RallyIQ

WTA · Right-handed · 33 charted matches · 2017–2026

Barbora Krejcikova

Archetype: First-strike aggressor · Short-point player

Against an average opponent

Serve points won 61.9% ±2.6 raw 60.5% · tour 56.3% · 2,448 points
Return points won 44.5% ±2.7 raw 40.4% · tour 43.7% · 2,495 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 +0.19 ±0.09 better than 84% of WTA · raw +0.18
Shot selection −0.47 ±0.17 better than 11% of WTA · raw −0.49
Execution −0.35 ±0.52 better than 40% of WTA · raw −0.48
Tactical adaptability +0.07 first serves toward what's working, set to set · 31 matches
Adaptation speed +0.19 same, every two to three service games · per 100 first serves
Points left on the table 2.49 per 100 shots vs best direction · lower than 66% 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 11,180 shots.

Shot expected value

The share of points Barbora Krejcikova 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 · 553 shots

OptionUsedWin %Tour
FH crosscourt 33% 58.0%±5.7 52.7%
FH through the middle 16% 47.8%±7.9 45.8%
BH through the middle 15% 49.7%±8.2 46.2%
FH down the line 14% 55.7%±8.3 52.2%
BH crosscourt 12% 51.3%±8.8 50.9%
BH down the line 5% 46.9%±11.7 50.0%
BH slice through the middle 2% 53.2%±15.0 44.8%

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

position worth 45% to the average player · 539 shots

OptionUsedWin %Tour
BH crosscourt 42% 42.9%±5.2 47.6%
BH through the middle 23% 46.6%±6.9 43.3%
BH slice crosscourt 11% 47.0%±9.1 40.4%
BH slice through the middle 11% 38.3%±9.1 34.4%
BH down the line 9% 51.2%±9.8 46.8%
BH slice down the line 3% 33.4%±13.3 31.7%

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

position worth 43% to the average player · 477 shots

OptionUsedWin %Tour
FH crosscourt 42% 43.1%±5.5 46.7%
FH through the middle 20% 31.0%±7.0 41.3%
FH down the line 18% 45.8%±7.9 44.9%
FH slice through the middle 11% 35.4%±9.2 29.2%
FH slice crosscourt 5% 39.5%±12.1 31.9%
FH slice down the line 3% 25.3%±12.1 24.3%

Return +1: drive to your middle

position worth 50% to the average player · 432 shots

OptionUsedWin %Tour
FH crosscourt 25% 50.0%±7.3 52.3%
FH through the middle 15% 46.2%±9.0 46.5%
FH down the line 14% 55.7%±9.1 53.0%
BH through the middle 14% 38.3%±9.0 46.2%
BH crosscourt 12% 62.2%±9.5 50.8%
BH down the line 7% 39.5%±11.3 50.6%
BH slice through the middle 4% 44.9%±13.6 45.9%
FH slice through the middle 4% 28.7%±12.4 41.7%

Serve under pressure

Pressure predictability index +9 How much less varied Barbora Krejcikova's first-serve direction gets on break points. Positive means easier to read. Based on 250 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 41% 48% 70% / 66%
Body 13% 3% ▼ 64% / 57%
T 47% 48% 75% / 68%

1,209 normal · 60 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 51% 52% 67% / 66%
Body 11% 7% 57% / 56%
T 38% 41% 67% / 64%

984 normal · 190 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
Wide41% 62.9%±3.4 n=523 38% ▼
Body12% 62.4%±5.9 n=154 0% ▼
T47% 64.7%±3.2 n=592 62% ▲

Consistent with an optimal mix (p = 0.73).
Optimal mix: +0.6 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide51% 57.9%±3.2 n=600 58% ▲
Body10% 53.4%±6.7 n=120 0% ▼
T39% 57.6%±3.7 n=454 42% ▲

Consistent with an optimal mix (p = 0.49).
Optimal mix: +0.3 per 100 first serves.

Exploitability 0.48 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: −0.4±3.3 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. (1,040 repeats, 1,337 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 146 44% ±0.0±6.2
1stAd courtT 307 38% +2.1±4.3
1stAd courtWide 269 30% −4.2±4.4
1stDeuce courtBody 172 42% −0.6±5.7
1stDeuce courtT 316 33% +0.4±4.1
1stDeuce courtWide 338 29% −5.2±3.9
2ndAd courtBody 209 53% −2.1±5.3
2ndAd courtT 79 46% −8.7±7.9
2ndAd courtWide 188 50% −3.5±5.6
2ndDeuce courtBody 217 55% +0.3±5.2
2ndDeuce courtT 146 49% −7.3±6.2
2ndDeuce courtWide 108 50% −3.7±7.0

Signature patterns

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

Serve → +1

  1. Wide serve (deuce court) → FH down the line used 3.5% · won 70% · +4.3±7.4 vs own baseline
  2. Wide serve (deuce court) → FH crosscourt used 2.4% · won 65% · −0.3±8.8 vs own baseline
  3. Wide serve (ad court) → FH crosscourt used 3.0% · won 63% · −2.3±8.2 vs own baseline
  4. Body serve (deuce court) → FH crosscourt used 3.0% · won 63% · −3.0±8.2 vs own baseline
  5. T serve (deuce court) → FH crosscourt used 4.2% · won 63% · −3.0±7.3 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, mid used 3.6% · won 56% · +14.8±8.3 vs own baseline
  2. vs body serve (ad court) → BH through the middle, deep used 2.7% · won 52% · +10.8±9.3 vs own baseline
  3. vs body serve (deuce court) → BH through the middle, deep used 2.4% · won 51% · +10.2±9.6 vs own baseline
  4. vs T serve (deuce court) → BH through the middle, mid used 5.1% · won 48% · +7.0±7.3 vs own baseline
  5. vs T serve (deuce court) → BH through the middle, deep used 3.5% · won 49% · +8.4±8.5 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH down the line used 6.3% · won 54% · +4.9±7.6 vs own baseline
  2. BH crosscourt → FH crosscourt used 5.1% · won 54% · +5.0±8.2 vs own baseline
  3. BH through the middle → FH crosscourt used 5.3% · won 54% · +4.9±8.2 vs own baseline
  4. FH crosscourt → BH through the middle used 2.2% · won 56% · +7.5±10.7 vs own baseline
  5. FH through the middle → FH crosscourt used 2.6% · won 55% · +6.2±10.3 vs own baseline

Discovered sequences

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

  1. BH crosscourt → BH through the middle → FH crosscourt used 1.2% · won 56% · +8.0±9.1 vs own baseline · +6.1 vs tour on the same sequence Disrupted by Dayana Yastremska (3/6), Anett Kontaveit (3/6)
  2. FH crosscourt → FH through the middle → FH down the line used 0.6% · won 59% · +10.3±11.1 vs own baseline · +14.2 vs tour on the same sequence Disrupted by Jessica Pegula (4/6)
  3. FH down the line → BH through the middle → FH crosscourt used 0.5% · won 59% · +11.0±11.5 vs own baseline · +13.8 vs tour on the same sequence
  4. T serve → BH through the middle return, mid → FH crosscourt used 0.6% · won 56% · +7.3±11.1 vs own baseline · +8.7 vs tour on the same sequence
  5. Wide serve → FH through the middle return, mid → FH down the line used 0.4% · won 57% · +8.6±12.3 vs own baseline · +13.3 vs tour on the same sequence
  6. Wide serve → BH through the middle return, mid → FH crosscourt used 0.5% · won 56% · +7.1±11.9 vs own baseline · +6.0 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 forehand · serve +1+3.5374
FH slice to the middle · return+3.0203
T 1st serve · deuce court+1.5592
T 1st serve · ad court+1.4454
Wide 1st serve · deuce court+1.3523

Most exposed to

T 2nd serve · deuce court−2.4146
FH to their forehand · return−1.5140
T 1st serve · deuce court−0.8541
Body 2nd serve · ad court−0.7209
BH to their forehand · return−0.6217

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +1.44, Caroline Wozniacki +1.09, Tatjana Maria +0.75, Daria Kasatkina +0.59, Angelique Kerber +0.53

Favourable matchups

Sara Errani +1.31, Marie Bouzkova +0.88, Angelique Kerber +0.85, Elina Avanesyan +0.81, Katie Volynets +0.52

Active players who are best at the shot in the top weakness: Madison Keys, Ons Jabeur, Iva Jovic, Caroline Wozniacki, Caroline Garcia

Tactical fingerprint

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

Unforced errors / shot13.8%
T serves · deuce47%
Point-ending shots30.7%
Wide serves · ad51%
Deep returns38%
Chipped returns19%
Backhand slice24%
Forehand share54%
T serves · ad39%
1st serve in63%
Wide serves · deuce41%
Serve & volley1%
Through the middle29%
Drop shots / shot1.3%
Points at net6%
Run-around forehands5%
BH down the line18%
FH down the line26%
Avg rally length3.5

Plays most like

  1. Johanna Konta 2013–2020 plan v
  2. Anett Kontaveit 2015–2023 plan v
  3. Elena Rybakina 2019–2026 plan v
  4. Petra Kvitova 2010–2025 plan v
  5. Olivia Gadecki 2023–2026 plan v
  6. Veronika Kudermetova 2018–2025 plan v
  7. Bernarda Pera 2017–2025 plan v
  8. Rebecca Marino 2018–2024 plan v

Closest from another era

  1. Jelena Dokic 2000–2009
  2. Lindsay Davenport 1995–2006
  3. Elena Dementieva 1999–2010

Charted matches