RallyIQ

WTA · Right-handed · 99 charted matches · 2009–2025

Victoria Azarenka

Archetype: Forehand line-changer · Backhand line-changer

Against an average opponent

Serve points won 58.8% ±2.4 raw 56.5% · tour 56.3% · 6,819 points
Return points won 47.2% ±2.5 raw 45.4% · tour 43.7% · 6,921 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 65% of WTA · raw +0.05
Shot selection +0.21 ±0.07 better than 67% of WTA · raw +0.19
Execution +0.96 ±0.29 better than 90% of WTA · raw +0.86
Tactical adaptability +0.18 first serves toward what's working, set to set · 96 matches
Adaptation speed +0.16 same, every two to three service games · per 100 first serves
Points left on the table 2.42 per 100 shots vs best direction · lower than 74% 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 34,333 shots.

Shot expected value

The share of points Victoria Azarenka 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 forehand side

position worth 43% to the average player · 2,234 shots

OptionUsedWin %Tour
FH crosscourt 39% 48.9%±2.8 46.7%
FH down the line 30% 47.5%±3.1 44.9%
FH through the middle 23% 39.9%±3.5 41.3%
FH slice through the middle 4% 29.9%±7.4 29.2%
FH slice down the line 2% 20.1%±8.6 24.3%
FH down the line + approach 1% 71.9%±10.9 65.4%
FH slice crosscourt 1% 29.7%±12.7 31.9%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 2,044 shots

OptionUsedWin %Tour
FH down the line 22% 57.6%±3.7 52.2%
FH crosscourt 21% 56.0%±3.8 52.7%
FH through the middle 15% 42.0%±4.5 45.8%
BH through the middle 15% 49.8%±4.6 46.2%
BH down the line 11% 54.4%±5.2 50.0%
BH crosscourt 10% 59.4%±5.4 50.9%
FH down the line + approach 1% 72.5%±11.5 68.6%
FH crosscourt + approach 1% 72.1%±12.3 69.7%

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

position worth 45% to the average player · 1,981 shots

OptionUsedWin %Tour
BH crosscourt 39% 48.8%±2.9 47.6%
BH through the middle 27% 45.6%±3.5 43.3%
BH down the line 13% 53.6%±5.0 46.8%
BH slice through the middle 7% 29.1%±5.9 34.4%
BH slice crosscourt 6% 35.7%±6.6 40.4%
BH slice down the line 3% 23.5%±7.9 31.7%
BH down the line + approach 1% 66.0%±11.7 70.2%
BH lob through the middle 1% 21.9%±10.4 27.1%

Return +1: drive to your middle

position worth 50% to the average player · 1,299 shots

OptionUsedWin %Tour
FH crosscourt 23% 54.9%±4.6 52.3%
FH down the line 17% 52.5%±5.3 53.0%
BH through the middle 16% 51.4%±5.4 46.2%
BH down the line 14% 55.8%±5.8 50.6%
FH through the middle 14% 43.8%±5.8 46.5%
BH crosscourt 10% 56.9%±6.7 50.8%
FH down the line + approach 1% 71.4%±11.9 69.2%
BH crosscourt + approach 1% 70.3%±12.9 64.5%

Serve under pressure

Pressure predictability index +1 How much less varied Victoria Azarenka's first-serve direction gets on break points. Positive means easier to read. Based on 808 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 40% 40% 65% / 66%
Body 19% 17% 58% / 57%
T 41% 43% 68% / 68%

3,346 normal · 197 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 41% 46% 67% / 66%
Body 21% 20% 57% / 56%
T 38% 34% 60% / 64%

2,657 normal · 611 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
Wide40% 57.3%±2.1 n=1,430 41%
Body18% 54.3%±3.1 n=655 3% ▼
T41% 58.7%±2.1 n=1,458 56% ▲

Consistent with an optimal mix (p = 0.12).
Optimal mix: +0.7 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide42% 57.1%±2.2 n=1,374 57% ▲
Body21% 54.6%±3.1 n=677 6% ▼
T37% 54.6%±2.3 n=1,217 37%

Consistent with an optimal mix (p = 0.28).
Optimal mix: +0.6 per 100 first serves.

Exploitability 0.65 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: +0.5±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. (2,526 repeats, 4,087 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 402 49% +5.0±4.0
1stAd courtT 941 38% +2.1±2.6
1stAd courtWide 702 31% −3.0±2.8
1stDeuce courtBody 506 44% +1.4±3.5
1stDeuce courtT 796 34% +1.6±2.7
1stDeuce courtWide 966 35% +0.7±2.5
2ndAd courtBody 558 59% +3.9±3.3
2ndAd courtT 251 62% +7.1±4.8
2ndAd courtWide 463 58% +4.1±3.7
2ndDeuce courtBody 673 56% +1.9±3.1
2ndDeuce courtT 376 65% +9.0±3.9
2ndDeuce courtWide 274 56% +2.2±4.7

Signature patterns

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

Serve → +1

  1. T serve (deuce court) → FH crosscourt used 2.1% · won 63% · +1.8±6.3 vs own baseline
  2. Body serve (ad court) → BH crosscourt used 2.1% · won 59% · −2.2±6.4 vs own baseline
  3. T serve (ad court) → FH crosscourt used 2.3% · won 57% · −3.7±6.2 vs own baseline
  4. T serve (deuce court) → FH down the line used 2.3% · won 57% · −3.7±6.2 vs own baseline
  5. T serve (deuce court) → BH crosscourt used 2.2% · won 56% · −5.2±6.4 vs own baseline

Return

  1. vs T serve (deuce court) → BH through the middle, deep used 2.7% · won 63% · +16.9±5.8 vs own baseline
  2. vs wide serve (deuce court) → FH crosscourt, mid used 2.6% · won 59% · +13.0±6.0 vs own baseline
  3. vs T serve (ad court) → FH through the middle, deep used 2.8% · won 59% · +12.3±5.8 vs own baseline
  4. vs wide serve (ad court) → BH crosscourt, mid used 3.7% · won 54% · +7.7±5.2 vs own baseline
  5. vs T serve (deuce court) → BH through the middle, mid used 3.4% · won 54% · +7.8±5.4 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → FH crosscourt used 3.7% · won 62% · +13.3±4.5 vs own baseline
  2. FH crosscourt → BH crosscourt used 2.7% · won 60% · +10.7±5.3 vs own baseline
  3. FH down the line → BH down the line used 2.4% · won 59% · +10.5±5.5 vs own baseline
  4. BH crosscourt → FH down the line used 2.2% · won 58% · +9.1±5.8 vs own baseline
  5. FH down the line → FH crosscourt used 2.2% · won 58% · +9.0±5.8 vs own baseline

Discovered sequences

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

  1. FH crosscourt → FH down the line → BH crosscourt used 0.6% · won 61% · +11.9±7.1 vs own baseline · +14.6 vs tour on the same sequence Disrupted by Maria Sharapova (3/7), Serena Williams (6/11)
  2. FH down the line → BH through the middle → BH crosscourt used 0.3% · won 65% · +15.8±9.1 vs own baseline · +21.4 vs tour on the same sequence
  3. BH crosscourt → BH through the middle → FH crosscourt used 0.7% · won 59% · +9.2±6.7 vs own baseline · +6.8 vs tour on the same sequence Disrupted by Maria Sharapova (1/8), Paula Badosa (3/6)
  4. BH crosscourt → BH through the middle → FH down the line used 0.5% · won 60% · +10.8±7.7 vs own baseline · +10.2 vs tour on the same sequence Disrupted by Sara Sorribes Tormo (3/6), Karolina Pliskova (6/7)
  5. BH crosscourt → BH slice crosscourt → BH down the line used 0.2% · won 64% · +14.7±9.7 vs own baseline · +18.7 vs tour on the same sequence Disrupted by Ashleigh Barty (6/6)
  6. BH crosscourt → BH slice down the line → FH crosscourt used 0.1% · won 68% · +18.6±11.0 vs own baseline · +32.8 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

BH to their forehand · return +1+4.2364
FH volley to their forehand · rally+3.6123
FH to their forehand · return +1+2.8693
BH to their forehand · return+2.6475
FH to their backhand · return+2.5671

Most exposed to

BH to their forehand · return +1−2.4393
BH to their backhand · serve +1−2.3708
FH to their backhand · return +1−1.9428
BH slice to their forehand · rally−1.5175
FH to their forehand · return−1.4713

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +3.39, Caroline Wozniacki +3.16, Angelique Kerber +2.68, Daria Kasatkina +2.59, Sara Errani +2.39

Favourable matchups

Sara Errani +3.25, Angelique Kerber +3.05, Marie Bouzkova +2.83, Elina Avanesyan +2.65, Magdalena Frech +2.40

Active players who are best at the shot in the top weakness: Iga Swiatek, Caroline Wozniacki, Leylah Fernandez, Jessica Pegula, Angelique Kerber

Tactical fingerprint

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

FH down the line38%
BH down the line25%
1st serve in66%
Deep returns36%
T serves · deuce41%
Points at net9%
Forehand share55%
Wide serves · ad42%
Avg rally length4.1
Wide serves · deuce40%
T serves · ad37%
Serve & volley0%
Backhand slice13%
Through the middle28%
Chipped returns7%
Point-ending shots22.4%
Drop shots / shot1.1%
Run-around forehands1%
Unforced errors / shot8.4%

Plays most like

  1. Alison Riske Amritraj 2014–2022 plan v
  2. Sorana Cirstea 2014–2026 plan v
  3. Mona Barthel 2012–2021 plan v
  4. Elise Mertens 2018–2026 plan v
  5. Leylah Fernandez 2020–2026 plan v
  6. Linda Fruhvirtova 2022–2025 plan v
  7. Belinda Bencic 2014–2026 plan v
  8. Vera Zvonareva 2003–2020 plan v

Closest from another era

  1. Lindsay Davenport 1995–2006
  2. Martina Hingis 1996–2007
  3. Monica Seles 1990–2003

Charted matches