RallyIQ

WTA · Right-handed · 48 charted matches · 2015–2026

Paula Badosa

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

Against an average opponent

Serve points won 59.8% ±2.7 raw 58.6% · tour 56.3% · 3,557 points
Return points won 47.6% ±2.8 raw 44.2% · tour 43.7% · 3,535 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 −0.24 ±0.05 better than 13% of WTA · raw −0.24
Shot selection +0.29 ±0.09 better than 77% of WTA · raw +0.29
Execution +0.75 ±0.35 better than 86% of WTA · raw +0.73
Tactical adaptability +0.02 first serves toward what's working, set to set · 48 matches
Adaptation speed −0.04 same, every two to three service games · per 100 first serves
Points left on the table 2.83 per 100 shots vs best direction · lower than 22% 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 18,660 shots.

Shot expected value

The share of points Paula Badosa 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 backhand side

position worth 45% to the average player · 1,267 shots

OptionUsedWin %Tour
BH through the middle 37% 43.0%±3.7 43.3%
BH crosscourt 35% 49.8%±3.8 47.6%
BH down the line 14% 46.7%±5.8 46.8%
BH slice through the middle 4% 35.8%±9.1 34.4%
FH inside-out 2% 61.0%±11.3 52.5%
BH slice crosscourt 2% 37.4%±12.1 40.4%
BH slice down the line 2% 28.4%±11.7 31.7%
BH drop shot crosscourt 1% 50.0%±14.3 47.5%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 1,082 shots

OptionUsedWin %Tour
FH crosscourt 22% 58.5%±5.0 52.7%
FH down the line 21% 53.7%±5.2 52.2%
FH through the middle 21% 48.8%±5.2 45.8%
BH through the middle 16% 47.8%±5.9 46.2%
BH crosscourt 12% 51.8%±6.6 50.9%
BH down the line 7% 54.4%±8.5 50.0%

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

position worth 43% to the average player · 916 shots

OptionUsedWin %Tour
FH through the middle 35% 42.4%±4.4 41.3%
FH crosscourt 34% 46.4%±4.5 46.7%
FH down the line 23% 41.7%±5.3 44.9%
FH slice through the middle 3% 40.9%±11.3 29.2%
FH slice crosscourt 2% 30.8%±12.5 31.9%
FH lob through the middle 1% 30.9%±13.4 29.4%

Return +1: drive to your backhand side

position worth 44% to the average player · 634 shots

OptionUsedWin %Tour
BH through the middle 43% 51.1%±4.8 43.0%
BH crosscourt 34% 43.4%±5.3 47.8%
BH down the line 12% 37.8%±8.1 46.2%
BH slice through the middle 6% 41.2%±10.9 33.2%
BH slice crosscourt 2% 44.9%±14.7 39.6%

Serve under pressure

Pressure predictability index ±0 How much less varied Paula Badosa's first-serve direction gets on break points. Positive means easier to read. Based on 372 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 48% 41% 67% / 66%
Body 19% 20% 62% / 57%
T 33% 39% 73% / 68%

1,758 normal · 90 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 26% 28% 67% / 66%
Body 16% 15% 53% / 56%
T 58% 58% 72% / 64%

1,407 normal · 282 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
Wide47% 58.1%±2.7 n=877 48%
Body19% 57.6%±4.1 n=358 4% ▼
T33% 60.4%±3.2 n=613 48% ▲

Consistent with an optimal mix (p = 0.54).
Optimal mix: +0.4 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide26% 59.1%±3.7 n=440 26%
Body16% 48.4%±4.8 n=267 1% ▼
T58% 60.8%±2.5 n=982 73% ▲

Off equilibrium (p < 0.001): serve T more. Gap 2.4 points per 100 first serves.
Optimal mix: +1.3 per 100 first serves.

Exploitability 0.84 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: +3.6±3.5 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. (1,262 repeats, 2,179 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 191 45% +1.0±5.5
1stAd courtT 380 38% +2.9±4.0
1stAd courtWide 456 38% +3.7±3.6
1stDeuce courtBody 267 46% +3.1±4.8
1stDeuce courtT 413 35% +3.2±3.7
1stDeuce courtWide 452 33% −0.8±3.5
2ndAd courtBody 253 55% −0.1±4.9
2ndAd courtT 109 53% −2.2±7.0
2ndAd courtWide 295 54% +0.3±4.5
2ndDeuce courtBody 295 52% −2.3±4.6
2ndDeuce courtT 216 57% +0.8±5.2
2ndDeuce courtWide 184 52% −1.4±5.6

Signature patterns

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

Serve → +1

  1. T serve (ad court) → FH down the line used 3.2% · won 69% · +4.6±6.6 vs own baseline
  2. T serve (ad court) → FH crosscourt used 2.8% · won 65% · +0.8±7.2 vs own baseline
  3. Body serve (deuce court) → FH down the line used 2.7% · won 62% · −1.9±7.4 vs own baseline
  4. Wide serve (ad court) → FH crosscourt used 2.4% · won 61% · −2.9±7.8 vs own baseline
  5. T serve (deuce court) → FH crosscourt used 2.3% · won 60% · −3.8±8.0 vs own baseline

Return

  1. vs T serve (deuce court) → BH through the middle, deep used 2.5% · won 55% · +9.1±8.1 vs own baseline
  2. vs wide serve (ad court) → BH through the middle, deep used 3.0% · won 53% · +7.6±7.5 vs own baseline
  3. vs wide serve (deuce court) → FH through the middle, deep used 3.7% · won 52% · +6.7±7.0 vs own baseline
  4. vs body serve (deuce court) → BH through the middle, deep used 2.1% · won 52% · +6.8±8.7 vs own baseline
  5. vs wide serve (ad court) → BH crosscourt, short used 2.2% · won 52% · +6.2±8.5 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 2.3% · won 62% · +13.1±7.2 vs own baseline
  2. FH crosscourt → FH down the line used 4.8% · won 54% · +5.1±5.4 vs own baseline
  3. FH through the middle → FH crosscourt used 3.5% · won 54% · +4.9±6.3 vs own baseline
  4. BH crosscourt → FH crosscourt used 3.3% · won 52% · +3.2±6.5 vs own baseline
  5. FH down the line → FH through the middle used 1.3% · won 54% · +5.0±9.2 vs own baseline

Discovered sequences

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

  1. FH down the line → BH through the middle → FH crosscourt used 0.5% · won 59% · +9.9±9.8 vs own baseline · +8.1 vs tour on the same sequence
  2. BH crosscourt → BH through the middle → FH crosscourt used 0.7% · won 56% · +6.5±8.6 vs own baseline · +4.6 vs tour on the same sequence Disrupted by Kaja Juvan (3/8), Marta Kostyuk (5/6)
  3. Wide serve → BH through the middle return, mid → FH crosscourt used 0.3% · won 60% · +10.1±11.3 vs own baseline · +11.5 vs tour on the same sequence
  4. BH crosscourt → BH slice through the middle → FH crosscourt used 0.3% · won 60% · +10.1±11.3 vs own baseline · +9.2 vs tour on the same sequence
  5. FH through the middle → BH through the middle → BH through the middle used 0.3% · won 58% · +8.6±11.0 vs own baseline · +19.1 vs tour on the same sequence Disrupted by Rebecca Marino (5/6)
  6. T serve → FH through the middle return, mid → FH down the line used 0.3% · won 59% · +9.3±11.5 vs own baseline · +16.1 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 · return+3.8457
FH to their forehand · return +1+3.1266
BH to their forehand · return+3.0259
FH to their forehand · serve +1+2.6457
FH to their backhand · serve +1+2.4473

Most exposed to

T 2nd serve · deuce court−1.8216
Body 2nd serve · deuce court−1.8295
BH to their forehand · rally−1.8495
FH to their backhand · serve +1−1.7519
FH to the middle · return−1.5699

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +2.97, Caroline Wozniacki +2.59, Angelique Kerber +2.24, Daria Kasatkina +2.04, Maja Chwalinska +1.94

Favourable matchups

Sara Errani +3.16, Angelique Kerber +2.86, Marie Bouzkova +2.79, Elina Avanesyan +2.49, Katie Volynets +2.39

Active players who are best at the shot in the top weakness: Madison Keys, Ons Jabeur, Iva Jovic, Caroline Wozniacki, Caroline Garcia

Tactical fingerprint

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

T serves · ad58%
Through the middle36%
Wide serves · deuce47%
FH down the line31%
Run-around forehands9%
Avg rally length4.2
Forehand share54%
BH down the line20%
Serve & volley0%
1st serve in62%
Chipped returns8%
Backhand slice8%
T serves · deuce33%
Deep returns30%
Point-ending shots20.9%
Points at net4%
Drop shots / shot0.7%
Unforced errors / shot7.8%
Wide serves · ad26%

Plays most like

  1. Anna Bondar 2017–2026 plan v
  2. Coco Gauff 2019–2026 plan v
  3. Qiang Wang 2012–2024 plan v
  4. Carla Suarez Navarro 2009–2021 plan v
  5. Lin Zhu 2016–2025 plan v
  6. Jennifer Brady 2016–2023 plan v
  7. Louisa Chirico 2015–2017 plan v
  8. Kimberly Birrell 2016–2026 plan v

Closest from another era

  1. Elena Dementieva 1999–2010
  2. Anastasia Myskina 2002–2006
  3. Justine Henin 1999–2010

Charted matches