RallyIQ

WTA · Right-handed · 76 charted matches · 2017–2026

Amanda Anisimova

Archetype: First-strike aggressor · Short-point player

Against an average opponent

Serve points won 58.5% ±2.5 raw 57.6% · tour 56.3% · 5,367 points
Return points won 47.4% ±2.6 raw 44.8% · tour 43.7% · 5,405 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 +0.21 ±0.05 better than 87% of WTA · raw +0.21
Shot selection +0.22 ±0.06 better than 69% of WTA · raw +0.21
Execution −1.05 ±0.38 better than 17% of WTA · raw −1.06
Tactical adaptability +0.02 first serves toward what's working, set to set · 74 matches
Adaptation speed ±0.00 same, every two to three service games · per 100 first serves
Points left on the table 2.27 per 100 shots vs best direction · lower than 88% 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 22,781 shots.

Shot expected value

The share of points Amanda Anisimova 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 · 1,310 shots

OptionUsedWin %Tour
FH down the line 25% 59.0%±4.3 52.2%
FH crosscourt 22% 48.7%±4.7 52.7%
FH through the middle 14% 42.8%±5.7 45.8%
BH down the line 13% 52.9%±6.0 50.0%
BH through the middle 11% 48.4%±6.3 46.2%
BH crosscourt 10% 49.1%±6.7 50.9%
FH down the line + approach 1% 64.9%±13.3 68.6%
FH slice down the line 1% 54.9%±14.5 47.9%

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

position worth 43% to the average player · 930 shots

OptionUsedWin %Tour
FH crosscourt 47% 45.1%±3.8 46.7%
FH down the line 25% 42.3%±5.2 44.9%
FH through the middle 21% 37.7%±5.5 41.3%
FH slice through the middle 3% 23.2%±9.7 29.2%
FH slice crosscourt 2% 30.0%±12.2 31.9%
FH slice down the line 1% 18.9%±11.6 24.3%

Return +1: drive to your middle

position worth 50% to the average player · 912 shots

OptionUsedWin %Tour
FH down the line 24% 55.1%±5.3 53.0%
FH crosscourt 18% 51.6%±6.0 52.3%
BH down the line 15% 59.2%±6.4 50.6%
BH through the middle 15% 40.0%±6.5 46.2%
BH crosscourt 14% 50.8%±6.8 50.8%
FH through the middle 11% 46.5%±7.5 46.5%

Serve +1: mid-depth return to your middle

position worth 51% to the average player · 815 shots

OptionUsedWin %Tour
FH down the line 23% 57.7%±5.6 53.3%
FH crosscourt 23% 47.9%±5.8 54.0%
BH crosscourt 16% 55.4%±6.7 52.5%
BH through the middle 14% 49.5%±7.1 46.3%
BH down the line 12% 51.4%±7.6 51.0%
FH through the middle 11% 51.0%±7.9 45.5%
FH down the line + approach 1% 81.6%±11.4 71.5%

Serve under pressure

Pressure predictability index ±0 How much less varied Amanda Anisimova's first-serve direction gets on break points. Positive means easier to read. Based on 611 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 40% 42% 63% / 66%
Body 18% 15% 58% / 57%
T 42% 43% 64% / 68%

2,647 normal · 142 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 53% 51% 66% / 66%
Body 16% 17% 57% / 56%
T 31% 33% 66% / 64%

2,099 normal · 469 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% 56.8%±2.4 n=1,121 48% ▲
Body18% 57.2%±3.5 n=505 3% ▼
T42% 56.7%±2.4 n=1,163 49% ▲

Consistent with an optimal mix (p = 0.98).
Optimal mix: +0.2 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide52% 58.6%±2.2 n=1,340 53%
Body17% 55.5%±3.8 n=425 1% ▼
T31% 60.1%±2.8 n=803 46% ▲

Consistent with an optimal mix (p = 0.23).
Optimal mix: +0.7 per 100 first serves.

Exploitability 0.43 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: +0.4±2.6 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. (1,868 repeats, 3,337 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 350 49% +4.8±4.2
1stAd courtT 639 39% +3.1±3.1
1stAd courtWide 586 32% −2.1±3.1
1stDeuce courtBody 434 43% +0.7±3.8
1stDeuce courtT 578 31% −1.4±3.1
1stDeuce courtWide 746 36% +1.8±2.8
2ndAd courtBody 475 57% +1.5±3.6
2ndAd courtT 221 56% +0.9±5.2
2ndAd courtWide 326 52% −1.3±4.4
2ndDeuce courtBody 553 56% +2.0±3.4
2ndDeuce courtT 199 62% +6.3±5.3
2ndDeuce courtWide 291 60% +6.4±4.5

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → BH crosscourt used 2.9% · won 60% · −2.7±6.1 vs own baseline
  2. Wide serve (ad court) → FH crosscourt used 3.7% · won 59% · −3.6±5.6 vs own baseline
  3. T serve (deuce court) → FH crosscourt used 2.1% · won 54% · −7.8±7.2 vs own baseline
  4. Wide serve (deuce court) → BH crosscourt used 2.5% · won 55% · −7.3±6.7 vs own baseline
  5. T serve (deuce court) → BH crosscourt used 2.5% · won 54% · −8.4±6.7 vs own baseline

Return

  1. vs wide serve (deuce court) → FH crosscourt, mid used 2.7% · won 61% · +15.7±6.5 vs own baseline
  2. vs body serve (deuce court) → BH through the middle, deep used 2.0% · won 62% · +17.0±7.2 vs own baseline
  3. vs T serve (ad court) → FH through the middle, deep used 2.6% · won 60% · +14.9±6.6 vs own baseline
  4. vs T serve (deuce court) → BH through the middle, deep used 2.2% · won 60% · +15.5±7.0 vs own baseline
  5. vs wide serve (deuce court) → FH through the middle, deep used 2.9% · won 58% · +12.9±6.4 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH down the line used 2.8% · won 65% · +15.9±7.4 vs own baseline
  2. FH crosscourt → BH crosscourt used 5.4% · won 57% · +7.9±5.9 vs own baseline
  3. FH down the line → FH crosscourt used 3.5% · won 59% · +9.5±7.1 vs own baseline
  4. BH down the line → FH down the line used 2.8% · won 58% · +8.6±7.7 vs own baseline
  5. BH crosscourt → FH crosscourt used 5.5% · won 55% · +5.9±5.9 vs own baseline

Discovered sequences

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

  1. Wide serve → BH through the middle return, mid → FH down the line used 0.3% · won 67% · +17.2±10.1 vs own baseline · +23.1 vs tour on the same sequence
  2. FH down the line → BH slice through the middle → FH down the line used 0.4% · won 63% · +13.5±9.9 vs own baseline · +10.3 vs tour on the same sequence
  3. BH crosscourt → BH down the line → FH crosscourt used 0.6% · won 60% · +10.4±8.5 vs own baseline · +16.3 vs tour on the same sequence Disrupted by Jessica Pegula (5/8)
  4. FH crosscourt → FH through the middle → FH down the line used 1.1% · won 57% · +7.1±6.9 vs own baseline · +4.6 vs tour on the same sequence Disrupted by Jasmine Paolini (3/7), Marta Kostyuk (4/7)
  5. FH down the line → BH through the middle → FH down the line used 0.5% · won 60% · +10.4±9.4 vs own baseline · +12.3 vs tour on the same sequence Disrupted by Mirra Andreeva (4/6)
  6. BH down the line → FH through the middle → FH down the line used 0.5% · won 60% · +10.2±9.2 vs own baseline · +10.8 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 backhand · return +1+1.9434
Body 2nd serve · deuce court+1.9475
BH to their forehand · serve +1+1.6417
BH to their forehand · return +1+1.3280
Body 2nd serve · ad court+1.1390

Most exposed to

FH slice to the middle · rally−0.7165
T 1st serve · deuce court−0.61,001
BH to the middle · return−0.51,391
Body 2nd serve · ad court−0.5446
Wide 1st serve · deuce court−0.31,148

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +1.72, Caroline Wozniacki +1.40, Tatjana Maria +1.12, Daria Kasatkina +0.79, Sara Errani +0.76

Favourable matchups

Sara Errani +0.94, Angelique Kerber +0.45, Elina Avanesyan +0.28, Marie Bouzkova +0.17, Katie Volynets −0.05

Active players who are best at the shot in the top weakness: Belinda Bencic, Tatjana Maria, Mirra Andreeva, Elina Svitolina, Karolina Muchova

Tactical fingerprint

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

Point-ending shots36.9%
Unforced errors / shot15.3%
FH down the line36%
BH down the line28%
Deep returns39%
Wide serves · ad52%
T serves · deuce42%
Forehand share55%
1st serve in63%
Wide serves · deuce40%
Serve & volley0%
Drop shots / shot1.3%
Run-around forehands5%
Backhand slice7%
Chipped returns5%
Points at net5%
T serves · ad31%
Through the middle24%
Avg rally length3.3

Plays most like

  1. Talia Gibson 2024–2026 plan v
  2. Petra Kvitova 2010–2025 plan v
  3. Daniela Hantuchova 2002–2015 plan v
  4. Aliaksandra Sasnovich 2015–2025 plan v
  5. Dayana Yastremska 2013–2026 plan v
  6. Anastasia Pavlyuchenkova 2014–2026 plan v
  7. Ekaterina Alexandrova 2017–2026 plan v
  8. Danielle Collins 2018–2025 plan v

Closest from another era

  1. Jelena Dokic 2000–2009
  2. Lindsay Davenport 1995–2006
  3. Mary Pierce 1994–2005

Charted matches