RallyIQ

WTA · Right-handed · 14 charted matches · 2016–2026

Kimberly Birrell

Archetype: Ad-court T server · Rallies through the middle

Against an average opponent

Serve points won 54.4% ±3.4 raw 51.0% · tour 56.3% · 834 points
Return points won 39.0% ±3.3 raw 34.6% · tour 43.7% · 801 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 ±0.18 better than 34% of WTA · raw −0.11
Shot selection +0.29 ±0.15 better than 77% of WTA · raw +0.30
Execution −1.63 ±0.97 better than 8% of WTA · raw −1.51
Tactical adaptability +0.06 first serves toward what's working, set to set · 14 matches
Adaptation speed +0.10 same, every two to three service games · per 100 first serves
Points left on the table 2.49 per 100 shots vs best direction · lower than 67% 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 4,272 shots.

Shot expected value

The share of points Kimberly Birrell 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 · 300 shots

OptionUsedWin %Tour
FH crosscourt 28% 49.6%±8.1 52.7%
FH through the middle 20% 43.9%±9.1 45.8%
BH crosscourt 17% 51.0%±9.8 50.9%
BH through the middle 15% 41.0%±10.1 46.2%
FH down the line 13% 47.4%±10.6 52.2%
BH down the line 7% 53.7%±12.8 50.0%

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

position worth 45% to the average player · 257 shots

OptionUsedWin %Tour
BH crosscourt 44% 50.8%±7.1 47.6%
BH through the middle 30% 39.5%±8.1 43.3%
BH down the line 18% 45.3%±10.0 46.8%

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

position worth 43% to the average player · 242 shots

OptionUsedWin %Tour
FH crosscourt 46% 47.6%±7.2 46.7%
FH through the middle 28% 38.9%±8.6 41.3%
FH down the line 22% 43.8%±9.6 44.9%

Serve +1: mid-depth return to your middle

position worth 51% to the average player · 150 shots

OptionUsedWin %Tour
BH through the middle 25% 47.0%±10.8 46.3%
FH crosscourt 20% 47.6%±11.6 54.0%
BH crosscourt 18% 60.6%±11.7 52.5%
FH down the line 16% 56.0%±12.3 53.3%
FH through the middle 11% 35.4%±12.9 45.5%
BH down the line 9% 50.6%±14.1 51.0%

Serve under pressure

Pressure predictability index ±0 How much less varied Kimberly Birrell's first-serve direction gets on break points. Positive means easier to read. Based on 111 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 44% 27% ▼ 55% / 66%
Body 30% 31% 59% / 57%
T 26% 42% ▲ 67% / 68%

405 normal · 26 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 34% 24% ▼ 62% / 66%
Body 23% 31% 53% / 56%
T 42% 46% 60% / 64%

318 normal · 85 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
Wide43% 49.8%±5.6 n=187 43%
Body30% 53.0%±6.5 n=128 15% ▼
T27% 53.4%±6.8 n=116 42% ▲

Consistent with an optimal mix (p = 0.68).
Optimal mix: +0.4 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide32% 45.5%±6.5 n=129 32%
Body25% 50.8%±7.2 n=100 10% ▼
T43% 53.3%±5.7 n=174 58% ▲

Consistent with an optimal mix (p = 0.22).
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.40 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: −8.4±5.1 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. (261 repeats, 545 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 40 42% −2.2±9.7
1stAd courtT 94 22% −13.2±6.1
1stAd courtWide 96 22% −12.0±6.1
1stDeuce courtBody 50 40% −2.9±9.0
1stDeuce courtT 89 25% −7.2±6.5
1stDeuce courtWide 102 26% −8.1±6.3
2ndAd courtBody 64 46% −8.8±8.5
2ndAd courtT 26 47% −7.7±11.0
2ndAd courtWide 61 51% −2.9±8.6
2ndDeuce courtBody 82 52% −2.4±7.8
2ndDeuce courtT 40 64% +8.0±9.4
2ndDeuce courtWide 51 50% −4.2±9.1

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 3.1% · won 61% · +4.3±11.3 vs own baseline
  2. T serve (ad court) → FH crosscourt used 4.0% · won 59% · +3.2±10.7 vs own baseline
  3. Body serve (deuce court) → FH down the line used 3.5% · won 55% · −0.9±11.2 vs own baseline
  4. Wide serve (deuce court) → BH crosscourt used 3.1% · won 53% · −3.6±11.6 vs own baseline
  5. Body serve (ad court) → FH crosscourt used 2.9% · won 52% · −4.5±11.7 vs own baseline

Return

  1. vs body serve (deuce court) → BH through the middle, mid used 5.0% · won 46% · +9.1±11.7 vs own baseline
  2. vs T serve (deuce court) → BH through the middle, mid used 6.5% · won 43% · +5.9±10.9 vs own baseline
  3. vs wide serve (ad court) → BH crosscourt, mid used 5.5% · won 43% · +5.4±11.3 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH down the line used 7.1% · won 53% · +6.4±8.6 vs own baseline
  2. BH crosscourt → FH crosscourt used 5.1% · won 52% · +5.6±9.7 vs own baseline
  3. FH through the middle → FH crosscourt used 4.3% · won 52% · +5.8±10.2 vs own baseline
  4. BH crosscourt → BH crosscourt used 7.3% · won 50% · +4.1±8.5 vs own baseline
  5. FH crosscourt → BH crosscourt used 3.5% · won 50% · +3.5±10.8 vs own baseline

Discovered sequences

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

  1. FH crosscourt → FH crosscourt → FH down the line used 2.0% · won 51% · +5.8±9.7 vs own baseline · +6.7 vs tour on the same sequence Disrupted by Suzan Lamens (2/6), Daria Kasatkina (10/15)
  2. BH crosscourt → BH crosscourt → BH crosscourt used 1.9% · won 50% · +4.4±9.9 vs own baseline · +3.7 vs tour on the same sequence Disrupted by Daria Kasatkina (8/17)
  3. FH crosscourt → FH down the line → BH crosscourt used 0.8% · won 52% · +6.6±12.6 vs own baseline · +11.3 vs tour on the same sequence Disrupted by Daria Kasatkina (6/9)
  4. BH crosscourt → BH through the middle → FH crosscourt used 1.2% · won 49% · +3.4±11.4 vs own baseline · −2.0 vs tour on the same sequence Disrupted by Daria Kasatkina (4/9)
  5. FH through the middle → FH crosscourt → FH crosscourt used 1.2% · won 47% · +1.4±11.4 vs own baseline · +1.4 vs tour on the same sequence Disrupted by Sorana Cirstea (1/6)
  6. BH through the middle → BH through the middle → FH crosscourt used 0.7% · won 47% · +1.8±12.8 vs own baseline · +1.1 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 · rally+0.7280
FH to their forehand · rally±0.0334
BH to the middle · rally−0.3192
Body 1st serve · deuce court−0.6128
BH to their forehand · rally−0.7130

Most exposed to

T 1st serve · deuce court−3.0163
FH to the middle · return−2.5198
BH to the middle · return−2.4200
FH to their forehand · rally−2.2310
FH to their backhand · rally−2.1204

Active players who are best at the shot in the top weakness: Serena Williams, Madison Keys, Ashlyn Krueger, Karolina Pliskova, Victoria Mboko

Tactical fingerprint

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

Deep returns40%
T serves · ad43%
Through the middle31%
Wide serves · deuce43%
Avg rally length4.1
Unforced errors / shot10.5%
1st serve in62%
Serve & volley0%
FH down the line28%
BH down the line19%
Forehand share52%
Point-ending shots21.6%
Points at net5%
Backhand slice4%
Run-around forehands2%
Chipped returns3%
Wide serves · ad32%
Drop shots / shot0.2%
T serves · deuce27%

Plays most like

  1. Iva Jovic 2024–2026 plan v
  2. Lin Zhu 2016–2025 plan v
  3. Varvara Gracheva 2021–2026 plan v
  4. Anastasia Potapova 2017–2026 plan v
  5. Anna Blinkova 2019–2026 plan v
  6. Eva Lys 2022–2026 plan v
  7. Emma Navarro 2019–2026 plan v
  8. Emma Raducanu 2018–2026 plan v

Closest from another era

  1. Elena Dementieva 1999–2010
  2. Anastasia Myskina 2002–2006
  3. Jennifer Capriati 1990–2002

Charted matches