RallyIQ

WTA · Right-handed · 10 charted matches · 2017–2023

Kateryna Baindl

Archetype: Rarely serves the T · Patient builder

Against an average opponent

Serve points won 53.6% ±3.5 raw 50.8% · tour 56.3% · 713 points
Return points won 42.4% ±3.5 raw 40.8% · tour 43.7% · 679 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 −0.22 ±0.17 better than 15% of WTA · raw −0.20
Shot selection −0.56 ±0.33 better than 10% of WTA · raw −0.52
Execution −0.18 ±0.49 better than 52% of WTA · raw +0.15
Tactical adaptability +0.04 first serves toward what's working, set to set · 10 matches
Adaptation speed +0.14 same, every two to three service games · per 100 first serves
Points left on the table 2.61 per 100 shots vs best direction · lower than 50% 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 3,774 shots.

Shot expected value

The share of points Kateryna Baindl 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 · 271 shots

OptionUsedWin %Tour
BH crosscourt 37% 44.2%±7.4 47.6%
BH through the middle 24% 43.6%±8.9 43.3%
BH down the line 15% 38.3%±10.2 46.8%
BH slice through the middle 9% 28.6%±11.1 34.4%
BH slice crosscourt 8% 36.8%±12.4 40.4%
BH slice down the line 4% 29.2%±13.2 31.7%

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

position worth 43% to the average player · 240 shots

OptionUsedWin %Tour
FH crosscourt 30% 39.5%±8.4 46.7%
FH through the middle 27% 42.0%±8.9 41.3%
FH down the line 27% 35.7%±8.6 44.9%
FH slice through the middle 11% 30.1%±11.1 29.2%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 224 shots

OptionUsedWin %Tour
FH down the line 25% 49.9%±9.5 52.2%
FH crosscourt 22% 37.0%±9.6 52.7%
BH through the middle 19% 56.8%±10.3 46.2%
BH crosscourt 12% 55.7%±11.9 50.9%
FH through the middle 10% 39.9%±12.3 45.8%
BH down the line 10% 44.2%±12.5 50.0%

Long rally, 9+: drive to your backhand side

position worth 44% to the average player · 127 shots

OptionUsedWin %Tour
BH crosscourt 32% 37.0%±10.2 47.9%
BH through the middle 26% 36.9%±10.9 42.7%
BH down the line 16% 43.4%±12.9 46.7%
BH slice through the middle 11% 28.5%±12.7 33.4%
BH slice crosscourt 10% 32.5%±13.4 38.7%

Serve under pressure

Pressure predictability index +1 How much less varied Kateryna Baindl's first-serve direction gets on break points. Positive means easier to read. Based on 102 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 33% 32% 59% / 66%
Body 29% 43% ▲ 60% / 57%
T 37% 25% ▼ 63% / 68%

339 normal · 28 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 32% 38% 59% / 66%
Body 33% 31% 53% / 56%
T 35% 31% 50% / 64%

272 normal · 74 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
Wide33% 52.3%±6.7 n=121 48% ▲
Body31% 54.4%±6.9 n=112 15% ▼
T37% 51.3%±6.4 n=134 37%

Consistent with an optimal mix (p = 0.81).
Optimal mix: +0.3 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide33% 50.8%±6.8 n=115 48% ▲
Body33% 50.0%±6.9 n=114 18% ▼
T34% 45.8%±6.8 n=117 34%

Consistent with an optimal mix (p = 0.53).
Optimal mix: +0.6 per 100 first serves.

Exploitability 0.42 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: −5.9±5.2 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. (243 repeats, 450 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 52 38% −5.9±8.8
1stAd courtT 65 40% +4.1±8.3
1stAd courtWide 90 31% −3.3±7.0
1stDeuce courtBody 53 39% −3.1±8.8
1stDeuce courtT 76 24% −7.9±6.8
1stDeuce courtWide 91 37% +3.3±7.2
2ndAd courtBody 60 56% +1.1±8.6
2ndAd courtT 18 51% −4.0±11.9
2ndAd courtWide 38 50% −3.4±10.0
2ndDeuce courtBody 58 54% −0.7±8.7
2ndDeuce courtT 51 54% −1.9±9.1
2ndDeuce courtWide 25 57% +2.8±11.0

Signature patterns

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

Serve → +1

  1. Body serve (deuce court) → FH down the line used 3.9% · won 59% · +2.0±11.4 vs own baseline
  2. Wide serve (deuce court) → FH through the middle used 3.7% · won 56% · −0.8±11.6 vs own baseline
  3. T serve (deuce court) → BH through the middle used 3.7% · won 50% · −6.8±11.7 vs own baseline
  4. T serve (deuce court) → FH through the middle used 4.1% · won 48% · −8.7±11.5 vs own baseline
  5. Body serve (ad court) → BH through the middle used 4.3% · won 47% · −9.6±11.3 vs own baseline

Return

  1. vs body serve (deuce court) → BH through the middle, mid used 7.1% · won 46% · +1.3±11.6 vs own baseline
  2. vs wide serve (ad court) → BH through the middle, mid used 7.1% · won 42% · −2.7±11.5 vs own baseline
  3. vs T serve (deuce court) → BH through the middle, mid used 8.2% · won 41% · −3.1±11.1 vs own baseline

Rally, consecutive own shots

  1. BH through the middle → FH down the line used 4.0% · won 45% · +3.1±11.7 vs own baseline
  2. BH through the middle → BH crosscourt used 4.2% · won 44% · +2.2±11.5 vs own baseline
  3. FH down the line → BH crosscourt used 5.8% · won 43% · +1.3±10.6 vs own baseline
  4. BH crosscourt → BH crosscourt used 4.4% · won 44% · +1.4±11.4 vs own baseline
  5. FH crosscourt → FH down the line used 6.0% · won 43% · +0.6±10.5 vs own baseline

Discovered sequences

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

  1. FH down the line → BH crosscourt → BH down the line used 0.8% · won 47% · +6.0±12.8 vs own baseline · +6.3 vs tour on the same sequence
  2. FH down the line → BH crosscourt → BH through the middle used 0.9% · won 42% · +1.5±12.4 vs own baseline · +0.6 vs tour on the same sequence
  3. FH crosscourt → FH crosscourt → FH down the line used 1.5% · won 41% · +0.3±11.0 vs own baseline · −6.3 vs tour on the same sequence Disrupted by Maria Timofeeva (4/8)
  4. FH crosscourt → FH crosscourt → FH crosscourt used 1.1% · won 41% · +0.1±11.8 vs own baseline · −7.4 vs tour on the same sequence Disrupted by Maria Timofeeva (3/8)
  5. BH crosscourt → BH crosscourt → BH through the middle used 1.0% · won 39% · −1.7±12.1 vs own baseline · −7.1 vs tour on the same sequence Disrupted by Katerina Siniakova (2/7)
  6. BH crosscourt → BH crosscourt → BH crosscourt used 1.3% · won 38% · −2.4±11.3 vs own baseline · −12.6 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 the middle · return+1.2130
BH to the middle · rally+0.8153
Wide 1st serve · deuce court+0.5121
BH to the middle · return+0.4184
FH to the middle · rally±0.0128

Most exposed to

FH to their backhand · rally−4.2194
FH to the middle · return−2.4120
BH to their backhand · return−2.1126
FH to their forehand · rally−1.1278
T 1st serve · deuce court−1.0138

Active players who are best at the shot in the top weakness: Clara Burel, Victoria Jimenez Kasintseva, Sara Sorribes Tormo, Arianne Hartono, Angelique Kerber

Tactical fingerprint

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

1st serve in71%
Drop shots / shot3.6%
FH down the line34%
Through the middle34%
Avg rally length4.5
BH down the line22%
Backhand slice17%
Deep returns33%
T serves · deuce37%
Serve & volley0%
Chipped returns7%
T serves · ad34%
Unforced errors / shot9.5%
Points at net5%
Run-around forehands3%
Forehand share51%
Wide serves · ad33%
Point-ending shots19.4%
Wide serves · deuce33%

Plays most like

  1. Zarina Diyas 2014–2025 plan v
  2. Viktorija Golubic 2017–2026 plan v
  3. Timea Bacsinszky 2015–2019 plan v
  4. Agnieszka Radwanska 2007–2018 plan v
  5. Simona Halep 2013–2022 plan v
  6. Victoria Azarenka 2009–2025 plan v
  7. Anastasija Sevastova 2011–2025 plan v
  8. Jaqueline Cristian 2021–2026 plan v

Closest from another era

  1. Elena Dementieva 1999–2010
  2. Jennifer Capriati 1990–2002
  3. Martina Hingis 1996–2007

Charted matches