RallyIQ

WTA · Right-handed · 13 charted matches · 2019–2025

Yafan Wang

Archetype: Rarely serves the T · Patient builder

Against an average opponent

Serve points won 55.7% ±3.6 raw 53.0% · tour 56.3% · 927 points
Return points won 42.6% ±3.6 raw 39.1% · tour 43.7% · 886 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 −0.09 ±0.14 better than 37% of WTA · raw −0.09
Shot selection +0.23 ±0.17 better than 71% of WTA · raw +0.23
Execution −0.19 ±0.49 better than 50% of WTA · raw −0.21
Tactical adaptability −0.05 first serves toward what's working, set to set · 13 matches
Adaptation speed −0.03 same, every two to three service games · per 100 first serves
Points left on the table 2.70 per 100 shots vs best direction · lower than 33% 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 5,132 shots.

Shot expected value

The share of points Yafan Wang 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 · 331 shots

OptionUsedWin %Tour
BH crosscourt 40% 46.0%±6.7 47.6%
BH through the middle 34% 36.1%±6.9 43.3%
BH down the line 13% 47.3%±10.4 46.8%
BH slice through the middle 5% 41.3%±13.5 34.4%
BH slice crosscourt 4% 32.6%±13.2 40.4%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 283 shots

OptionUsedWin %Tour
FH crosscourt 33% 46.0%±7.7 52.7%
FH through the middle 21% 48.3%±9.2 45.8%
FH down the line 20% 51.2%±9.4 52.2%
BH crosscourt 11% 48.4%±11.4 50.9%
BH through the middle 11% 40.5%±11.4 46.2%

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

position worth 43% to the average player · 251 shots

OptionUsedWin %Tour
FH crosscourt 41% 51.1%±7.5 46.7%
FH through the middle 30% 40.5%±8.4 41.3%
FH down the line 26% 39.0%±8.9 44.9%

Long rally, 9+: drive to your backhand side

position worth 44% to the average player · 181 shots

OptionUsedWin %Tour
BH crosscourt 39% 55.1%±8.6 47.9%
BH through the middle 25% 31.6%±9.5 42.7%
BH down the line 16% 45.6%±11.7 46.7%
BH slice crosscourt 9% 34.4%±12.8 38.7%
BH slice through the middle 8% 30.5%±12.8 33.4%

Serve under pressure

Pressure predictability index +4 How much less varied Yafan Wang's first-serve direction gets on break points. Positive means easier to read. Based on 127 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 54% 59% 60% / 66%
Body 21% 19% 64% / 57%
T 25% 22% 68% / 68%

450 normal · 27 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 42% 49% 63% / 66%
Body 22% 17% 47% / 56%
T 36% 34% 63% / 64%

350 normal · 100 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
Wide54% 54.1%±4.8 n=259 55%
Body21% 58.8%±7.2 n=98 5% ▼
T25% 53.3%±6.7 n=120 40% ▲

Consistent with an optimal mix (p = 0.51).
Optimal mix: +0.2 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide44% 51.4%±5.5 n=197 43%
Body21% 42.9%±7.3 n=93 6% ▼
T36% 55.5%±5.9 n=160 51% ▲

Off equilibrium (p = 0.042): serve T more. Gap 4.4 points per 100 first serves.
Optimal mix: +1.0 per 100 first serves.

Exploitability 0.59 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: +0.7±5.5 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. (296 repeats, 605 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 52 44% +0.2±9.0
1stAd courtT 90 32% −3.3±7.0
1stAd courtWide 121 33% −1.1±6.3
1stDeuce courtBody 63 38% −4.1±8.3
1stDeuce courtT 100 23% −9.3±6.1
1stDeuce courtWide 132 32% −2.4±6.0
2ndAd courtBody 71 54% −1.1±8.2
2ndAd courtT 17 52% −2.9±12.0
2ndAd courtWide 74 50% −3.5±8.1
2ndDeuce courtBody 83 54% −0.2±7.7
2ndDeuce courtT 36 51% −4.8±10.1
2ndDeuce courtWide 47 56% +2.2±9.3

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 4.4% · won 56% · +0.4±10.5 vs own baseline
  2. Body serve (deuce court) → BH through the middle used 3.1% · won 54% · −1.5±11.5 vs own baseline
  3. Body serve (deuce court) → FH crosscourt used 3.2% · won 53% · −2.5±11.4 vs own baseline
  4. Body serve (deuce court) → BH crosscourt used 3.2% · won 53% · −2.5±11.4 vs own baseline
  5. Body serve (ad court) → FH crosscourt used 4.1% · won 53% · −2.9±10.8 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, deep used 5.2% · won 52% · +6.8±11.4 vs own baseline
  2. vs wide serve (ad court) → BH crosscourt, short used 5.4% · won 49% · +3.9±11.2 vs own baseline
  3. vs wide serve (ad court) → BH through the middle, deep used 4.7% · won 48% · +2.9±11.6 vs own baseline
  4. vs wide serve (ad court) → BH crosscourt, mid used 4.5% · won 47% · +1.9±11.7 vs own baseline
  5. vs wide serve (ad court) → BH through the middle, mid used 8.3% · won 46% · +0.4±9.9 vs own baseline

Rally, consecutive own shots

  1. BH down the line → FH down the line used 2.2% · won 59% · +10.9±11.5 vs own baseline
  2. FH through the middle → FH crosscourt used 6.1% · won 54% · +6.2±8.8 vs own baseline
  3. BH crosscourt → FH down the line used 2.6% · won 55% · +7.6±11.3 vs own baseline
  4. BH crosscourt → BH crosscourt used 4.0% · won 52% · +4.3±10.1 vs own baseline
  5. FH crosscourt → FH down the line used 7.4% · won 50% · +2.6±8.2 vs own baseline

Discovered sequences

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

  1. FH through the middle → FH crosscourt → FH crosscourt used 1.3% · won 56% · +10.1±10.5 vs own baseline · +16.2 vs tour on the same sequence Disrupted by Sofia Kenin (5/6)
  2. FH crosscourt → FH through the middle → FH down the line used 1.1% · won 52% · +6.1±11.3 vs own baseline · +3.5 vs tour on the same sequence Disrupted by Elina Svitolina (3/7)
  3. FH crosscourt → FH through the middle → FH through the middle used 0.6% · won 54% · +7.9±13.0 vs own baseline · +20.9 vs tour on the same sequence
  4. FH crosscourt → FH crosscourt → FH down the line used 1.8% · won 49% · +3.6±9.5 vs own baseline · +3.3 vs tour on the same sequence Disrupted by Magda Linette (2/6), Elina Svitolina (5/8)
  5. BH crosscourt → BH crosscourt → BH crosscourt used 1.2% · won 50% · +4.2±10.9 vs own baseline · +4.5 vs tour on the same sequence Disrupted by Magda Linette (3/6), Qinwen Zheng (3/6)
  6. FH down the line → BH crosscourt → BH down the line used 0.8% · won 50% · +4.2±12.3 vs own baseline · +5.0 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

FH to their forehand · serve +1+3.1146
FH to their backhand · rally+2.9260
FH to the middle · return+1.7163
FH to the middle · rally+1.3218
FH to their forehand · rally+0.2389

Most exposed to

BH to the middle · return−2.2197
BH to their backhand · rally−2.1274
FH to the middle · return−1.8223
FH to their backhand · rally−1.5302
FH to their forehand · serve +1−1.2139

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +3.63, Caroline Wozniacki +3.41, Angelique Kerber +2.82, Daria Kasatkina +2.81, Sara Errani +2.64

Favourable matchups

Sara Errani +2.26, Angelique Kerber +2.06, Marie Bouzkova +1.99, Linda Fruhvirtova +1.63, Elina Avanesyan +1.57

Active players who are best at the shot in the top weakness: Sara Sorribes Tormo, Maja Chwalinska, Daria Saville, Daria Kasatkina, Caroline Wozniacki

Tactical fingerprint

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

Wide serves · deuce54%
Forehand share58%
Avg rally length4.6
Run-around forehands11%
Through the middle31%
Points at net9%
Wide serves · ad44%
Chipped returns11%
FH down the line29%
Serve & volley1%
Backhand slice15%
T serves · ad36%
1st serve in60%
Drop shots / shot0.9%
Deep returns30%
Unforced errors / shot8.8%
Point-ending shots20.0%
BH down the line16%
T serves · deuce25%

Plays most like

  1. Emma Navarro 2019–2026 plan v
  2. Coco Gauff 2019–2026 plan v
  3. Elena Dementieva 1999–2010 plan v
  4. Nao Hibino 2016–2025 plan v
  5. Louisa Chirico 2015–2017 plan v
  6. Emma Raducanu 2018–2026 plan v
  7. Tereza Martincova 2015–2022 plan v
  8. Anastasia Potapova 2017–2026 plan v

Closest from another era

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

Charted matches