RallyIQ

WTA · Right-handed · 68 charted matches · 2018–2026

Marta Kostyuk

Archetype: Ad-court slider · Avoids the wide serve

Against an average opponent

Serve points won 60.0% ±2.5 raw 58.2% · tour 56.3% · 5,012 points
Return points won 46.8% ±2.6 raw 44.7% · tour 43.7% · 5,119 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 −0.06 ±0.05 better than 43% of WTA · raw −0.06
Shot selection +0.13 ±0.09 better than 60% of WTA · raw +0.13
Execution −0.34 ±0.29 better than 41% of WTA · raw −0.35
Tactical adaptability +0.13 first serves toward what's working, set to set · 68 matches
Adaptation speed +0.29 same, every two to three service games · per 100 first serves
Points left on the table 2.69 per 100 shots vs best direction · lower than 36% 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 25,480 shots.

Shot expected value

The share of points Marta Kostyuk 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 · 1,553 shots

OptionUsedWin %Tour
BH through the middle 32% 43.6%±3.6 43.3%
BH crosscourt 31% 48.0%±3.7 47.6%
BH down the line 13% 51.7%±5.5 46.8%
BH slice through the middle 6% 38.6%±7.3 34.4%
BH slice crosscourt 5% 38.6%±8.4 40.4%
FH inside-out 4% 54.3%±9.0 52.5%
BH slice down the line 2% 27.8%±10.6 31.7%
BH lob through the middle 1% 24.8%±11.0 27.1%

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

position worth 43% to the average player · 1,281 shots

OptionUsedWin %Tour
FH crosscourt 42% 45.7%±3.5 46.7%
FH through the middle 25% 39.9%±4.4 41.3%
FH down the line 17% 49.8%±5.4 44.9%
FH slice through the middle 8% 31.8%±7.1 29.2%
FH slice crosscourt 5% 33.0%±8.6 31.9%
FH slice down the line 2% 26.4%±10.8 24.3%
FH down the line + approach 1% 66.9%±14.1 65.4%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 1,279 shots

OptionUsedWin %Tour
FH down the line 23% 50.1%±4.6 52.2%
FH crosscourt 20% 53.7%±4.9 52.7%
FH through the middle 19% 45.1%±5.0 45.8%
BH through the middle 13% 53.9%±6.0 46.2%
BH crosscourt 8% 50.2%±7.6 50.9%
BH down the line 4% 48.7%±9.4 50.0%
FH down the line + approach 3% 74.9%±9.1 68.6%
BH slice through the middle 3% 52.8%±11.3 44.8%

Return +1: drive to your backhand side

position worth 44% to the average player · 841 shots

OptionUsedWin %Tour
BH crosscourt 38% 42.2%±4.4 47.8%
BH through the middle 32% 37.8%±4.7 43.0%
BH down the line 10% 42.8%±8.1 46.2%
BH slice through the middle 7% 32.5%±8.7 33.2%
BH slice crosscourt 4% 41.4%±11.1 39.6%
FH inside-out 3% 60.7%±12.3 55.4%
BH lob through the middle 2% 26.4%±12.3 26.1%
FH inside-in 1% 55.2%±14.7 55.6%

Serve under pressure

Pressure predictability index +4 How much less varied Marta Kostyuk's first-serve direction gets on break points. Positive means easier to read. Based on 556 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 35% 41% 70% / 66%
Body 25% 21% 60% / 57%
T 40% 38% 72% / 68%

2,466 normal · 140 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 46% 53% 73% / 66%
Body 26% 23% 58% / 56%
T 27% 24% 64% / 64%

1,984 normal · 416 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
Wide36% 61.7%±2.6 n=933 51% ▲
Body24% 55.6%±3.2 n=636 9% ▼
T40% 57.5%±2.5 n=1,037 40%

Off equilibrium (p = 0.018): serve wide more. Gap 3.2 points per 100 first serves.
Optimal mix: +1.1 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide47% 61.1%±2.3 n=1,136 62% ▲
Body26% 53.5%±3.2 n=620 11% ▼
T27% 56.3%±3.1 n=644 27%

Off equilibrium (p = 0.001): serve wide more. Gap 3.3 points per 100 first serves.
Optimal mix: +1.0 per 100 first serves.

Exploitability 1.09 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: +1.8±2.3 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. (1,837 repeats, 3,033 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 277 42% −1.5±4.6
1stAd courtT 673 39% +3.4±3.0
1stAd courtWide 561 36% +2.0±3.3
1stDeuce courtBody 351 43% +0.4±4.2
1stDeuce courtT 546 32% −0.3±3.2
1stDeuce courtWide 759 37% +2.5±2.8
2ndAd courtBody 431 55% +0.4±3.8
2ndAd courtT 206 54% −1.0±5.3
2ndAd courtWide 306 51% −2.3±4.5
2ndDeuce courtBody 478 60% +5.1±3.6
2ndDeuce courtT 268 58% +2.0±4.7
2ndDeuce courtWide 257 58% +3.8±4.8

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 2.2% · won 62% · −1.6±7.1 vs own baseline
  2. Body serve (ad court) → FH down the line used 2.6% · won 55% · −8.2±6.8 vs own baseline
  3. Body serve (ad court) → BH crosscourt used 2.8% · won 53% · −9.9±6.6 vs own baseline
  4. Wide serve (deuce court) → FH down the line used 4.1% · won 54% · −9.3±5.6 vs own baseline
  5. Body serve (deuce court) → FH crosscourt used 2.5% · won 51% · −12.1±7.0 vs own baseline

Return

  1. vs wide serve (ad court) → BH through the middle, deep used 2.2% · won 59% · +14.5±7.2 vs own baseline
  2. vs T serve (ad court) → FH through the middle, deep used 2.7% · won 55% · +11.1±6.7 vs own baseline
  3. vs wide serve (deuce court) → FH through the middle, deep used 2.4% · won 56% · +11.6±7.0 vs own baseline
  4. vs T serve (deuce court) → BH through the middle, deep used 2.5% · won 53% · +8.5±7.0 vs own baseline
  5. vs body serve (deuce court) → BH through the middle, mid used 2.4% · won 50% · +6.0±7.0 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 1.6% · won 56% · +9.1±8.3 vs own baseline
  2. FH crosscourt → FH down the line used 4.5% · won 53% · +5.2±5.4 vs own baseline
  3. BH crosscourt → FH crosscourt used 3.1% · won 54% · +6.1±6.3 vs own baseline
  4. BH through the middle → FH crosscourt used 5.3% · won 52% · +4.4±5.0 vs own baseline
  5. BH crosscourt → FH down the line used 1.6% · won 55% · +7.3±8.2 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Marta Kostyuk 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 crosscourt used 0.8% · won 55% · +7.0±7.6 vs own baseline · +8.9 vs tour on the same sequence Disrupted by Maryna Zanevska (3/6), Qinwen Zheng (5/7)
  2. BH through the middle → BH through the middle → FH down the line used 0.3% · won 58% · +9.9±10.3 vs own baseline · +14.9 vs tour on the same sequence
  3. Wide serve → FH through the middle return, mid → FH down the line + approach used 0.1% · won 63% · +14.4±12.6 vs own baseline · +9.3 vs tour on the same sequence
  4. FH down the line → BH through the middle → BH through the middle used 0.3% · won 58% · +9.7±10.8 vs own baseline · +17.9 vs tour on the same sequence
  5. FH down the line → BH through the middle → FH crosscourt used 0.4% · won 55% · +7.1±9.4 vs own baseline · +1.8 vs tour on the same sequence Disrupted by Paula Badosa (5/8)
  6. FH down the line → BH crosscourt → FH inside-out used 0.3% · won 57% · +9.0±10.9 vs own baseline · +9.6 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 their backhand · return +1+2.0362
FH to the middle · serve +1+1.6553
BH to their backhand · rally+1.5918
FH to their forehand · return +1+1.5498
FH to their backhand · return+1.4472

Most exposed to

Body 2nd serve · ad court−1.6431
BH to the middle · return +1−1.0370
BH to their backhand · return +1−0.9491
BH to the middle · return−0.4944
BH to their backhand · serve +1±0.0563

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +1.53, Caroline Wozniacki +1.34, Daria Kasatkina +0.70, Sara Errani +0.61, Angelique Kerber +0.50

Favourable matchups

Sara Errani +2.02, Marie Bouzkova +1.78, Angelique Kerber +1.77, Elina Avanesyan +1.57, Katie Volynets +1.34

Active players who are best at the shot in the top weakness: Magda Linette, Emma Navarro, Mirra Andreeva, Jessica Pegula, Ons Jabeur

Tactical fingerprint

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

Forehand share57%
Through the middle32%
Wide serves · ad47%
FH down the line32%
T serves · deuce40%
Run-around forehands10%
Points at net9%
Drop shots / shot1.9%
Deep returns34%
Point-ending shots25.0%
Chipped returns12%
Backhand slice14%
Serve & volley0%
Unforced errors / shot10.4%
Avg rally length3.9
BH down the line18%
1st serve in60%
Wide serves · deuce36%
T serves · ad27%

Plays most like

  1. Leylah Fernandez 2020–2026 plan v
  2. Nao Hibino 2016–2025 plan v
  3. Diana Shnaider 2022–2026 plan v
  4. Kaja Juvan 2018–2026 plan v
  5. Bianca Andreescu 2017–2026 plan v
  6. Alexandra Eala 2021–2026 plan v
  7. Xin Yu Wang 2019–2026 plan v
  8. Katie Boulter 2018–2025 plan v

Closest from another era

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

Charted matches