RallyIQ

WTA · Right-handed · 58 charted matches · 2016–2026

Aryna Sabalenka

Archetype: First-strike aggressor · Short-point player

Against an average opponent

Serve points won 62.0% ±2.5 raw 61.1% · tour 56.3% · 3,995 points
Return points won 45.9% ±2.6 raw 43.4% · tour 43.7% · 4,000 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 +0.36 ±0.05 better than 97% of WTA · raw +0.36
Shot selection +0.04 ±0.10 better than 49% of WTA · raw +0.03
Execution −0.05 ±0.37 better than 59% of WTA · raw −0.13
Tactical adaptability −0.12 first serves toward what's working, set to set · 56 matches
Adaptation speed −0.12 same, every two to three service games · per 100 first serves
Points left on the table 2.23 per 100 shots vs best direction · lower than 92% 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 17,308 shots.

Shot expected value

The share of points Aryna Sabalenka 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 · 787 shots

OptionUsedWin %Tour
FH crosscourt 27% 56.8%±5.3 52.7%
FH down the line 19% 50.6%±6.3 52.2%
BH crosscourt 15% 56.7%±6.9 50.9%
FH through the middle 11% 43.7%±7.9 45.8%
BH through the middle 9% 42.0%±8.5 46.2%
BH down the line 8% 51.2%±8.9 50.0%
FH crosscourt + approach 2% 71.7%±13.1 69.7%
FH down the line + approach 1% 72.4%±13.4 68.6%

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

position worth 45% to the average player · 730 shots

OptionUsedWin %Tour
BH crosscourt 45% 53.8%±4.4 47.6%
BH through the middle 18% 51.4%±6.6 43.3%
BH down the line 13% 41.7%±7.5 46.8%
BH slice through the middle 10% 28.9%±7.7 34.4%
BH slice crosscourt 6% 43.2%±10.1 40.4%
BH slice down the line 3% 17.9%±9.9 31.7%

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

position worth 43% to the average player · 683 shots

OptionUsedWin %Tour
FH crosscourt 50% 50.8%±4.3 46.7%
FH down the line 20% 43.6%±6.5 44.9%
FH through the middle 16% 42.3%±7.2 41.3%
FH slice through the middle 7% 38.4%±9.6 29.2%
FH slice crosscourt 3% 38.5%±12.7 31.9%
FH slice down the line 3% 37.5%±13.1 24.3%

Return +1: drive to your middle

position worth 50% to the average player · 607 shots

OptionUsedWin %Tour
FH crosscourt 29% 52.3%±5.9 52.3%
BH crosscourt 16% 53.5%±7.6 50.8%
FH down the line 15% 52.3%±7.8 53.0%
BH through the middle 10% 49.1%±9.1 46.2%
BH down the line 10% 54.0%±9.3 50.6%
FH through the middle 9% 51.0%±9.4 46.5%
FH crosscourt + approach 3% 74.6%±11.6 66.8%
BH slice through the middle 2% 34.9%±13.9 45.9%

Serve under pressure

Pressure predictability index +9 How much less varied Aryna Sabalenka's first-serve direction gets on break points. Positive means easier to read. Based on 364 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 51% 49% 71% / 66%
Body 18% 14% 56% / 57%
T 31% 37% 72% / 68%

1,979 normal · 90 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 55% 62% 68% / 66%
Body 13% 7% 50% / 56%
T 31% 30% 71% / 64%

1,630 normal · 274 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
Wide51% 65.8%±2.4 n=1,053 66% ▲
Body18% 55.8%±4.0 n=379 3% ▼
T31% 60.8%±3.1 n=637 31%

Off equilibrium (p < 0.001): serve wide more. Gap 3.4 points per 100 first serves.
Optimal mix: +1.4 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide56% 59.9%±2.4 n=1,073 54% ▼
Body12% 55.1%±5.0 n=236 0% ▼
T31% 61.0%±3.2 n=595 46% ▲

Consistent with an optimal mix (p = 0.19).
Optimal mix: +0.9 per 100 first serves.

Exploitability 1.14 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: +0.8±2.1 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. (1,354 repeats, 2,503 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 243 45% +1.2±5.0
1stAd courtT 378 35% −0.3±3.9
1stAd courtWide 529 34% −0.2±3.3
1stDeuce courtBody 291 38% −4.7±4.5
1stDeuce courtT 345 26% −5.8±3.7
1stDeuce courtWide 609 34% −0.2±3.1
2ndAd courtBody 360 54% −1.3±4.2
2ndAd courtT 112 60% +4.5±6.8
2ndAd courtWide 302 56% +2.8±4.5
2ndDeuce courtBody 441 55% +0.6±3.8
2ndDeuce courtT 170 65% +9.4±5.5
2ndDeuce courtWide 207 54% +0.7±5.3

Signature patterns

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

Serve → +1

  1. T serve (ad court) → FH crosscourt used 2.4% · won 64% · −2.1±7.3 vs own baseline
  2. Body serve (deuce court) → FH crosscourt used 2.4% · won 63% · −2.6±7.3 vs own baseline
  3. Wide serve (ad court) → BH crosscourt used 2.8% · won 61% · −4.9±7.0 vs own baseline
  4. Body serve (deuce court) → BH crosscourt used 2.9% · won 61% · −5.3±7.0 vs own baseline
  5. Body serve (ad court) → FH crosscourt used 2.3% · won 58% · −8.3±7.7 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, mid used 4.3% · won 60% · +15.9±6.2 vs own baseline
  2. vs wide serve (deuce court) → FH crosscourt, deep used 2.8% · won 58% · +14.2±7.4 vs own baseline
  3. vs wide serve (ad court) → BH crosscourt, deep used 2.7% · won 58% · +13.6±7.6 vs own baseline
  4. vs body serve (deuce court) → BH through the middle, deep used 2.6% · won 57% · +13.2±7.6 vs own baseline
  5. vs wide serve (ad court) → BH through the middle, deep used 2.4% · won 55% · +10.8±7.9 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → FH crosscourt used 6.7% · won 61% · +9.5±6.5 vs own baseline
  2. BH crosscourt → BH crosscourt used 6.7% · won 55% · +4.1±6.6 vs own baseline
  3. FH crosscourt → BH crosscourt used 5.4% · won 56% · +4.3±7.2 vs own baseline
  4. BH crosscourt → BH through the middle used 2.3% · won 56% · +5.0±9.7 vs own baseline
  5. FH slice through the middle → BH crosscourt used 1.2% · won 58% · +6.3±11.4 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Aryna Sabalenka 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 1.0% · won 62% · +11.2±8.0 vs own baseline · +12.3 vs tour on the same sequence Disrupted by Kiki Bertens (4/6), Emma Raducanu (5/6)
  2. BH crosscourt → BH crosscourt → BH through the middle used 0.5% · won 60% · +8.8±10.1 vs own baseline · +21.9 vs tour on the same sequence Disrupted by Qinwen Zheng (3/6)
  3. Body serve → BH through the middle return, mid → FH crosscourt used 0.4% · won 61% · +10.0±11.1 vs own baseline · +17.4 vs tour on the same sequence
  4. BH crosscourt → BH slice through the middle → FH crosscourt used 0.3% · won 62% · +11.1±12.2 vs own baseline · +17.8 vs tour on the same sequence
  5. BH crosscourt → BH crosscourt → BH crosscourt used 1.6% · won 56% · +4.4±6.9 vs own baseline · +7.9 vs tour on the same sequence Disrupted by Ekaterina Alexandrova (1/6), Maria Sakkari (2/8)
  6. Wide serve → FH crosscourt return, mid → FH down the line used 0.4% · won 60% · +8.8±11.1 vs own baseline · +17.7 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 forehand · return+2.3563
FH to their forehand · rally+2.2849
T 2nd serve · deuce court+2.2149
BH to their forehand · return +1+1.6166
Wide 1st serve · deuce court+1.51,053

Most exposed to

BH to their backhand · return +1−3.3232
BH to their forehand · return +1−2.4145
BH to their forehand · rally−1.8315
FH to their forehand · return +1−1.7263
FH to the middle · serve +1−1.5357

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +2.14, Caroline Wozniacki +1.87, Tatjana Maria +1.32, Daria Kasatkina +1.27, Angelique Kerber +1.13

Favourable matchups

Sara Errani +1.96, Angelique Kerber +1.37, Elina Avanesyan +1.37, Marie Bouzkova +1.27, Katie Volynets +1.08

Active players who are best at the shot in the top weakness: Caroline Wozniacki, Sara Errani, Jessica Pegula, Mirra Andreeva, Danielle Collins

Tactical fingerprint

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

Point-ending shots35.6%
Wide serves · ad56%
Drop shots / shot3.0%
Wide serves · deuce51%
Unforced errors / shot12.6%
BH down the line24%
Deep returns35%
FH down the line31%
Chipped returns13%
Points at net8%
1st serve in63%
Backhand slice15%
Serve & volley0%
Forehand share53%
Run-around forehands6%
T serves · ad31%
T serves · deuce31%
Avg rally length3.3
Through the middle21%

Plays most like

  1. Daniela Hantuchova 2002–2015 plan v
  2. Aliaksandra Sasnovich 2015–2025 plan v
  3. Johanna Konta 2013–2020 plan v
  4. Danielle Collins 2018–2025 plan v
  5. Anastasia Pavlyuchenkova 2014–2026 plan v
  6. Sabine Lisicki 2009–2022 plan v
  7. Amanda Anisimova 2017–2026 plan v
  8. Anna Kalinskaya 2019–2026 plan v

Closest from another era

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

Charted matches