RallyIQ

WTA · Right-handed · 42 charted matches · 2013–2025

Caroline Garcia

Archetype: First-strike aggressor · Short-point player

Against an average opponent

Serve points won 60.4% ±2.8 raw 57.9% · tour 56.3% · 2,737 points
Return points won 43.4% ±2.8 raw 38.9% · tour 43.7% · 2,637 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 +0.13 ±0.06 better than 76% of WTA · raw +0.12
Shot selection +0.74 ±0.11 better than 98% of WTA · raw +0.72
Execution −1.52 ±0.45 better than 10% of WTA · raw −1.63
Tactical adaptability +0.05 first serves toward what's working, set to set · 42 matches
Adaptation speed +0.10 same, every two to three service games · per 100 first serves
Points left on the table 2.53 per 100 shots vs best direction · lower than 61% 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 11,798 shots.

Shot expected value

The share of points Caroline Garcia 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 · 610 shots

OptionUsedWin %Tour
FH crosscourt 31% 45.8%±5.6 52.7%
FH through the middle 19% 37.0%±6.9 45.8%
BH crosscourt 13% 48.1%±8.3 50.9%
BH through the middle 12% 37.5%±8.2 46.2%
FH down the line 12% 49.9%±8.5 52.2%
BH down the line 4% 50.0%±12.7 50.0%
FH crosscourt + approach 3% 65.7%±12.2 69.7%
BH crosscourt + approach 2% 63.9%±13.4 66.7%

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

position worth 45% to the average player · 543 shots

OptionUsedWin %Tour
BH crosscourt 48% 46.1%±4.9 47.6%
BH through the middle 24% 34.6%±6.3 43.3%
BH down the line 12% 37.2%±8.5 46.8%
BH slice through the middle 5% 28.6%±11.1 34.4%
BH slice crosscourt 3% 28.8%±12.6 40.4%
FH inside-out 2% 53.0%±14.3 52.5%
BH slice down the line 2% 26.9%±13.1 31.7%
BH crosscourt + approach 2% 67.0%±13.9 68.9%

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

position worth 43% to the average player · 451 shots

OptionUsedWin %Tour
FH crosscourt 41% 41.6%±5.7 46.7%
FH through the middle 26% 41.1%±6.9 41.3%
FH down the line 23% 42.6%±7.4 44.9%
FH slice through the middle 5% 21.6%±10.6 29.2%
FH slice crosscourt 3% 26.2%±12.8 31.9%

Serve +1: mid-depth return to your middle

position worth 51% to the average player · 447 shots

OptionUsedWin %Tour
FH crosscourt 30% 51.2%±6.7 54.0%
FH through the middle 18% 38.5%±8.0 45.5%
BH through the middle 16% 43.6%±8.6 46.3%
BH crosscourt 14% 54.3%±9.0 52.5%
FH down the line 12% 57.6%±9.4 53.3%
FH crosscourt + approach 4% 70.4%±12.5 71.8%
BH down the line 3% 56.4%±14.0 51.0%
BH crosscourt + approach 3% 67.3%±13.6 72.6%

Serve under pressure

Pressure predictability index +4 How much less varied Caroline Garcia's first-serve direction gets on break points. Positive means easier to read. Based on 282 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 35% 29% 70% / 66%
Body 16% 13% 55% / 57%
T 48% 58% ▲ 67% / 68%

1,361 normal · 62 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 39% 42% 75% / 66%
Body 12% 10% 59% / 56%
T 49% 48% 64% / 64%

1,087 normal · 220 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% 61.6%±3.5 n=498 50% ▲
Body16% 54.7%±5.1 n=229 1% ▼
T49% 59.7%±3.0 n=696 49%

Consistent with an optimal mix (p = 0.13).
Optimal mix: +1.1 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide40% 58.7%±3.5 n=519 55% ▲
Body12% 59.2%±6.0 n=152 11%
T49% 53.5%±3.2 n=636 34% ▼

Consistent with an optimal mix (p = 0.11).
Optimal mix: +0.6 per 100 first serves.

Exploitability 0.85 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: −2.4±2.7 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. (847 repeats, 1,799 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 243 44% +0.1±4.9
1stAd courtT 293 31% −4.7±4.2
1stAd courtWide 264 31% −3.7±4.4
1stDeuce courtBody 270 42% −1.0±4.7
1stDeuce courtT 286 26% −6.6±4.0
1stDeuce courtWide 360 30% −4.2±3.8
2ndAd courtBody 224 49% −6.4±5.2
2ndAd courtT 75 53% −2.2±8.0
2ndAd courtWide 166 53% −1.0±5.9
2ndDeuce courtBody 235 51% −3.8±5.1
2ndDeuce courtT 123 50% −6.5±6.6
2ndDeuce courtWide 92 53% −1.2±7.4

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 2.0% · won 61% · −0.6±9.1 vs own baseline
  2. T serve (ad court) → BH crosscourt used 2.4% · won 56% · −5.3±8.6 vs own baseline
  3. T serve (deuce court) → BH crosscourt used 2.1% · won 54% · −7.1±9.1 vs own baseline
  4. T serve (deuce court) → FH crosscourt used 4.9% · won 55% · −6.3±6.6 vs own baseline
  5. Body serve (deuce court) → FH crosscourt used 3.1% · won 53% · −8.1±8.0 vs own baseline

Return

  1. vs body serve (deuce court) → BH through the middle, deep used 2.2% · won 55% · +16.3±9.6 vs own baseline
  2. vs wide serve (deuce court) → FH crosscourt, mid used 3.1% · won 52% · +13.0±8.6 vs own baseline
  3. vs wide serve (deuce court) → FH through the middle, deep used 3.4% · won 49% · +10.3±8.3 vs own baseline
  4. vs wide serve (ad court) → BH through the middle, deep used 2.6% · won 50% · +10.8±9.1 vs own baseline
  5. vs T serve (ad court) → FH through the middle, deep used 2.2% · won 50% · +11.4±9.7 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 2.0% · won 52% · +8.7±11.2 vs own baseline
  2. BH crosscourt → FH down the line used 2.7% · won 49% · +6.1±10.3 vs own baseline
  3. FH crosscourt → BH crosscourt used 4.7% · won 47% · +4.0±8.7 vs own baseline
  4. FH down the line → BH crosscourt used 2.7% · won 47% · +4.5±10.3 vs own baseline
  5. BH down the line → FH crosscourt used 1.7% · won 47% · +3.9±11.5 vs own baseline

Discovered sequences

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

  1. T serve → BH through the middle return, mid → FH crosscourt used 0.7% · won 53% · +8.1±10.7 vs own baseline · +5.4 vs tour on the same sequence
  2. BH crosscourt → BH through the middle → FH down the line used 0.4% · won 54% · +8.8±12.0 vs own baseline · +10.3 vs tour on the same sequence
  3. FH crosscourt → FH down the line → BH crosscourt used 0.9% · won 51% · +6.2±9.9 vs own baseline · +4.7 vs tour on the same sequence Disrupted by Garbine Muguruza (2/7), Coco Gauff (2/6)
  4. T serve → FH down the line return, mid → BH crosscourt used 0.4% · won 54% · +9.1±12.5 vs own baseline · +18.1 vs tour on the same sequence Disrupted by Iga Swiatek (4/6)
  5. Wide serve → BH through the middle return, mid → FH crosscourt used 0.4% · won 53% · +7.9±12.4 vs own baseline · +5.5 vs tour on the same sequence
  6. FH down the line → BH crosscourt → BH crosscourt used 0.9% · won 50% · +4.7±9.7 vs own baseline · +3.8 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

T 2nd serve · deuce court+2.6214
Wide 1st serve · deuce court+2.4498
Body 2nd serve · ad court+1.8178
Body 2nd serve · deuce court+1.4244
FH to their backhand · serve +1+1.0294

Most exposed to

BH to their backhand · rally−3.1397
FH to their backhand · serve +1−2.9235
BH to their forehand · rally−2.7182
Wide 1st serve · deuce court−2.0524
FH to their forehand · return +1−1.4196

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +2.84, Caroline Wozniacki +2.80, Daria Kasatkina +2.16, Angelique Kerber +2.05, Sara Errani +1.99

Favourable matchups

Sara Errani +0.50, Angelique Kerber +0.01, Marie Bouzkova −0.14, Elina Avanesyan −0.17, Katie Volynets −0.28

Active players who are best at the shot in the top weakness: Maja Chwalinska, Sara Sorribes Tormo, Yulia Putintseva, Elsa Jacquemot, Caroline Wozniacki

Tactical fingerprint

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

Point-ending shots33.3%
T serves · deuce49%
Unforced errors / shot13.9%
T serves · ad49%
Deep returns38%
Points at net11%
Forehand share57%
Run-around forehands10%
Serve & volley1%
Wide serves · ad40%
Through the middle28%
Chipped returns7%
Backhand slice8%
Drop shots / shot1.0%
1st serve in60%
Wide serves · deuce35%
FH down the line24%
BH down the line14%
Avg rally length3.2

Plays most like

  1. Arianne Hartono 2021–2025 plan v
  2. Coco Vandeweghe 2014–2018 plan v
  3. Lulu Sun 2022–2025 plan v
  4. Elena Rybakina 2019–2026 plan v
  5. Barbora Krejcikova 2017–2026 plan v
  6. Veronika Kudermetova 2018–2025 plan v
  7. Rebecca Marino 2018–2024 plan v
  8. Petra Kvitova 2010–2025 plan v

Closest from another era

  1. Lindsay Davenport 1995–2006
  2. Monica Seles 1990–2003
  3. Anastasia Myskina 2002–2006

Charted matches