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VfB Stuttgart vs Bayer Leverkusen: statistics and analysis

BUNDESLIGA 2026/27 · PRE-MATCH ANALYSIS

Round 25

· LONDON TIME · MHPArena · Referee: not provided

VfB Stuttgart

VfB Stuttgart

15 · 3 pts · 4 P · 1 W · 0 D · 3 L · GD -3

VSBayer Leverkusen

Bayer Leverkusen

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

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

82.3%

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

Model factors

  • League average — goals: 3.32

    Weighted average using only matches played before the fixture.

  • Home/away strength: 1.65 × 1.64

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

  • Opponent strength: 1548 × 1557

    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

    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: 1.57 × 1.66

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

  • Model expected goals: 1.63 × 1.64

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

  • Signal consensus: 78.1

    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 82.3%, high confidence and a sample of 38 matches per team.

League average — goals: 3.32 (Weighted average using only matches played before the fixture.) Home/away strength: 1.65 × 1.64 (Separate home and away expectations, shrunk towards the overall average.) Opponent strength: 1548 × 1557 (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

76.3%

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

Model factors

  • League average — goals: 3.32

    Weighted average using only matches played before the fixture.

  • Home/away strength: 1.65 × 1.64

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

  • Opponent strength: 1548 × 1557

    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

    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: 1.57 × 1.66

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

  • Model expected goals: 1.63 × 1.64

    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: 97.5

    Agreement between the parametric model and the smoothed empirical frequency.

Understand this analysisStructured analysis

Double chance 12 has a model probability of 76.3%, medium confidence and a sample of 38 matches per team.

League average — goals: 3.32 (Weighted average using only matches played before the fixture.) Home/away strength: 1.65 × 1.64 (Separate home and away expectations, shrunk towards the overall average.) Opponent strength: 1548 × 1557 (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

61.6%

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

Model factors

  • League average — goals: 3.32

    Weighted average using only matches played before the fixture.

  • Home/away strength: 1.65 × 1.64

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

  • Opponent strength: 1548 × 1557

    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

    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: 1.57 × 1.66

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

  • Model expected goals: 1.63 × 1.64

    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: 64.4

    Agreement between the parametric model and the smoothed empirical frequency.

Understand this analysisStructured analysis

Double chance 1X has a model probability of 61.6%, medium confidence and a sample of 38 matches per team.

League average — goals: 3.32 (Weighted average using only matches played before the fixture.) Home/away strength: 1.65 × 1.64 (Separate home and away expectations, shrunk towards the overall average.) Opponent strength: 1548 × 1557 (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

62.2%

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

Model factors

  • League average — goals: 3.32

    Weighted average using only matches played before the fixture.

  • Home/away strength: 1.65 × 1.64

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

  • Opponent strength: 1548 × 1557

    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

    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: 1.57 × 1.66

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

  • Model expected goals: 1.63 × 1.64

    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: 61.5

    Agreement between the parametric model and the smoothed empirical frequency.

Understand this analysisStructured analysis

Double chance X2 has a model probability of 62.2%, medium confidence and a sample of 38 matches per team.

League average — goals: 3.32 (Weighted average using only matches played before the fixture.) Home/away strength: 1.65 × 1.64 (Separate home and away expectations, shrunk towards the overall average.) Opponent strength: 1548 × 1557 (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

96.5%

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

Model factors

  • League average — goals: 3.32

    Weighted average using only matches played before the fixture.

  • Home/away strength: 1.65 × 1.64

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

  • Opponent strength: 1548 × 1557

    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

    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: 1.57 × 1.66

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

  • Model expected goals: 1.63 × 1.64

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

  • Signal consensus: 96.5

    Agreement between the parametric model and the smoothed empirical frequency.

Understand this analysisStructured analysis

Over 0.5 goals has a model probability of 96.5%, high confidence and a sample of 38 matches per team.

League average — goals: 3.32 (Weighted average using only matches played before the fixture.) Home/away strength: 1.65 × 1.64 (Separate home and away expectations, shrunk towards the overall average.) Opponent strength: 1548 × 1557 (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

49.5%

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

Model factors

  • League average — goals: 3.32

    Weighted average using only matches played before the fixture.

  • Home/away strength: 1.65 × 1.64

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

  • Opponent strength: 1548 × 1557

    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

    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: 1.57 × 1.66

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

  • Model expected goals: 1.63 × 1.64

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

  • Signal consensus: 85.3

    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 49.5%, high confidence and a sample of 38 matches per team.

League average — goals: 3.32 (Weighted average using only matches played before the fixture.) Home/away strength: 1.65 × 1.64 (Separate home and away expectations, shrunk towards the overall average.) Opponent strength: 1548 × 1557 (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

93.4%

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

Model factors

  • League average — shots: 27.29

    Weighted average using only matches played before the fixture.

  • Home/away strength: 14.05 × 14.58

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

  • Opponent strength: 1548 × 1557

    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: 28.63

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

  • Signal consensus: 89.7

    Agreement between the parametric model and the smoothed empirical frequency.

Understand this analysisStructured analysis

Over 20.5 shots has a model probability of 93.4%, high confidence and a sample of 38 matches per team.

League average — shots: 27.29 (Weighted average using only matches played before the fixture.) Home/away strength: 14.05 × 14.58 (Separate home and away expectations, shrunk towards the overall average.) Opponent strength: 1548 × 1557 (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

38.4%

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

Model factors

  • League average — goals: 3.32

    Weighted average using only matches played before the fixture.

  • Home/away strength: 1.65 × 1.64

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

  • Opponent strength: 1548 × 1557

    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

    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: 1.57 × 1.66

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

  • Model expected goals: 1.63 × 1.64

    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: 64.4

    Agreement between the parametric model and the smoothed empirical frequency.

Draw

23.7%

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

Model factors

  • League average — goals: 3.32

    Weighted average using only matches played before the fixture.

  • Home/away strength: 1.65 × 1.64

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

  • Opponent strength: 1548 × 1557

    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

    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: 1.57 × 1.66

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

  • Model expected goals: 1.63 × 1.64

    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: 97.5

    Agreement between the parametric model and the smoothed empirical frequency.

Home win

37.8%

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

Model factors

  • League average — goals: 3.32

    Weighted average using only matches played before the fixture.

  • Home/away strength: 1.65 × 1.64

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

  • Opponent strength: 1548 × 1557

    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

    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: 1.57 × 1.66

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

  • Model expected goals: 1.63 × 1.64

    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: 61.5

    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, VfB Stuttgart recorded 3 wins, 3 draws and 4 defeats and averaged 2.10 goals scored per match. Bayer Leverkusen's 10-match sample contains 5 wins, 2 draws and 3 defeats, with 2.00 goals scored per match.

The venue split shows VfB Stuttgart at home with 13 wins, 3 draws and 3 defeats in 19 matches, averaging 1.79 goals scored and 0.95 goals conceded. Away from home, Bayer Leverkusen has 8 wins, 5 draws and 6 defeats in 19 matches, with 1.79 goals scored and 1.74 goals conceded.

Both teams scored in 8 of 10 matches (80%) of VfB Stuttgart's sample and 7 of 10 matches (70%) of Bayer Leverkusen's. Over 2.5 goals occurred in 8 of 10 matches (80%) and 7 of 10 matches (70%), respectively.

Shot volume separates the sides at 16.20 per match for VfB Stuttgart and 20.00 for Bayer Leverkusen. On target, the averages are 6.50 and 6.40, 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

VfB Stuttgart

5 matches
LLWLD
W
1
D
1
L
3
GF
8
GA
11

Last 5

Bayer Leverkusen

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

Last 10

VfB Stuttgart

10 matches
LLWLDWDDLW
W
3
D
3
L
4
GF
21
GA
20

Last 10

Bayer Leverkusen

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

Last 20

VfB Stuttgart

20 matches
LLWLDWDDLWLWWDWDWLWW
W
9
D
5
L
6
GF
44
GA
32

Last 20

Bayer Leverkusen

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

Season

VfB Stuttgart

38 matches
LLWLDWDDLWLWWDWDWLWWDWWDWLLDWLWWWWWLWL
W
19
D
8
L
11
GF
77
GA
58

Season

Bayer Leverkusen

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

Goals

Frequencies across the last 10

Average goals scored

VfB Stuttgart

2.10 · 10 matches

Bayer Leverkusen

2.00 · 10 matches

Average goals conceded

VfB Stuttgart

2.00 · 10 matches

Bayer Leverkusen

1.30 · 10 matches

Over 0.5

VfB Stuttgart

100% · 10 of 10 matches

Bayer Leverkusen

100% · 10 of 10 matches

Over 1.5

VfB Stuttgart

90% · 9 of 10 matches

Bayer Leverkusen

90% · 9 of 10 matches

Over 2.5

VfB Stuttgart

80% · 8 of 10 matches

Bayer Leverkusen

70% · 7 of 10 matches

Over 3.5

VfB Stuttgart

70% · 7 of 10 matches

Bayer Leverkusen

50% · 5 of 10 matches

Both teams scored

VfB Stuttgart

80% · 8 of 10 matches

Bayer Leverkusen

70% · 7 of 10 matches

Clean sheet

VfB Stuttgart

10% · 1 of 10 matches

Bayer Leverkusen

30% · 3 of 10 matches

Failed to score

VfB Stuttgart

10% · 1 of 10 matches

Bayer Leverkusen

0% · 0 of 10 matches

Corners

Volume and observed lines

Average for

VfB Stuttgart

6.90 · 10 matches

Bayer Leverkusen

7.90 · 10 matches

Average against

VfB Stuttgart

5.50 · 10 matches

Bayer Leverkusen

3.70 · 10 matches

Total average

VfB Stuttgart

12.40 · 10 matches

Bayer Leverkusen

11.60 · 10 matches

Over 7.5

VfB Stuttgart

100% · 10 of 10 matches

Bayer Leverkusen

80% · 8 of 10 matches

Over 8.5

VfB Stuttgart

90% · 9 of 10 matches

Bayer Leverkusen

80% · 8 of 10 matches

Over 9.5

VfB Stuttgart

80% · 8 of 10 matches

Bayer Leverkusen

80% · 8 of 10 matches

Over 10.5

VfB Stuttgart

70% · 7 of 10 matches

Bayer Leverkusen

60% · 6 of 10 matches

Over 11.5

VfB Stuttgart

70% · 7 of 10 matches

Bayer Leverkusen

50% · 5 of 10 matches

Cards

Averages and frequencies

Team average

VfB Stuttgart

1.67 · 9 matches

Bayer Leverkusen

1.40 · 10 matches

Opponent average

VfB Stuttgart

2.00 · 9 matches

Bayer Leverkusen

2.10 · 10 matches

Total average

VfB Stuttgart

3.67 · 9 matches

Bayer Leverkusen

3.50 · 10 matches

Over 2.5

VfB Stuttgart

78% · 7 of 9 matches

Bayer Leverkusen

90% · 9 of 10 matches

Over 3.5

VfB Stuttgart

56% · 5 of 9 matches

Bayer Leverkusen

40% · 4 of 10 matches

Over 4.5

VfB Stuttgart

33% · 3 of 9 matches

Bayer Leverkusen

20% · 2 of 10 matches

Over 5.5

VfB Stuttgart

11% · 1 of 9 matches

Bayer Leverkusen

0% · 0 of 10 matches

Fouls

Match intensity

Committed average

VfB Stuttgart

9.40 · 10 matches

Bayer Leverkusen

9.10 · 10 matches

Opponent average

VfB Stuttgart

11.50 · 10 matches

Bayer Leverkusen

10.40 · 10 matches

Total average

VfB Stuttgart

20.90 · 10 matches

Bayer Leverkusen

19.50 · 10 matches

Shots

Production and concessions

Average shots

VfB Stuttgart

16.20 · 10 matches

Bayer Leverkusen

20.00 · 10 matches

Average shots on target

VfB Stuttgart

6.50 · 10 matches

Bayer Leverkusen

6.40 · 10 matches

Average shots conceded

VfB Stuttgart

16.10 · 10 matches

Bayer Leverkusen

13.90 · 10 matches

Average shots on target conceded

VfB Stuttgart

6.00 · 10 matches

Bayer Leverkusen

5.00 · 10 matches

Average xG

VfB Stuttgart

1.91 · 7 matches

Bayer Leverkusen

2.37 · 8 matches

Average xG against

VfB Stuttgart

2.27 · 7 matches

Bayer Leverkusen

1.67 · 8 matches

Home vs away

VfB Stuttgart at home × Bayer Leverkusen away

VfB Stuttgart at home

VfB Stuttgart

19 matches
LWWDWLWWWWDWDLWWWWW
W
13
D
3
L
3
GF
34
GA
18

Bayer Leverkusen away

Bayer Leverkusen

19 matches
DLLWWDDWLDWLWLWLWWD
W
8
D
5
L
6
GF
34
GA
33
Average goals scored

VfB Stuttgart at home

1.79 · 19 matches

Bayer Leverkusen away

1.79 · 19 matches

Average goals conceded

VfB Stuttgart at home

0.95 · 19 matches

Bayer Leverkusen away

1.74 · 19 matches

Over 0.5

VfB Stuttgart at home

95% · 18 of 19 matches

Bayer Leverkusen away

100% · 19 of 19 matches

Over 1.5

VfB Stuttgart at home

68% · 13 of 19 matches

Bayer Leverkusen away

79% · 15 of 19 matches

Over 2.5

VfB Stuttgart at home

47% · 9 of 19 matches

Bayer Leverkusen away

68% · 13 of 19 matches

Over 3.5

VfB Stuttgart at home

42% · 8 of 19 matches

Bayer Leverkusen away

53% · 10 of 19 matches

Both teams scored

VfB Stuttgart at home

42% · 8 of 19 matches

Bayer Leverkusen away

68% · 13 of 19 matches

Clean sheet

VfB Stuttgart at home

42% · 8 of 19 matches

Bayer Leverkusen away

11% · 2 of 19 matches

Failed to score

VfB Stuttgart at home

21% · 4 of 19 matches

Bayer Leverkusen away

21% · 4 of 19 matches

Total corner average

VfB Stuttgart at home

10.21 · 19 matches

Bayer Leverkusen away

9.63 · 19 matches

Over 8.5 corners

VfB Stuttgart at home

58% · 11 of 19 matches

Bayer Leverkusen away

63% · 12 of 19 matches

Total card average

VfB Stuttgart at home

3.89 · 19 matches

Bayer Leverkusen away

4.79 · 19 matches

Players and goalkeepers

Pre-match highlights

VfB Stuttgart

J. Vagnoman

Midfielder

7.02

4 matches · 351 min

2 goals · 1 assists · 3 of 6 shots on target

M. Mittelstädt

Centre-back

7.75

4 matches · 348 min

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

B. El Khannouss

Midfielder

6.72

4 matches · 203 min

1 goals · 0 assists · 2 of 6 shots on target

Finn Jeltsch

Centre-back

6.59

4 matches · 360 min

0 goals · 1 assists · 1 of 6 shots on target

G. Prömel

Midfielder

6.56

4 matches · 354 min

1 goals · 0 assists · 3 of 8 shots on target

F. Bredlow

Goalkeeper

7.13

4 matches · 360 min

15 saves · 5 goals conceded

M. Funk

Goalkeeper

0.00

3 matches · 0 min

0 saves · 0 goals conceded

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

H2H

Recent meetings

VfB Stuttgart 3 × 1 Bayer Leverkusen1388603
Bayer Leverkusen 1 × 4 VfB Stuttgart1388443
Average goals
4.50 · 2 matches
Both teams scored
100% · 2 of 2 matches
Over 2.5
100% · 2 of 2 matches

H2H corners: 10.50 · 2 matches

Combined view

Data convergences

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

Descriptive analysis based exclusively on available frequencies.