RallyIQ

WTA · Left-handed · 96 charted matches · 2010–2025

Petra Kvitova

Archetype: First-strike aggressor · Short-point player

Against an average opponent

Serve points won 62.5% ±2.4 raw 60.7% · tour 56.3% · 6,716 points
Return points won 46.8% ±2.5 raw 42.9% · tour 43.7% · 6,759 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 +0.13 ±0.04 better than 77% of WTA · raw +0.12
Shot selection +0.33 ±0.07 better than 82% of WTA · raw +0.31
Execution −0.96 ±0.32 better than 18% of WTA · raw −1.08
Tactical adaptability +0.02 first serves toward what's working, set to set · 89 matches
Adaptation speed +0.08 same, every two to three service games · per 100 first serves
Points left on the table 3.00 per 100 shots vs best direction · lower than 11% 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 29,347 shots.

Shot expected value

The share of points Petra Kvitova 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 middle

position worth 50% to the average player · 1,764 shots

OptionUsedWin %Tour
FH crosscourt 22% 47.7%±4.0 52.7%
FH down the line 18% 53.9%±4.4 52.2%
FH through the middle 16% 46.1%±4.7 45.8%
BH through the middle 13% 42.7%±5.2 46.2%
BH crosscourt 12% 48.6%±5.4 50.9%
BH down the line 9% 48.1%±6.1 50.0%
FH crosscourt + approach 2% 65.4%±10.3 69.7%
BH slice through the middle 2% 44.6%±11.9 44.8%

Return +1: drive to your middle

position worth 50% to the average player · 1,235 shots

OptionUsedWin %Tour
FH down the line 22% 58.7%±4.7 53.0%
FH crosscourt 20% 52.6%±5.0 52.3%
FH through the middle 16% 42.0%±5.5 46.5%
BH through the middle 13% 44.0%±6.1 46.2%
BH crosscourt 12% 50.1%±6.3 50.8%
BH down the line 9% 49.7%±7.3 50.6%
FH crosscourt + approach 2% 73.6%±10.9 66.8%
FH down the line + approach 2% 70.3%±11.7 69.2%

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

position worth 45% to the average player · 1,214 shots

OptionUsedWin %Tour
BH crosscourt 44% 45.3%±3.5 47.6%
BH through the middle 23% 41.0%±4.7 43.3%
BH down the line 11% 46.4%±6.5 46.8%
BH slice through the middle 7% 34.4%±7.5 34.4%
BH slice crosscourt 5% 43.6%±8.8 40.4%
BH slice down the line 3% 32.0%±10.7 31.7%
BH drop shot crosscourt 2% 46.4%±12.7 47.5%
BH down the line + approach 1% 71.2%±12.1 70.2%

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

position worth 43% to the average player · 1,076 shots

OptionUsedWin %Tour
FH crosscourt 48% 47.8%±3.5 46.7%
FH through the middle 23% 35.8%±4.9 41.3%
FH down the line 21% 47.5%±5.3 44.9%
FH slice through the middle 3% 30.1%±10.1 29.2%
FH slice crosscourt 2% 24.1%±11.3 31.9%
FH drop shot crosscourt 1% 42.9%±14.4 48.6%
FH slice down the line 1% 16.2%±11.1 24.3%

Serve under pressure

Pressure predictability index −1 How much less varied Petra Kvitova's first-serve direction gets on break points. Positive means easier to read. Based on 659 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 42% 42% 72% / 66%
Body 12% 11% 57% / 57%
T 46% 47% 66% / 68%

3,340 normal · 146 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 54% 51% 71% / 66%
Body 8% 9% 54% / 56%
T 37% 40% 73% / 64%

2,689 normal · 513 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
Wide42% 60.5%±2.1 n=1,454 57% ▲
Body12% 55.1%±3.9 n=421 0% ▼
T46% 58.5%±2.0 n=1,611 43% ▼

Consistent with an optimal mix (p = 0.08).
Optimal mix: +0.7 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide54% 63.7%±1.9 n=1,722 69% ▲
Body8% 54.7%±4.7 n=272 0% ▼
T38% 63.3%±2.3 n=1,208 31% ▼

Off equilibrium (p = 0.005): serve wide more. Gap 0.9 points per 100 first serves.
Optimal mix: +0.9 per 100 first serves.

Exploitability 0.81 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: +1.7±2.1 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. (2,553 repeats, 3,943 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 471 42% −1.9±3.6
1stAd courtT 836 36% +0.3±2.7
1stAd courtWide 709 33% −1.5±2.8
1stDeuce courtBody 502 43% ±0.0±3.5
1stDeuce courtT 861 32% +0.3±2.6
1stDeuce courtWide 837 34% +0.1±2.6
2ndAd courtBody 572 55% −0.3±3.3
2ndAd courtT 348 58% +3.0±4.2
2ndAd courtWide 302 49% −4.7±4.5
2ndDeuce courtBody 686 54% −0.1±3.1
2ndDeuce courtT 230 58% +2.0±5.0
2ndDeuce courtWide 374 55% +1.7±4.1

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → BH crosscourt used 2.4% · won 62% · −3.9±6.1 vs own baseline
  2. Wide serve (ad court) → FH down the line used 5.1% · won 61% · −4.4±4.3 vs own baseline
  3. Wide serve (ad court) → FH crosscourt used 3.7% · won 59% · −6.9±5.1 vs own baseline
  4. T serve (deuce court) → BH crosscourt used 2.9% · won 54% · −11.7±5.7 vs own baseline
  5. T serve (deuce court) → FH crosscourt used 4.0% · won 54% · −11.8±5.0 vs own baseline

Return

  1. vs T serve (ad court) → BH through the middle, deep used 3.8% · won 57% · +14.2±5.1 vs own baseline
  2. vs wide serve (ad court) → FH crosscourt, mid used 2.1% · won 61% · +18.0±6.6 vs own baseline
  3. vs wide serve (deuce court) → BH crosscourt, deep used 2.2% · won 60% · +16.6±6.4 vs own baseline
  4. vs wide serve (ad court) → FH crosscourt, deep used 2.1% · won 57% · +13.6±6.6 vs own baseline
  5. vs T serve (deuce court) → FH through the middle, deep used 2.4% · won 54% · +11.0±6.3 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → FH crosscourt used 3.8% · won 53% · +6.7±6.1 vs own baseline
  2. FH crosscourt → FH down the line used 6.3% · won 52% · +4.7±4.9 vs own baseline
  3. FH down the line → FH crosscourt used 1.5% · won 56% · +9.1±8.8 vs own baseline
  4. BH crosscourt → FH down the line used 1.8% · won 54% · +6.8±8.2 vs own baseline
  5. FH crosscourt → FH crosscourt used 7.0% · won 49% · +2.2±4.6 vs own baseline

Discovered sequences

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

  1. Wide serve → BH through the middle return, mid → FH down the line used 0.6% · won 59% · +11.2±8.2 vs own baseline · +7.1 vs tour on the same sequence Disrupted by Elina Svitolina (8/11), Venus Williams (5/6)
  2. Wide serve → FH through the middle return, mid → FH down the line used 0.3% · won 62% · +13.7±10.8 vs own baseline · +18.2 vs tour on the same sequence
  3. FH through the middle return, deep → FH through the middle → FH down the line used 0.2% · won 62% · +13.4±11.1 vs own baseline · +19.7 vs tour on the same sequence
  4. BH crosscourt → FH through the middle → FH down the line used 0.5% · won 58% · +9.3±9.1 vs own baseline · +6.0 vs tour on the same sequence Disrupted by Jessica Pegula (4/7)
  5. Wide serve → BH crosscourt return, mid → FH crosscourt used 0.4% · won 58% · +9.6±9.6 vs own baseline · +7.9 vs tour on the same sequence Disrupted by Varvara Gracheva (5/6)
  6. Wide serve → BH through the middle return, short → FH down the line used 0.2% · won 62% · +13.3±12.1 vs own baseline · +14.7 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

Wide 1st serve · ad court+2.51,722
BH to their forehand · serve +1+2.3568
Wide 2nd serve · ad court+1.6606
T 1st serve · ad court+1.51,208
T 2nd serve · deuce court+1.4589

Most exposed to

BH to their forehand · return +1−2.3323
BH to their forehand · serve +1−2.2487
Wide 2nd serve · ad court−1.4302
T 2nd serve · ad court−1.0348
T 1st serve · deuce court−0.81,518

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +1.30, Angelique Kerber +0.67, Caroline Wozniacki +0.59, Maja Chwalinska +0.40, Tatjana Maria +0.27

Favourable matchups

Sara Errani +0.77, Angelique Kerber +0.65, Elina Avanesyan +0.29, Marie Bouzkova +0.11, Katie Volynets −0.23

Active players who are best at the shot in the top weakness: Victoria Azarenka, Iga Swiatek, Caroline Wozniacki, Leylah Fernandez, Jessica Pegula

Tactical fingerprint

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

Point-ending shots36.8%
Unforced errors / shot15.7%
Deep returns41%
Wide serves · ad54%
T serves · deuce46%
Forehand share58%
BH down the line22%
FH down the line30%
Serve & volley2%
Drop shots / shot1.7%
Wide serves · deuce42%
Points at net8%
T serves · ad38%
1st serve in62%
Backhand slice13%
Through the middle27%
Chipped returns5%
Run-around forehands3%
Avg rally length3.2

Plays most like

  1. Amanda Anisimova 2017–2026 plan v
  2. Talia Gibson 2024–2026 plan v
  3. Barbora Krejcikova 2017–2026 plan v
  4. Elena Rybakina 2019–2026 plan v
  5. Aliaksandra Sasnovich 2015–2025 plan v
  6. Johanna Konta 2013–2020 plan v
  7. Anastasia Pavlyuchenkova 2014–2026 plan v
  8. Madison Keys 2014–2026 plan v

Closest from another era

  1. Lindsay Davenport 1995–2006
  2. Monica Seles 1990–2003
  3. Mary Pierce 1994–2005

Charted matches