RallyIQ

WTA · Right-handed · 49 charted matches · 2022–2026

Qinwen Zheng

Archetype: Runs around the backhand · Forehand-dominant

Against an average opponent

Serve points won 60.1% ±2.6 raw 59.2% · tour 56.3% · 3,387 points
Return points won 46.5% ±2.7 raw 44.5% · tour 43.7% · 3,446 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 +0.01 ±0.05 better than 53% of WTA · raw ±0.00
Shot selection +0.42 ±0.08 better than 91% of WTA · raw +0.40
Execution −0.51 ±0.36 better than 32% of WTA · raw −0.63
Tactical adaptability +0.08 first serves toward what's working, set to set · 48 matches
Adaptation speed +0.11 same, every two to three service games · per 100 first serves
Points left on the table 2.65 per 100 shots vs best direction · lower than 43% 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 15,602 shots.

Shot expected value

The share of points Qinwen Zheng 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 · 935 shots

OptionUsedWin %Tour
BH crosscourt 39% 43.0%±4.2 47.6%
BH through the middle 27% 42.8%±5.0 43.3%
BH down the line 16% 38.7%±6.2 46.8%
BH slice through the middle 5% 26.7%±8.9 34.4%
FH inside-out 4% 44.0%±10.7 52.5%
BH slice crosscourt 3% 36.9%±11.3 40.4%
BH slice down the line 2% 25.2%±11.2 31.7%
FH through the middle 2% 50.0%±13.7 45.1%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 804 shots

OptionUsedWin %Tour
FH down the line 30% 52.3%±5.1 52.2%
FH crosscourt 25% 59.2%±5.5 52.7%
FH through the middle 16% 44.3%±6.7 45.8%
BH through the middle 11% 49.8%±7.9 46.2%
BH crosscourt 9% 46.0%±8.4 50.9%
BH down the line 8% 51.8%±9.0 50.0%

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

position worth 43% to the average player · 737 shots

OptionUsedWin %Tour
FH crosscourt 36% 47.3%±4.9 46.7%
FH down the line 35% 41.2%±4.8 44.9%
FH through the middle 20% 45.4%±6.3 41.3%
FH slice through the middle 4% 30.9%±11.0 29.2%
FH slice down the line 4% 24.7%±10.2 24.3%

Return +1: drive to your middle

position worth 50% to the average player · 556 shots

OptionUsedWin %Tour
FH crosscourt 27% 49.7%±6.3 52.3%
FH down the line 26% 53.7%±6.4 53.0%
FH through the middle 14% 40.1%±8.1 46.5%
BH through the middle 12% 40.5%±8.7 46.2%
BH crosscourt 10% 52.8%±9.3 50.8%
BH down the line 9% 52.9%±9.7 50.6%

Serve under pressure

Pressure predictability index +2 How much less varied Qinwen Zheng's first-serve direction gets on break points. Positive means easier to read. Based on 323 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 47% 46% 73% / 66%
Body 9% 11% 59% / 57%
T 43% 43% 77% / 68%

1,682 normal · 83 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 49% 59% ▲ 74% / 66%
Body 8% 8% 60% / 56%
T 43% 33% ▼ 73% / 64%

1,372 normal · 240 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% 61.0%±2.7 n=835 62% ▲
Body9% 56.5%±5.9 n=163 0% ▼
T43% 59.5%±2.9 n=767 38% ▼

Consistent with an optimal mix (p = 0.42).
Optimal mix: +0.6 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide50% 58.1%±2.8 n=809 43% ▼
Body8% 53.1%±6.5 n=130 0% ▼
T42% 59.9%±3.0 n=673 57% ▲

Consistent with an optimal mix (p = 0.20).
Optimal mix: +0.5 per 100 first serves.

Exploitability 0.55 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: −1.9±2.8 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. (1,158 repeats, 2,121 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 194 45% +0.8±5.5
1stAd courtT 270 34% −1.6±4.5
1stAd courtWide 524 40% +5.1±3.4
1stDeuce courtBody 300 47% +4.3±4.5
1stDeuce courtT 287 35% +2.8±4.4
1stDeuce courtWide 539 36% +1.9±3.3
2ndAd courtBody 270 50% −5.2±4.7
2ndAd courtT 73 55% −0.2±8.1
2ndAd courtWide 321 53% −0.2±4.4
2ndDeuce courtBody 310 56% +1.8±4.4
2ndDeuce courtT 201 56% −0.3±5.4
2ndDeuce courtWide 157 51% −2.9±6.0

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 2.6% · won 58% · −6.1±7.8 vs own baseline
  2. Wide serve (deuce court) → FH down the line used 3.8% · won 59% · −5.3±6.8 vs own baseline
  3. T serve (ad court) → FH crosscourt used 2.0% · won 57% · −7.9±8.6 vs own baseline
  4. Body serve (deuce court) → BH through the middle used 2.0% · won 54% · −10.2±8.6 vs own baseline
  5. Wide serve (deuce court) → FH crosscourt used 2.7% · won 55% · −9.0±7.8 vs own baseline

Return

  1. vs wide serve (ad court) → BH through the middle, deep used 4.1% · won 58% · +13.9±6.6 vs own baseline
  2. vs wide serve (deuce court) → FH through the middle, deep used 3.9% · won 54% · +9.9±6.8 vs own baseline
  3. vs wide serve (ad court) → BH crosscourt, deep used 2.0% · won 57% · +12.4±8.7 vs own baseline
  4. vs wide serve (ad court) → BH crosscourt, mid used 3.1% · won 53% · +9.0±7.5 vs own baseline
  5. vs wide serve (ad court) → BH through the middle, mid used 4.4% · won 51% · +7.3±6.5 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 2.5% · won 60% · +12.3±8.0 vs own baseline
  2. BH direction unknown → FH direction unknown used 2.1% · won 56% · +8.5±8.6 vs own baseline
  3. FH down the line → FH inside-out used 1.5% · won 57% · +9.9±9.6 vs own baseline
  4. FH crosscourt → FH down the line used 7.3% · won 52% · +4.5±5.2 vs own baseline
  5. FH direction unknown → BH direction unknown used 1.7% · won 56% · +8.8±9.3 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Qinwen Zheng 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 0.7% · won 60% · +13.5±9.3 vs own baseline · +10.3 vs tour on the same sequence Disrupted by Donna Vekic (5/6), Bianca Andreescu (9/11)
  2. BH down the line → FH crosscourt → FH crosscourt used 0.5% · won 59% · +12.0±10.1 vs own baseline · +18.8 vs tour on the same sequence
  3. Body serve → BH through the middle return, mid → FH crosscourt used 0.3% · won 60% · +13.4±11.9 vs own baseline · +23.2 vs tour on the same sequence
  4. BH down the line → FH through the middle → FH down the line used 0.2% · won 62% · +14.9±12.6 vs own baseline · +32.7 vs tour on the same sequence
  5. BH through the middle → FH through the middle → FH crosscourt used 0.5% · won 55% · +8.2±10.3 vs own baseline · +11.6 vs tour on the same sequence Disrupted by Iga Swiatek (5/7)
  6. FH crosscourt → BH through the middle → FH down the line used 0.3% · won 57% · +9.7±11.6 vs own baseline · +12.3 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

Body 2nd serve · deuce court+1.4391
FH to the middle · serve +1+1.2287
FH to the middle · return+1.2666
FH to their forehand · serve +1+0.8413
Wide 2nd serve · ad court+0.7321

Most exposed to

Wide 2nd serve · deuce court−2.4151
Wide 2nd serve · ad court−2.0289
Body 2nd serve · ad court−1.9258
FH to their forehand · serve +1−1.2423
BH to their backhand · return +1−1.1221

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +2.25, Caroline Wozniacki +1.81, Daria Kasatkina +1.29, Sara Errani +1.26, Angelique Kerber +1.26

Favourable matchups

Sara Errani +1.51, Angelique Kerber +1.26, Marie Bouzkova +0.94, Elina Avanesyan +0.92, Katie Volynets +0.55

Active players who are best at the shot in the top weakness: Karolina Muchova, Veronika Kudermetova, Jessica Pegula, Elina Svitolina, Bianca Andreescu

Tactical fingerprint

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

FH down the line37%
Forehand share59%
Deep returns39%
BH down the line26%
Wide serves · ad50%
T serves · deuce43%
Wide serves · deuce47%
Run-around forehands13%
Point-ending shots27.5%
T serves · ad42%
Drop shots / shot1.8%
Unforced errors / shot11.0%
Serve & volley0%
Backhand slice10%
Through the middle27%
Points at net5%
Chipped returns5%
Avg rally length3.7
1st serve in52%

Plays most like

  1. Donna Vekic 2014–2026 plan v
  2. Katie Boulter 2018–2025 plan v
  3. Dayana Yastremska 2013–2026 plan v
  4. Ekaterina Alexandrova 2017–2026 plan v
  5. Xin Yu Wang 2019–2026 plan v
  6. Rebecca Sramkova 2016–2026 plan v
  7. Ana Ivanovic 2007–2016 plan v
  8. Sorana Cirstea 2014–2026 plan v

Closest from another era

  1. Daniela Hantuchova 2002–2015
  2. Jelena Dokic 2000–2009
  3. Dinara Safina 2007–2011

Charted matches