RallyIQ

WTA · Right-handed · 28 charted matches · 2009–2019

Dominika Cibulkova

Archetype: Ad-court T server · Rallies through the middle

Against an average opponent

Serve points won 55.0% ±2.9 raw 52.6% · tour 56.3% · 2,010 points
Return points won 44.0% ±2.9 raw 41.4% · tour 43.7% · 1,911 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 −0.17 ±0.12 better than 22% of WTA · raw −0.17
Shot selection +0.17 ±0.10 better than 62% of WTA · raw +0.17
Execution −0.60 ±0.39 better than 29% of WTA · raw −0.59
Tactical adaptability −0.14 first serves toward what's working, set to set · 27 matches
Adaptation speed −0.10 same, every two to three service games · per 100 first serves
Points left on the table 2.53 per 100 shots vs best direction · lower than 61% 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 9,713 shots.

Shot expected value

The share of points Dominika Cibulkova 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 · 650 shots

OptionUsedWin %Tour
FH crosscourt 30% 55.7%±5.6 52.7%
FH through the middle 22% 48.9%±6.5 45.8%
FH down the line 17% 54.5%±7.2 52.2%
BH through the middle 14% 48.5%±7.7 46.2%
BH crosscourt 11% 53.5%±8.6 50.9%
BH down the line 5% 44.0%±11.5 50.0%

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

position worth 45% to the average player · 563 shots

OptionUsedWin %Tour
BH crosscourt 38% 55.6%±5.4 47.6%
BH through the middle 26% 44.6%±6.4 43.3%
BH down the line 13% 51.4%±8.5 46.8%
BH slice through the middle 8% 33.2%±9.5 34.4%
BH slice crosscourt 4% 42.7%±12.9 40.4%
BH slice down the line 3% 19.3%±10.5 31.7%
FH inside-out 3% 51.3%±13.3 52.5%
FH inside-in 2% 55.2%±14.7 55.6%

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

position worth 43% to the average player · 536 shots

OptionUsedWin %Tour
FH crosscourt 44% 48.0%±5.1 46.7%
FH down the line 28% 47.6%±6.3 44.9%
FH through the middle 26% 42.8%±6.4 41.3%

Serve +1: mid-depth return to your middle

position worth 51% to the average player · 376 shots

OptionUsedWin %Tour
FH crosscourt 24% 50.7%±7.8 54.0%
FH down the line 22% 53.5%±8.0 53.3%
BH through the middle 19% 41.6%±8.5 46.3%
FH through the middle 16% 47.0%±9.1 45.5%
BH crosscourt 13% 54.5%±10.0 52.5%
BH down the line 6% 57.6%±12.5 51.0%

Serve under pressure

Pressure predictability index ±0 How much less varied Dominika Cibulkova's first-serve direction gets on break points. Positive means easier to read. Based on 259 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 29% 24% 62% / 66%
Body 38% 32% 58% / 57%
T 33% 44% ▲ 61% / 68%

971 normal · 62 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 26% 24% 62% / 66%
Body 30% 35% 55% / 56%
T 44% 41% 58% / 64%

773 normal · 197 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
Wide29% 56.0%±4.5 n=298 44% ▲
Body37% 53.6%±4.0 n=387 22% ▼
T34% 53.4%±4.2 n=348 34%

Consistent with an optimal mix (p = 0.71).
Optimal mix: +0.5 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide25% 50.3%±4.9 n=247 41% ▲
Body31% 51.6%±4.5 n=300 16% ▼
T44% 50.8%±3.9 n=423 43%

Consistent with an optimal mix (p = 0.93).
Optimal mix: +0.3 per 100 first serves.

Exploitability 0.38 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: +0.2±3.2 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. (671 repeats, 1,276 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 106 42% −1.9±7.0
1stAd courtT 226 30% −5.2±4.7
1stAd courtWide 204 30% −4.4±4.9
1stDeuce courtBody 134 40% −2.5±6.3
1stDeuce courtT 236 31% −1.1±4.7
1stDeuce courtWide 266 33% −0.8±4.5
2ndAd courtBody 170 56% +0.7±5.8
2ndAd courtT 96 54% −1.5±7.3
2ndAd courtWide 118 53% −0.8±6.8
2ndDeuce courtBody 152 57% +2.3±6.0
2ndDeuce courtT 100 57% +0.8±7.1
2ndDeuce courtWide 94 57% +2.8±7.3

Signature patterns

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

Serve → +1

  1. Wide serve (deuce court) → FH through the middle used 2.1% · won 57% · +0.2±9.9 vs own baseline
  2. T serve (ad court) → BH crosscourt used 2.2% · won 56% · −0.7±9.9 vs own baseline
  3. Body serve (ad court) → BH crosscourt used 3.6% · won 56% · −0.6±8.4 vs own baseline
  4. Body serve (deuce court) → FH crosscourt used 3.1% · won 55% · −1.1±8.9 vs own baseline
  5. Body serve (deuce court) → BH crosscourt used 2.2% · won 55% · −1.5±9.8 vs own baseline

Return

  1. vs wide serve (deuce court) → FH crosscourt, mid used 3.0% · won 63% · +19.5±9.7 vs own baseline
  2. vs wide serve (deuce court) → FH crosscourt, deep used 3.0% · won 52% · +9.1±10.0 vs own baseline
  3. vs T serve (deuce court) → BH through the middle, mid used 4.0% · won 51% · +7.5±9.2 vs own baseline
  4. vs wide serve (ad court) → BH crosscourt, mid used 3.3% · won 51% · +7.5±9.7 vs own baseline
  5. vs body serve (ad court) → BH through the middle, mid used 2.3% · won 52% · +8.5±10.8 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH down the line used 8.0% · won 56% · +5.5±6.2 vs own baseline
  2. BH crosscourt → FH down the line used 2.3% · won 58% · +7.6±9.7 vs own baseline
  3. FH down the line → BH crosscourt used 3.3% · won 57% · +6.0±8.8 vs own baseline
  4. BH down the line → FH down the line used 2.3% · won 56% · +5.5±9.9 vs own baseline
  5. FH down the line → FH down the line used 2.1% · won 56% · +5.0±10.1 vs own baseline

Discovered sequences

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

  1. FH crosscourt → FH through the middle → FH down the line used 0.8% · won 59% · +9.7±10.0 vs own baseline · +11.4 vs tour on the same sequence Disrupted by Sloane Stephens (4/6)
  2. Body serve → FH through the middle return, mid → FH crosscourt used 0.5% · won 60% · +11.0±11.7 vs own baseline · +21.0 vs tour on the same sequence
  3. FH crosscourt → FH down the line → BH crosscourt used 0.7% · won 57% · +7.9±10.5 vs own baseline · +13.1 vs tour on the same sequence Disrupted by Dinara Safina (3/7), Tsvetana Pironkova (6/8)
  4. FH crosscourt → FH through the middle → FH crosscourt used 0.8% · won 57% · +7.7±10.3 vs own baseline · +6.9 vs tour on the same sequence Disrupted by Tsvetana Pironkova (4/6)
  5. FH through the middle → FH down the line → BH crosscourt used 0.5% · won 59% · +9.7±11.7 vs own baseline · +23.9 vs tour on the same sequence
  6. BH through the middle → BH through the middle → FH crosscourt used 0.7% · won 56% · +6.5±10.7 vs own baseline · +11.7 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

FH to their backhand · return +1+4.1137
BH to their backhand · serve +1+2.0240
FH to their forehand · rally+1.1708
FH to the middle · serve +1+0.8224
BH to the middle · return +1+0.8134

Most exposed to

BH to their forehand · return−5.0138
FH to their backhand · return−4.2155
BH to their backhand · return−2.9306
Wide 1st serve · deuce court−2.6396
T 1st serve · ad court−2.3388

Active players who are best at the shot in the top weakness: Alexandra Eala, Magdalena Frech, Belinda Bencic, Angelique Kerber, Clara Tauson

Tactical fingerprint

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

Forehand share57%
T serves · ad44%
Deep returns36%
Through the middle31%
1st serve in63%
Run-around forehands9%
FH down the line30%
Drop shots / shot1.7%
Point-ending shots23.5%
Unforced errors / shot10.3%
Serve & volley0%
Backhand slice13%
Chipped returns8%
Avg rally length3.9
T serves · deuce34%
BH down the line17%
Points at net4%
Wide serves · deuce29%
Wide serves · ad25%

Plays most like

  1. Alexandra Eala 2021–2026 plan v
  2. Jessica Pegula 2015–2026 plan v
  3. Jaqueline Cristian 2021–2026 plan v
  4. Jasmine Paolini 2016–2026 plan v
  5. Robin Montgomery 2022–2026 plan v
  6. Nao Hibino 2016–2025 plan v
  7. Ashlyn Krueger 2023–2026 plan v
  8. R – plan v

Closest from another era

  1. Monica Seles 1990–2003
  2. Jennifer Capriati 1990–2002
  3. Arantxa Sanchez Vicario 1988–2001

Charted matches