RallyIQ

WTA · Right-handed · 55 charted matches · 2014–2026

Donna Vekic

Archetype: Runs around the backhand · Forehand-dominant

Against an average opponent

Serve points won 60.4% ±2.5 raw 57.6% · tour 56.3% · 4,009 points
Return points won 44.9% ±2.6 raw 41.1% · tour 43.7% · 4,095 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 −0.09 ±0.05 better than 38% of WTA · raw −0.09
Shot selection +0.24 ±0.09 better than 72% of WTA · raw +0.23
Execution −0.33 ±0.37 better than 43% of WTA · raw −0.42
Tactical adaptability −0.04 first serves toward what's working, set to set · 55 matches
Adaptation speed ±0.00 same, every two to three service games · per 100 first serves
Points left on the table 2.67 per 100 shots vs best direction · lower than 39% 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 19,035 shots.

Shot expected value

The share of points Donna Vekic 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 · 1,016 shots

OptionUsedWin %Tour
BH through the middle 33% 40.0%±4.3 43.3%
BH crosscourt 32% 44.3%±4.4 47.6%
BH down the line 17% 40.2%±5.9 46.8%
BH lob crosscourt 4% 34.9%±10.5 32.8%
BH lob through the middle 3% 36.0%±10.7 27.1%
FH inside-out 2% 61.1%±12.0 52.5%
BH drop shot down the line 2% 55.2%±12.2 49.1%
FH inside-in 2% 47.8%±13.0 55.6%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 951 shots

OptionUsedWin %Tour
FH down the line 27% 57.5%±4.9 52.2%
FH through the middle 24% 48.4%±5.2 45.8%
FH crosscourt 18% 53.4%±5.9 52.7%
BH down the line 12% 45.8%±7.2 50.0%
BH through the middle 10% 48.5%±7.6 46.2%
BH crosscourt 4% 41.0%±10.5 50.9%
BH drop shot down the line 2% 49.8%±13.2 47.1%
FH down the line + approach 1% 59.7%±14.0 68.6%

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

position worth 43% to the average player · 911 shots

OptionUsedWin %Tour
FH crosscourt 40% 46.0%±4.2 46.7%
FH through the middle 30% 42.0%±4.8 41.3%
FH down the line 17% 54.0%±6.2 44.9%
FH lob through the middle 4% 24.4%±9.4 29.4%
FH slice through the middle 3% 20.1%±9.9 29.2%
FH slice crosscourt 2% 25.4%±11.8 31.9%
FH lob down the line 2% 25.6%±11.8 27.3%
FH down the line + approach 1% 56.9%±14.9 65.4%

Return +1: drive to your middle

position worth 50% to the average player · 646 shots

OptionUsedWin %Tour
FH down the line 30% 55.8%±5.6 53.0%
FH through the middle 20% 49.5%±6.7 46.5%
FH crosscourt 16% 42.8%±7.3 52.3%
BH through the middle 13% 39.4%±8.0 46.2%
BH down the line 11% 38.8%±8.3 50.6%
BH crosscourt 5% 50.3%±11.4 50.8%
BH drop shot down the line 2% 49.0%±13.7 53.3%
FH down the line + approach 2% 68.2%±13.5 69.2%

Serve under pressure

Pressure predictability index +3 How much less varied Donna Vekic's first-serve direction gets on break points. Positive means easier to read. Based on 426 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 43% 47% 70% / 66%
Body 15% 11% 65% / 57%
T 41% 42% 73% / 68%

1,973 normal · 108 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 48% 50% 68% / 66%
Body 20% 16% 59% / 56%
T 32% 34% 67% / 64%

1,600 normal · 318 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
Wide44% 59.3%±2.6 n=909 44%
Body15% 55.1%±4.4 n=312 0% ▼
T41% 60.3%±2.7 n=860 56% ▲

Consistent with an optimal mix (p = 0.20).
Optimal mix: +0.7 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide48% 56.1%±2.6 n=929 48%
Body19% 57.2%±4.1 n=367 4% ▼
T32% 55.7%±3.2 n=622 48% ▲

Consistent with an optimal mix (p = 0.88).
Optimal mix: +0.2 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: +0.7±2.9 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. (1,220 repeats, 2,669 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 255 42% −2.1±4.8
1stAd courtT 441 30% −5.7±3.5
1stAd courtWide 525 33% −1.8±3.3
1stDeuce courtBody 278 40% −3.1±4.6
1stDeuce courtT 562 31% −1.6±3.1
1stDeuce courtWide 451 31% −2.6±3.5
2ndAd courtBody 294 54% −1.2±4.6
2ndAd courtT 135 55% −0.2±6.4
2ndAd courtWide 311 53% −1.0±4.4
2ndDeuce courtBody 431 56% +1.6±3.8
2ndDeuce courtT 262 54% −1.6±4.8
2ndDeuce courtWide 142 48% −5.4±6.3

Signature patterns

Recurring sequences that win more than Donna Vekic'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 2.6% · won 62% · −0.6±7.2 vs own baseline
  2. T serve (ad court) → FH down the line used 2.6% · won 55% · −7.5±7.5 vs own baseline
  3. Body serve (ad court) → FH down the line used 2.2% · won 53% · −10.2±7.9 vs own baseline
  4. Wide serve (deuce court) → FH down the line used 5.5% · won 55% · −8.4±5.4 vs own baseline
  5. Body serve (deuce court) → BH through the middle used 2.5% · won 49% · −13.5±7.6 vs own baseline

Return

  1. vs wide serve (ad court) → BH through the middle, deep used 3.4% · won 55% · +13.5±6.9 vs own baseline
  2. vs T serve (deuce court) → BH through the middle, deep used 3.2% · won 54% · +11.9±7.0 vs own baseline
  3. vs T serve (deuce court) → BH through the middle, mid used 4.4% · won 50% · +8.1±6.2 vs own baseline
  4. vs wide serve (deuce court) → FH through the middle, deep used 2.8% · won 51% · +9.0±7.5 vs own baseline
  5. vs body serve (deuce court) → FH through the middle, mid used 2.7% · won 50% · +8.1±7.5 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 1.5% · won 59% · +11.7±9.3 vs own baseline
  2. FH through the middle → FH down the line used 2.7% · won 55% · +7.6±7.7 vs own baseline
  3. BH crosscourt → FH down the line used 1.9% · won 56% · +8.9±8.8 vs own baseline
  4. BH through the middle → FH down the line used 2.4% · won 54% · +7.0±8.1 vs own baseline
  5. BH down the line → FH down the line used 2.6% · won 53% · +6.4±7.9 vs own baseline

Discovered sequences

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

  1. FH through the middle → FH through the middle → FH down the line used 0.4% · won 58% · +10.5±10.3 vs own baseline · +13.6 vs tour on the same sequence
  2. BH through the middle → BH through the middle → FH down the line used 0.3% · won 59% · +11.7±11.0 vs own baseline · +19.0 vs tour on the same sequence
  3. FH crosscourt → FH through the middle → FH down the line used 0.8% · won 55% · +7.6±8.7 vs own baseline · +4.2 vs tour on the same sequence Disrupted by Kiki Bertens (9/13), Garbine Muguruza (5/6)
  4. FH crosscourt → FH crosscourt → FH crosscourt used 0.9% · won 54% · +6.4±8.0 vs own baseline · +7.4 vs tour on the same sequence Disrupted by Kiki Bertens (8/11)
  5. BH down the line → FH through the middle → FH down the line used 0.3% · won 58% · +11.2±11.4 vs own baseline · +15.3 vs tour on the same sequence
  6. FH through the middle → BH through the middle → FH crosscourt used 0.2% · won 60% · +12.8±12.3 vs own baseline · +26.3 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+1.3373
FH to their backhand · rally+1.2881
BH to the middle · rally+1.0638
BH to their backhand · return +1+0.9245
FH to the middle · return+0.9835

Most exposed to

FH to their forehand · return−2.2312
T 1st serve · ad court−1.6705
FH to their backhand · rally−1.6921
Wide 2nd serve · deuce court−1.5140
Body 2nd serve · deuce court−1.4418

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +2.87, Caroline Wozniacki +2.61, Daria Kasatkina +2.02, Angelique Kerber +1.95, Sara Errani +1.91

Favourable matchups

Sara Errani +2.08, Angelique Kerber +1.88, Marie Bouzkova +1.61, Elina Avanesyan +1.54, Katie Volynets +1.30

Active players who are best at the shot in the top weakness: Caroline Wozniacki, Su Wei Hsieh, Anhelina Kalinina, Ashlyn Krueger, Katie Boulter

Tactical fingerprint

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

Drop shots / shot3.3%
Forehand share60%
BH down the line28%
FH down the line34%
Wide serves · ad48%
Through the middle33%
Point-ending shots27.5%
Deep returns36%
T serves · deuce41%
Run-around forehands11%
Unforced errors / shot11.7%
Wide serves · deuce44%
Serve & volley0%
Points at net5%
T serves · ad32%
Chipped returns5%
Backhand slice4%
Avg rally length3.7
1st serve in56%

Plays most like

  1. Qinwen Zheng 2022–2026 plan v
  2. Katie Boulter 2018–2025 plan v
  3. Anastasia Pavlyuchenkova 2014–2026 plan v
  4. Xin Yu Wang 2019–2026 plan v
  5. Marta Kostyuk 2018–2026 plan v
  6. Harriet Dart 2018–2025 plan v
  7. Sabine Lisicki 2009–2022 plan v
  8. Aliaksandra Sasnovich 2015–2025 plan v

Closest from another era

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

Charted matches