average.

  • Opponent strength: 1557 × 1442

    Chronological Elo adjustment with no future matches used.

  • Recency: 120-day half-life

    Exponential weighting with a 0.2 floor; older matches never disappear completely.

  • Historical stability: 64.3

    Index derived from the dispersion of previous outcomes for this market.

  • Sample per team: 38 / 38

    Valid home-team and away-team matches available before kick-off.

  • Historical coverage: 100.0%

    Share of previous matches with complete data for this market.

  • Expected Goals: 2.33 × 1.06

    The xG signal receives 28% of the weight; observed goals receive 72%.

  • Model expected goals: 2.50 × 0.96

    Parameters from the independent Poisson model for the home and away teams.

  • Signal consensus: 66.7

    Agreement between the parametric model and the smoothed empirical frequency.

Understand this analysisStructured analysis

Home team to score 2+ goals has a model probability of 68.7%, medium confidence and a sample of 38 matches per team.

League average — goals: 3.37 (Weighted average using only matches played before the fixture.) Home/away strength: 2.56 × 0.92 (Separate home and away expectations, shrunk towards the overall average.) Opponent strength: 1557 × 1442 (Chronological Elo adjustment with no future matches used.)

No current market price is available for this signal.

The explanation organises results that have already been calculated; it does not change probabilities, odds, edge, EV, confidence or value classification.

Over 20.5 shots

94.7%

high
View full analysis
Sample
38 matches/team
Model
radaronze-v1

Model factors

  • League average — shots: 27.7

    Weighted average using only matches played before the fixture.

  • Home/away strength: 19.39 × 10.35

    Separate home and away expectations, shrunk towards the overall average.

  • Opponent strength: 1557 × 1442

    Chronological Elo adjustment with no future matches used.

  • Recency: 120-day half-life

    Exponential weighting with a 0.2 floor; older matches never disappear completely.

  • Historical stability: 85.3

    Index derived from the dispersion of previous outcomes for this market.

  • Sample per team: 38 / 38

    Valid home-team and away-team matches available before kick-off.

  • Historical coverage: 100.0%

    Share of previous matches with complete data for this market.

  • Model expected shots: 29.75

    Count model with home/away adjustment, team strength and empirical smoothing.

  • Signal consensus: 81.5

    Agreement between the parametric model and the smoothed empirical frequency.

Understand this analysisStructured analysis

Over 20.5 shots has a model probability of 94.7%, high confidence and a sample of 38 matches per team.

League average — shots: 27.7 (Weighted average using only matches played before the fixture.) Home/away strength: 19.39 × 10.35 (Separate home and away expectations, shrunk towards the overall average.) Opponent strength: 1557 × 1442 (Chronological Elo adjustment with no future matches used.)

No current market price is available for this signal.

The explanation organises results that have already been calculated; it does not change probabilities, odds, edge, EV, confidence or value classification.

Result probabilities — 1X2Complementary statistical view. It does not take part in top signals or tickets.

Away win

13.7%

medium
View full analysis
Sample
38 matches/team
Model
radaronze-v1

Model factors

  • League average — goals: 3.37

    Weighted average using only matches played before the fixture.

  • Home/away strength: 2.56 × 0.92

    Separate home and away expectations, shrunk towards the overall average.

  • Opponent strength: 1557 × 1442

    Chronological Elo adjustment with no future matches used.

  • Recency: 120-day half-life

    Exponential weighting with a 0.2 floor; older matches never disappear completely.

  • Historical stability: 64.3

    Index derived from the dispersion of previous outcomes for this market.

  • Sample per team: 38 / 38

    Valid home-team and away-team matches available before kick-off.

  • Historical coverage: 100.0%

    Share of previous matches with complete data for this market.

  • Expected Goals: 2.33 × 1.06

    The xG signal receives 28% of the weight; observed goals receive 72%.

  • Model expected goals: 2.50 × 0.96

    Parameters from the independent Poisson model for the home and away teams.

  • Score matrix: 0–10 goals per team

    The 1X2 probabilities are normalised to add up to exactly 100%.

  • Signal consensus: 48.5

    Agreement between the parametric model and the smoothed empirical frequency.

Draw

17.6%

medium
View full analysis
Sample
38 matches/team
Model
radaronze-v1

Model factors

  • League average — goals: 3.37

    Weighted average using only matches played before the fixture.

  • Home/away strength: 2.56 × 0.92

    Separate home and away expectations, shrunk towards the overall average.

  • Opponent strength: 1557 × 1442

    Chronological Elo adjustment with no future matches used.

  • Recency: 120-day half-life

    Exponential weighting with a 0.2 floor; older matches never disappear completely.

  • Historical stability: 64.3

    Index derived from the dispersion of previous outcomes for this market.

  • Sample per team: 38 / 38

    Valid home-team and away-team matches available before kick-off.

  • Historical coverage: 100.0%

    Share of previous matches with complete data for this market.

  • Expected Goals: 2.33 × 1.06

    The xG signal receives 28% of the weight; observed goals receive 72%.

  • Model expected goals: 2.50 × 0.96

    Parameters from the independent Poisson model for the home and away teams.

  • Score matrix: 0–10 goals per team

    The 1X2 probabilities are normalised to add up to exactly 100%.

  • Signal consensus: 81

    Agreement between the parametric model and the smoothed empirical frequency.

Home win

68.7%

medium
View full analysis
Sample
38 matches/team
Model
radaronze-v1

Model factors

  • League average — goals: 3.37

    Weighted average using only matches played before the fixture.

  • Home/away strength: 2.56 × 0.92

    Separate home and away expectations, shrunk towards the overall average.

  • Opponent strength: 1557 × 1442

    Chronological Elo adjustment with no future matches used.

  • Recency: 120-day half-life

    Exponential weighting with a 0.2 floor; older matches never disappear completely.

  • Historical stability: 64.3

    Index derived from the dispersion of previous outcomes for this market.

  • Sample per team: 38 / 38

    Valid home-team and away-team matches available before kick-off.

  • Historical coverage: 100.0%

    Share of previous matches with complete data for this market.

  • Expected Goals: 2.33 × 1.06

    The xG signal receives 28% of the weight; observed goals receive 72%.

  • Model expected goals: 2.50 × 0.96

    Parameters from the independent Poisson model for the home and away teams.

  • Score matrix: 0–10 goals per team

    The 1X2 probabilities are normalised to add up to exactly 100%.

  • Signal consensus: 29.8

    Agreement between the parametric model and the smoothed empirical frequency.

18+ · Statistical estimates, not guaranteed outcomes. Bet responsibly.

Data interpretation

RadarOnze analysis

An original, deterministic reading of the real samples shown on this page.

Across 10 recent matches, Bayer Leverkusen recorded 5 wins, 2 draws and 3 defeats and averaged 2.00 goals scored per match. Borussia Mönchengladbach's 10-match sample contains 2 wins, 2 draws and 6 defeats, with 1.30 goals scored per match.

The venue split shows Bayer Leverkusen at home with 11 wins, 4 draws and 4 defeats in 19 matches, averaging 2.32 goals scored and 1.00 goal conceded. Away from home, Borussia Mönchengladbach has 3 wins, 5 draws and 11 defeats in 19 matches, with 0.95 goals scored and 1.95 goals conceded.

Both teams scored in 7 of 10 matches (70%) of Bayer Leverkusen's sample and 4 of 10 matches (40%) of Borussia Mönchengladbach's. Over 2.5 goals occurred in 7 of 10 matches (70%) and 6 of 10 matches (60%), respectively.

Shot volume separates the sides at 20.00 per match for Bayer Leverkusen and 13.70 for Borussia Mönchengladbach. On target, the averages are 6.40 and 4.00, respectively.

Historical frequencies describe the available sample; they are not a promise or certainty about a future result.

Form

Recent form and season

Last 5

Bayer Leverkusen

5 matches
WDWLD
W
2
D
2
L
1
GF
11
GA
6

Last 5

Borussia Mönchengladbach

5 matches
LLLLW
W
1
D
0
L
4
GF
10
GA
16

Last 10

Bayer Leverkusen

10 matches
WDWLDLWWLW
W
5
D
2
L
3
GF
20
GA
13

Last 10

Borussia Mönchengladbach

10 matches
LLLLWLWDDL
W
2
D
2
L
6
GF
13
GA
21

Last 20

Bayer Leverkusen

20 matches
WDWLDLWWLWWDDDWDLWDW
W
9
D
7
L
4
GF
43
GA
27

Last 20

Borussia Mönchengladbach

20 matches
LLLLWLWDDLDDWLWLLDDL
W
4
D
6
L
10
GF
25
GA
40

Season

Bayer Leverkusen

38 matches
WDWLDLWWLWWDDDWDLWDWWLLWWLLWWLWWWWDWDL
W
19
D
9
L
10
GF
78
GA
52

Season

Borussia Mönchengladbach

38 matches
LLLLWLWDDLDDWLWLLDDLDLWLLWDWWWLLDLDLLD
W
9
D
11
L
18
GF
48
GA
69

Goals

Frequencies across the last 10

Average goals scored

Bayer Leverkusen

2.00 · 10 matches

Borussia Mönchengladbach

1.30 · 10 matches

Average goals conceded

Bayer Leverkusen

1.30 · 10 matches

Borussia Mönchengladbach

2.10 · 10 matches

Over 0.5

Bayer Leverkusen

100% · 10 of 10 matches

Borussia Mönchengladbach

90% · 9 of 10 matches

Over 1.5

Bayer Leverkusen

90% · 9 of 10 matches

Borussia Mönchengladbach

70% · 7 of 10 matches

Over 2.5

Bayer Leverkusen

70% · 7 of 10 matches

Borussia Mönchengladbach

60% · 6 of 10 matches

Over 3.5

Bayer Leverkusen

50% · 5 of 10 matches

Borussia Mönchengladbach

50% · 5 of 10 matches

Both teams scored

Bayer Leverkusen

70% · 7 of 10 matches

Borussia Mönchengladbach

40% · 4 of 10 matches

Clean sheet

Bayer Leverkusen

30% · 3 of 10 matches

Borussia Mönchengladbach

30% · 3 of 10 matches

Failed to score

Bayer Leverkusen

0% · 0 of 10 matches

Borussia Mönchengladbach

40% · 4 of 10 matches

Corners

Volume and observed lines

Average for

Bayer Leverkusen

7.90 · 10 matches

Borussia Mönchengladbach

4.10 · 10 matches

Average against

Bayer Leverkusen

3.70 · 10 matches

Borussia Mönchengladbach

5.90 · 10 matches

Total average

Bayer Leverkusen

11.60 · 10 matches

Borussia Mönchengladbach

10.00 · 10 matches

Over 7.5

Bayer Leverkusen

80% · 8 of 10 matches

Borussia Mönchengladbach

70% · 7 of 10 matches

Over 8.5

Bayer Leverkusen

80% · 8 of 10 matches

Borussia Mönchengladbach

60% · 6 of 10 matches

Over 9.5

Bayer Leverkusen

80% · 8 of 10 matches

Borussia Mönchengladbach

60% · 6 of 10 matches

Over 10.5

Bayer Leverkusen

60% · 6 of 10 matches

Borussia Mönchengladbach

50% · 5 of 10 matches

Over 11.5

Bayer Leverkusen

50% · 5 of 10 matches

Borussia Mönchengladbach

40% · 4 of 10 matches

Cards

Averages and frequencies

Team average

Bayer Leverkusen

1.40 · 10 matches

Borussia Mönchengladbach

3.10 · 10 matches

Opponent average

Bayer Leverkusen

2.10 · 10 matches

Borussia Mönchengladbach

2.50 · 10 matches

Total average

Bayer Leverkusen

3.50 · 10 matches

Borussia Mönchengladbach

5.60 · 10 matches

Over 2.5

Bayer Leverkusen

90% · 9 of 10 matches

Borussia Mönchengladbach

90% · 9 of 10 matches

Over 3.5

Bayer Leverkusen

40% · 4 of 10 matches

Borussia Mönchengladbach

90% · 9 of 10 matches

Over 4.5

Bayer Leverkusen

20% · 2 of 10 matches

Borussia Mönchengladbach

50% · 5 of 10 matches

Over 5.5

Bayer Leverkusen

0% · 0 of 10 matches

Borussia Mönchengladbach

30% · 3 of 10 matches

Fouls

Match intensity

Committed average

Bayer Leverkusen

9.10 · 10 matches

Borussia Mönchengladbach

11.60 · 10 matches

Opponent average

Bayer Leverkusen

10.40 · 10 matches

Borussia Mönchengladbach

11.10 · 10 matches

Total average

Bayer Leverkusen

19.50 · 10 matches

Borussia Mönchengladbach

22.70 · 10 matches

Shots

Production and concessions

Average shots

Bayer Leverkusen

20.00 · 10 matches

Borussia Mönchengladbach

13.70 · 10 matches

Average shots on target

Bayer Leverkusen

6.40 · 10 matches

Borussia Mönchengladbach

4.00 · 10 matches

Average shots conceded

Bayer Leverkusen

13.90 · 10 matches

Borussia Mönchengladbach

16.00 · 10 matches

Average shots on target conceded

Bayer Leverkusen

5.00 · 10 matches

Borussia Mönchengladbach

7.40 · 10 matches

Average xG

Bayer Leverkusen

2.37 · 8 matches

Borussia Mönchengladbach

1.36 · 8 matches

Average xG against

Bayer Leverkusen

1.67 · 8 matches

Borussia Mönchengladbach

2.15 · 8 matches

Home vs away

Bayer Leverkusen at home × Borussia Mönchengladbach away

Bayer Leverkusen at home

Bayer Leverkusen

19 matches
WWDWLWDDWWLWLWWWDWL
W
11
D
4
L
4
GF
44
GA
19

Borussia Mönchengladbach away

Borussia Mönchengladbach

19 matches
LLLDLDLLLDDLLWWWLDL
W
3
D
5
L
11
GF
18
GA
37
Average goals scored

Bayer Leverkusen at home

2.32 · 19 matches

Borussia Mönchengladbach away

0.95 · 19 matches

Average goals conceded

Bayer Leverkusen at home

1.00 · 19 matches

Borussia Mönchengladbach away

1.95 · 19 matches

Over 0.5

Bayer Leverkusen at home

100% · 19 of 19 matches

Borussia Mönchengladbach away

89% · 17 of 19 matches

Over 1.5

Bayer Leverkusen at home

95% · 18 of 19 matches

Borussia Mönchengladbach away

74% · 14 of 19 matches

Over 2.5

Bayer Leverkusen at home

53% · 10 of 19 matches

Borussia Mönchengladbach away

58% · 11 of 19 matches

Over 3.5

Bayer Leverkusen at home

37% · 7 of 19 matches

Borussia Mönchengladbach away

37% · 7 of 19 matches

Both teams scored

Bayer Leverkusen at home

58% · 11 of 19 matches

Borussia Mönchengladbach away

42% · 8 of 19 matches

Clean sheet

Bayer Leverkusen at home

42% · 8 of 19 matches

Borussia Mönchengladbach away

26% · 5 of 19 matches

Failed to score

Bayer Leverkusen at home

0% · 0 of 19 matches

Borussia Mönchengladbach away

42% · 8 of 19 matches

Total corner average

Bayer Leverkusen at home

10.37 · 19 matches

Borussia Mönchengladbach away

9.89 · 19 matches

Over 8.5 corners

Bayer Leverkusen at home

68% · 13 of 19 matches

Borussia Mönchengladbach away

58% · 11 of 19 matches

Total card average

Bayer Leverkusen at home

4.74 · 19 matches

Borussia Mönchengladbach away

4.16 · 19 matches

Players and goalkeepers

Pre-match highlights

Bayer Leverkusen

P. Schick

Forward

7.58

4 matches · 261 min

4 goals · 1 assists · 7 of 16 shots on target

Miguel Gutiérrez

Centre-back

7.68

4 matches · 353 min

1 goals · 3 assists · 2 of 4 shots on target

I. Maza

Midfielder

7.37

4 matches · 360 min

1 goals · 1 assists · 2 of 15 shots on target

Christian Kofane

Forward

7.02

4 matches · 134 min

2 goals · 0 assists · 2 of 7 shots on target

F. Medina

Centre-back

7.08

4 matches · 281 min

1 goals · 0 assists · 2 of 2 shots on target

M. Flekken

Goalkeeper

6.61

4 matches · 360 min

9 saves · 3 goals conceded

J. Blaswich

Goalkeeper

0.00

2 matches · 0 min

0 saves · 0 goals conceded

Borussia Mönchengladbach

H. Bolin

Midfielder

7.14

4 matches · 309 min

2 goals · 0 assists · 5 of 7 shots on target

F. Honorat

Midfielder

6.50

4 matches · 238 min

0 goals · 2 assists · 2 of 3 shots on target

L. Ullrich

Midfielder

4.91

4 matches · 235 min

0 goals · 2 assists · 0 of 3 shots on target

S. Machino

Forward

6.70

2 matches · 51 min

1 goals · 0 assists · 1 of 5 shots on target

I. Lidberg

Forward

6.58

4 matches · 152 min

1 goals · 0 assists · 2 of 3 shots on target

M. Nicolas

Goalkeeper

6.83

4 matches · 360 min

22 saves · 7 goals conceded

D. Batz

Goalkeeper

0.00

2 matches · 0 min

0 saves · 0 goals conceded

H2H

Recent meetings

Borussia Mönchengladbach 1 × 1 Bayer Leverkusen1388489
Bayer Leverkusen 1 × 1 Borussia Mönchengladbach1388336
Average goals
2.00 · 2 matches
Both teams scored
100% · 2 of 2 matches
Over 2.5
0% · 0 of 2 matches

H2H corners: 5.50 · 2 matches

Combined view

Data convergences

  • Both scopes show a high frequency of the home team scoring.
  • Recent histories converge towards matches with three or more goals.

Descriptive analysis based exclusively on available frequencies.