RallyIQ

WTA · Right-handed · 7 charted matches · 2021–2026

Kamilla Rakhimova

Against an average opponent

Serve points won 56.5% ±3.7 raw 54.2% · tour 56.3% · 509 points
Return points won 45.2% ±3.7 raw 43.9% · tour 43.7% · 515 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 +0.11 ±0.08 better than 75% of WTA · raw +0.13
Shot selection −0.26 ±0.13 better than 23% of WTA · raw −0.23
Execution −0.33 ±0.69 better than 43% of WTA · raw −0.12
Points left on the table 2.22 per 100 shots vs best direction · lower than 93% 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 2,803 shots.

Shot expected value

The share of points Kamilla Rakhimova 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 · 213 shots

OptionUsedWin %Tour
FH crosscourt 31% 53.6%±8.9 52.7%
FH through the middle 17% 37.8%±10.7 45.8%
FH down the line 16% 59.0%±10.9 52.2%
BH crosscourt 15% 56.9%±11.2 50.9%
BH through the middle 12% 41.8%±12.0 46.2%
BH down the line 6% 53.1%±14.5 50.0%

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

position worth 45% to the average player · 147 shots

OptionUsedWin %Tour
BH crosscourt 54% 50.0%±8.3 47.6%
BH through the middle 20% 59.3%±11.4 43.3%
BH down the line 11% 51.0%±13.7 46.8%

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

position worth 43% to the average player · 130 shots

OptionUsedWin %Tour
FH crosscourt 56% 42.3%±8.4 46.7%
FH through the middle 23% 38.5%±11.3 41.3%
FH down the line 11% 49.9%±14.1 44.9%

Return +1: drive to your middle

position worth 50% to the average player · 92 shots

OptionUsedWin %Tour
FH crosscourt 28% 55.4%±12.1 52.3%
BH crosscourt 24% 40.8%±12.5 50.8%
BH through the middle 16% 52.1%±13.9 46.2%
FH through the middle 14% 43.4%±14.2 46.5%
FH down the line 11% 62.0%±14.6 53.0%

Serve under pressure

Pressure predictability index +14 How much less varied Kamilla Rakhimova's first-serve direction gets on break points. Positive means easier to read. Based on 60 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 36% 29% 64% / 66%
Body 27% 65% ▲ 47% / 57%
T 37% 6% ▼ 69% / 68%

249 normal · 17 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 47% 49% 68% / 66%
Body 18% 9% ▼ 55% / 56%
T 35% 42% 63% / 64%

196 normal · 43 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
Wide35% 56.2%±7.3 n=94 36%
Body29% 43.9%±7.9 n=78 14% ▼
T35% 61.0%±7.2 n=94 50% ▲

Off equilibrium (p = 0.007): serve T more. Gap 6.7 points per 100 first serves.
Optimal mix: +1.2 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide47% 55.6%±6.8 n=113 62% ▲
Body17% 55.5%±9.8 n=40 2% ▼
T36% 53.5%±7.6 n=86 36%

Consistent with an optimal mix (p = 0.91).
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.82 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: −4.4±11.3 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. (157 repeats, 334 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 42 39% −4.8±9.5
1stAd courtT 41 32% −3.6±9.1
1stAd courtWide 90 36% +1.7±7.2
1stDeuce courtBody 55 40% −2.9±8.7
1stDeuce courtT 56 38% +5.8±8.6
1stDeuce courtWide 70 38% +4.2±8.0
2ndAd courtBody 26 53% −2.3±11.0
2ndAd courtT 17 61% +5.6±11.7
2ndAd courtWide 26 52% −1.6±11.0
2ndDeuce courtBody 38 64% +9.3±9.6
2ndDeuce courtT 18 54% −2.3±11.8
2ndDeuce courtWide 35 54% +0.3±10.2

Signature patterns

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

Serve → +1

  1. Body serve (deuce court) → BH crosscourt used 6.6% · won 57% · −0.2±11.5 vs own baseline
  2. Body serve (deuce court) → FH crosscourt used 6.9% · won 47% · −10.9±11.5 vs own baseline

Return

  1. Not enough data

Rally, consecutive own shots

  1. FH crosscourt → FH crosscourt used 10.3% · won 55% · +2.9±9.3 vs own baseline
  2. FH crosscourt → BH crosscourt used 5.4% · won 56% · +3.9±11.3 vs own baseline
  3. BH crosscourt → FH crosscourt used 7.7% · won 53% · +1.3±10.3 vs own baseline
  4. FH through the middle → FH crosscourt used 4.9% · won 52% · +0.2±11.6 vs own baseline
  5. BH crosscourt → BH through the middle used 5.4% · won 52% · +0.1±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 Kamilla Rakhimova wins the point once the sequence happens, weighted by how often it happens. Think of them as chess openings.

  1. BH crosscourt → BH crosscourt → BH crosscourt used 1.2% · won 52% · +1.0±12.7 vs own baseline · +4.3 vs tour on the same sequence Disrupted by Jaqueline Cristian (5/8)
  2. FH crosscourt → FH crosscourt → FH crosscourt used 1.4% · won 49% · −1.4±12.4 vs own baseline · −0.9 vs tour on the same sequence Disrupted by Jaqueline Cristian (3/7), Jessica Pegula (3/6)
  3. FH crosscourt → FH crosscourt → FH through the middle used 1.1% · won 47% · −4.0±13.0 vs own baseline · −3.2 vs tour on the same sequence Disrupted by Jaqueline Cristian (3/9)

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 the middle · return+0.5120
BH to their backhand · rally−0.6135
FH to their forehand · rally−1.5193
FH to their backhand · rally−1.9175

Most exposed to

Wide 1st serve · ad court−2.2125
FH to the middle · rally−1.8136
FH to their backhand · rally+0.3153
BH to the middle · return+0.3124
FH to their forehand · rally+1.1162

Active players who are best at the shot in the top weakness: Taylor Townsend, Rebecca Marino, Caroline Dolehide, Petra Kvitova, Serena Williams

Charted matches