RallyIQ

WTA · Left-handed · 78 charted matches · 2011–2024

Angelique Kerber

Archetype: Ad-court slider · Avoids the wide serve

Against an average opponent

Serve points won 59.1% ±2.4 raw 56.1% · tour 56.3% · 5,639 points
Return points won 45.8% ±2.5 raw 42.6% · tour 43.7% · 5,807 points

Serve and return points won, refitted against every opponent at once so a record built on weak or strong opposition is put on the same scale. Career, all surfaces, with a 90% margin. Raw is the plain share of points won.

Value per 100 shots

Direction choice +0.18 ±0.05 better than 83% of WTA · raw +0.18
Shot selection +0.05 ±0.08 better than 50% of WTA · raw +0.05
Execution +1.65 ±0.29 better than 97% of WTA · raw +1.64
Tactical adaptability −0.07 first serves toward what's working, set to set · 78 matches
Adaptation speed −0.18 same, every two to three service games · per 100 first serves
Points left on the table 2.57 per 100 shots vs best direction · lower than 56% of WTA

Points gained per 100 shots compared with an average tour player in the same position, adjusted for the strength of the opponents faced, with a 90% margin (shots clustered by match). Raw is before the opponent adjustment. Built on 32,100 shots.

Shot expected value

The share of points Angelique Kerber goes on to win after each option in the positions they face most often, shrunk toward tour average when the sample is small. Showing the 8 most-used options; teal marks the best one with at least 30 shots.

Rally, shots 5–8: drive to your backhand side

position worth 45% to the average player · 2,296 shots

OptionUsedWin %Tour
BH crosscourt 45% 48.9%±2.5 47.6%
BH through the middle 24% 40.9%±3.4 43.3%
BH down the line 11% 50.3%±5.0 46.8%
BH slice through the middle 5% 29.6%±6.2 34.4%
BH slice crosscourt 4% 26.3%±7.1 40.4%
BH drop shot down the line 2% 51.1%±9.6 49.1%
BH lob through the middle 2% 33.5%±9.1 27.1%
BH slice down the line 2% 33.3%±9.7 31.7%

Rally, shots 5–8: drive to your forehand side

position worth 43% to the average player · 2,104 shots

OptionUsedWin %Tour
FH crosscourt 54% 48.6%±2.4 46.7%
FH down the line 22% 49.5%±3.8 44.9%
FH through the middle 17% 43.2%±4.3 41.3%
FH slice through the middle 2% 29.0%±9.3 29.2%
FH slice crosscourt 2% 26.0%±9.1 31.9%
FH lob through the middle 1% 25.3%±10.9 29.4%
FH lob crosscourt 1% 34.2%±13.8 29.8%
BH inside-out 1% 49.6%±14.8 46.9%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 1,776 shots

OptionUsedWin %Tour
FH crosscourt 28% 51.0%±3.6 52.7%
FH down the line 18% 60.0%±4.4 52.2%
BH through the middle 15% 47.7%±4.8 46.2%
BH crosscourt 14% 52.3%±5.0 50.9%
FH through the middle 10% 44.5%±5.7 45.8%
BH down the line 9% 52.6%±6.2 50.0%
BH drop shot down the line 2% 45.8%±10.4 47.1%
BH slice down the line 1% 35.5%±13.1 43.9%

Serve +1: mid-depth return to your middle

position worth 51% to the average player · 1,185 shots

OptionUsedWin %Tour
FH down the line 24% 56.9%±4.7 53.3%
FH crosscourt 21% 55.1%±5.0 54.0%
BH crosscourt 18% 54.2%±5.4 52.5%
BH through the middle 16% 41.8%±5.6 46.3%
FH through the middle 10% 49.0%±6.9 45.5%
BH down the line 10% 56.9%±6.9 51.0%
BH drop shot down the line 1% 58.8%±14.3 54.1%

Serve under pressure

Pressure predictability index +2 How much less varied Angelique Kerber's first-serve direction gets on break points. Positive means easier to read. Based on 682 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 35% 51% ▲ 65% / 66%
Body 27% 21% 56% / 57%
T 37% 28% ▼ 59% / 68%

2,750 normal · 178 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 62% 63% 62% / 66%
Body 20% 17% 54% / 56%
T 18% 20% 71% / 64%

2,179 normal · 504 break-point 1st serves

Is the serve mix in equilibrium?

Game theory says a well-mixed server wins equally often with every direction they use. If one direction wins more, it's underused and points are being left behind. This is the minimax test Walker and Wooders ran on Wimbledon finals, applied to every charted first serve. Win rates include faults. "Optimal" allows for returners reading a habit. A direction loses 0.19 points per 100 serves for every 10 points of habitual usage, measured from WTA servers whose mix drifted between matches. Shifts stay within the range servers' habits actually vary, the only range that response was measured over.

Deuce court

1st serveUsagePoints wonOptimal
Wide36% 56.8%±2.5 n=1,058 51% ▲
Body27% 53.7%±2.9 n=793 12% ▼
T37% 55.7%±2.5 n=1,077 37%

Consistent with an optimal mix (p = 0.35).
Optimal mix: +0.5 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide62% 57.6%±2.0 n=1,669 63%
Body19% 51.2%±3.5 n=522 4% ▼
T18% 60.4%±3.5 n=492 33% ▲

Off equilibrium (p = 0.003): serve T more. Gap 3.5 points per 100 first serves.
Optimal mix: +1.1 per 100 first serves.

Exploitability 0.79 points per 100 first serves What the optimal mix would win over the current one, both courts. More exploitable than 100% of WTA servers. Tested on matches they weren't fitted on, WTA mixes picked this way win 0.42 per 100 first serves on average.

Repeating the previous direction to the same court: +2.0±2.2 points per 100 against switching. Negative means returners read repeats. Tour-wide, repeating costs women about 0.4 points per 100 and costs men nothing, so men's returners don't measurably anticipate direction. (2,144 repeats, 3,311 switches.)

Return by serve direction

Return points won against each serve direction, compared with the tour average.

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 415 42% −1.6±3.9
1stAd courtT 803 40% +4.5±2.8
1stAd courtWide 564 33% −1.9±3.2
1stDeuce courtBody 388 41% −2.0±4.0
1stDeuce courtT 693 37% +4.5±2.9
1stDeuce courtWide 824 31% −2.8±2.6
2ndAd courtBody 463 53% −1.6±3.7
2ndAd courtT 337 54% −0.7±4.3
2ndAd courtWide 196 49% −4.4±5.5
2ndDeuce courtBody 545 53% −1.3±3.4
2ndDeuce courtT 148 56% +0.1±6.1
2ndDeuce courtWide 417 54% ±0.0±3.9

Signature patterns

Recurring sequences that win more than Angelique Kerber's own baseline, ranked by edge weighted by how often they're used.

Serve → +1

  1. T serve (deuce court) → FH down the line used 3.2% · won 61% · +2.5±5.7 vs own baseline
  2. Wide serve (ad court) → BH crosscourt used 4.6% · won 58% · −0.4±4.9 vs own baseline
  3. Wide serve (ad court) → FH down the line used 8.5% · won 58% · −0.7±3.6 vs own baseline
  4. Wide serve (deuce court) → FH crosscourt used 2.2% · won 57% · −2.3±6.7 vs own baseline
  5. T serve (deuce court) → BH crosscourt used 2.6% · won 56% · −2.7±6.3 vs own baseline

Return

  1. vs wide serve (deuce court) → BH through the middle, deep used 2.1% · won 54% · +10.6±7.0 vs own baseline
  2. vs T serve (deuce court) → FH through the middle, mid used 3.2% · won 51% · +7.3±5.9 vs own baseline
  3. vs T serve (ad court) → BH through the middle, mid used 5.2% · won 49% · +5.3±4.7 vs own baseline
  4. vs T serve (ad court) → BH down the line, mid used 2.1% · won 51% · +7.3±7.1 vs own baseline
  5. vs T serve (deuce court) → FH through the middle, deep used 2.1% · won 50% · +6.6±7.1 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH down the line used 7.5% · won 56% · +7.5±3.2 vs own baseline
  2. FH through the middle → FH crosscourt used 2.9% · won 55% · +6.8±5.1 vs own baseline
  3. FH down the line → FH down the line used 1.2% · won 58% · +9.3±7.4 vs own baseline
  4. FH down the line → BH down the line used 1.6% · won 56% · +7.9±6.7 vs own baseline
  5. FH crosscourt → BH crosscourt used 5.3% · won 52% · +4.1±3.9 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Angelique Kerber wins the point once the sequence happens, weighted by how often it happens. Think of them as chess openings.

  1. BH crosscourt → FH through the middle → FH crosscourt used 0.8% · won 61% · +12.4±6.6 vs own baseline · +9.0 vs tour on the same sequence Disrupted by Bianca Andreescu (2/8), Madison Keys (4/7)
  2. FH down the line → FH through the middle → FH down the line used 0.4% · won 62% · +13.4±8.1 vs own baseline · +9.8 vs tour on the same sequence Disrupted by Qinwen Zheng (6/8), Ajla Tomljanovic (5/6)
  3. Wide serve → BH through the middle return, mid → BH crosscourt used 0.6% · won 60% · +11.5±7.3 vs own baseline · +7.2 vs tour on the same sequence Disrupted by Elina Svitolina (3/6), Bianca Andreescu (5/10)
  4. BH crosscourt → FH through the middle → FH down the line used 0.6% · won 59% · +10.5±7.2 vs own baseline · +5.9 vs tour on the same sequence Disrupted by Magdalena Frech (3/6), Sara Sorribes Tormo (5/10)
  5. FH crosscourt → BH through the middle → FH down the line used 0.8% · won 58% · +8.9±6.5 vs own baseline · +4.9 vs tour on the same sequence Disrupted by Ajla Tomljanovic (2/6), Jelena Jankovic (3/7)
  6. T serve → BH through the middle return, mid → FH down the line used 0.4% · won 60% · +11.3±8.6 vs own baseline · +9.9 vs tour on the same sequence

Strengths and vulnerabilities

Value per 100 shots compared with the average player hitting (strengths) or facing (vulnerabilities) the same shot. Only shot types seen at least 120 times.

Hurts opponents most with

FH to their backhand · return+4.4755
BH to their forehand · return+4.0884
FH to their backhand · return +1+3.6987
BH to their backhand · return+3.1476
FH to their backhand · rally+3.02,922

Most exposed to

FH volley to their backhand · rally−7.2163
BH to their forehand · return−5.8835
BH slice to their forehand · rally−4.8323
BH to their forehand · serve +1−4.5762
FH to their forehand · serve +1−4.4884

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +4.53, Caroline Wozniacki +4.17, Maja Chwalinska +3.62, Daria Kasatkina +3.57, Alexandra Eala +3.53

Favourable matchups

Sara Errani +4.23, Marie Bouzkova +3.64, Elina Avanesyan +3.62, Beatriz Haddad Maia +3.21, Linda Fruhvirtova +3.20

Active players who are best at the shot in the top weakness: Iga Swiatek, Elina Svitolina, Victoria Azarenka, Bianca Andreescu, Serena Williams

Tactical fingerprint

Each bar shows how far a style trait is from the WTA average, in standard deviations.

Wide serves · ad62%
1st serve in68%
Avg rally length4.7
Forehand share55%
FH down the line31%
Drop shots / shot1.5%
T serves · deuce37%
Serve & volley0%
Backhand slice12%
BH down the line17%
Wide serves · deuce36%
Run-around forehands3%
Chipped returns3%
Points at net4%
Point-ending shots20.1%
Through the middle24%
Unforced errors / shot8.3%
Deep returns26%
T serves · ad18%

Plays most like

  1. Brenda Fruhvirtova 2022–2024 plan v
  2. Anhelina Kalinina 2019–2025 plan v
  3. Magda Linette 2016–2026 plan v
  4. Sara Bejlek 2022–2026 plan v
  5. Anna Lena Friedsam 2014–2023 plan v
  6. Leylah Fernandez 2020–2026 plan v
  7. Flavia Pennetta 2006–2015 plan v
  8. Cristina Bucsa 2016–2026 plan v

Closest from another era

  1. Monica Seles 1990–2003
  2. Arantxa Sanchez Vicario 1988–2001
  3. Martina Hingis 1996–2007

Charted matches