RallyIQ

WTA · Right-handed · 12 charted matches · 2016–2025

Lin Zhu

Archetype: Rarely serves the T · Patient builder

Against an average opponent

Serve points won 55.3% ±3.4 raw 51.4% · tour 56.3% · 918 points
Return points won 42.4% ±3.5 raw 38.8% · 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 −0.19 ±0.13 better than 18% of WTA · raw −0.20
Shot selection +0.09 ±0.16 better than 53% of WTA · raw +0.09
Execution −0.19 ±0.84 better than 50% of WTA · raw −0.22
Tactical adaptability −0.08 first serves toward what's working, set to set · 12 matches
Adaptation speed −0.10 same, every two to three service games · per 100 first serves
Points left on the table 2.64 per 100 shots vs best direction · lower than 45% 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 4,850 shots.

Shot expected value

The share of points Lin Zhu 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 · 325 shots

OptionUsedWin %Tour
BH crosscourt 41% 42.5%±6.6 47.6%
BH through the middle 32% 42.5%±7.3 43.3%
BH down the line 14% 43.6%±10.1 46.8%
BH slice through the middle 6% 30.5%±12.1 34.4%
BH slice crosscourt 3% 30.3%±13.8 40.4%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 319 shots

OptionUsedWin %Tour
FH crosscourt 24% 54.3%±8.4 52.7%
FH down the line 23% 48.3%±8.5 52.2%
FH through the middle 19% 50.8%±9.1 45.8%
BH through the middle 15% 46.7%±9.9 46.2%
BH crosscourt 13% 52.8%±10.5 50.9%
BH down the line 6% 48.7%±13.2 50.0%

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

position worth 43% to the average player · 288 shots

OptionUsedWin %Tour
FH crosscourt 40% 41.7%±7.0 46.7%
FH through the middle 33% 34.1%±7.3 41.3%
FH down the line 22% 39.3%±8.8 44.9%

Long rally, 9+: drive to your backhand side

position worth 44% to the average player · 168 shots

OptionUsedWin %Tour
BH crosscourt 43% 42.6%±8.4 47.9%
BH through the middle 26% 45.3%±10.3 42.7%
BH down the line 15% 44.2%±12.0 46.7%
BH slice crosscourt 7% 28.2%±13.3 38.7%

Serve under pressure

Pressure predictability index +1 How much less varied Lin Zhu's first-serve direction gets on break points. Positive means easier to read. Based on 131 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 50% 50% 62% / 66%
Body 23% 32% ▲ 64% / 57%
T 27% 18% ▼ 57% / 68%

444 normal · 28 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 34% 33% 56% / 66%
Body 25% 24% 55% / 56%
T 41% 43% 61% / 64%

343 normal · 103 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
Wide50% 54.5%±5.0 n=238 61% ▲
Body23% 60.5%±6.8 n=109 28% ▲
T26% 47.4%±6.6 n=125 11% ▼

Off equilibrium (p = 0.033): serve body more. Gap 6.5 points per 100 first serves.
Optimal mix: +0.2 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide34% 41.5%±6.0 n=150 19% ▼
Body25% 51.7%±6.9 n=112 25%
T41% 52.7%±5.6 n=184 56% ▲

Off equilibrium (p = 0.028): serve T more. Gap 4.1 points per 100 first serves.
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.31 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: −0.3±6.7 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. (273 repeats, 621 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 70 40% −3.7±8.1
1stAd courtT 80 36% +0.5±7.5
1stAd courtWide 96 29% −5.6±6.6
1stDeuce courtBody 64 41% −1.3±8.4
1stDeuce courtT 78 27% −5.6±7.0
1stDeuce courtWide 139 26% −8.5±5.5
2ndAd courtBody 69 62% +7.1±8.0
2ndAd courtT 23 54% −1.2±11.3
2ndAd courtWide 43 51% −2.8±9.6
2ndDeuce courtBody 89 54% −0.4±7.5
2ndDeuce courtT 26 51% −4.6±11.0
2ndDeuce courtWide 24 54% +0.2±11.2

Signature patterns

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

Serve → +1

  1. Body serve (deuce court) → FH through the middle used 5.0% · won 57% · +2.7±9.7 vs own baseline
  2. Wide serve (deuce court) → FH down the line used 3.9% · won 57% · +2.9±10.5 vs own baseline
  3. Body serve (deuce court) → FH crosscourt used 2.6% · won 54% · +0.4±11.7 vs own baseline
  4. Wide serve (deuce court) → FH through the middle used 4.1% · won 52% · −2.1±10.4 vs own baseline
  5. Body serve (ad court) → BH through the middle used 4.9% · won 52% · −2.3±9.9 vs own baseline

Return

  1. vs wide serve (deuce court) → FH through the middle, deep used 6.0% · won 50% · +5.3±11.1 vs own baseline
  2. vs body serve (ad court) → BH crosscourt, mid used 5.0% · won 48% · +3.3±11.6 vs own baseline
  3. vs T serve (ad court) → FH through the middle, deep used 5.0% · won 48% · +3.3±11.6 vs own baseline
  4. vs wide serve (deuce court) → FH through the middle, mid used 5.0% · won 46% · +1.4±11.6 vs own baseline
  5. vs T serve (deuce court) → BH through the middle, mid used 5.3% · won 41% · −3.3±11.3 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH down the line used 5.5% · won 53% · +9.2±9.1 vs own baseline
  2. BH through the middle → FH crosscourt used 5.1% · won 49% · +5.3±9.3 vs own baseline
  3. FH crosscourt → BH crosscourt used 4.4% · won 49% · +5.2±9.8 vs own baseline
  4. BH crosscourt → FH through the middle used 3.1% · won 48% · +4.9±10.8 vs own baseline
  5. FH through the middle → FH crosscourt used 2.7% · won 48% · +4.8±11.2 vs own baseline

Discovered sequences

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

  1. BH through the middle → FH crosscourt → FH crosscourt used 1.1% · won 50% · +7.7±11.1 vs own baseline · +12.1 vs tour on the same sequence Disrupted by Victoria Azarenka (4/6)
  2. FH crosscourt → FH crosscourt → FH down the line used 1.2% · won 48% · +5.0±11.0 vs own baseline · +3.9 vs tour on the same sequence Disrupted by Lesia Tsurenko (3/7)
  3. BH through the middle → FH through the middle → FH crosscourt used 0.8% · won 48% · +5.6±12.3 vs own baseline · +6.0 vs tour on the same sequence
  4. FH crosscourt → FH down the line → BH crosscourt used 0.8% · won 47% · +4.5±12.1 vs own baseline · +2.6 vs tour on the same sequence
  5. BH crosscourt → BH through the middle → FH down the line used 0.8% · won 47% · +4.5±12.1 vs own baseline · −1.0 vs tour on the same sequence Disrupted by Lesia Tsurenko (2/7)
  6. BH down the line → FH crosscourt → FH crosscourt used 0.9% · won 46% · +3.7±11.7 vs own baseline · +2.1 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

FH to the middle · return+3.4172
BH to the middle · rally+2.4226
FH to the middle · serve +1+1.9130
BH to the middle · serve +1+1.6156
FH to the middle · rally+0.6234

Most exposed to

FH to their forehand · rally−4.1312
BH to their backhand · return−2.6152
BH to their backhand · rally−2.2308
Wide 1st serve · deuce court−1.7205
BH to their forehand · rally−1.6134

Active players who are best at the shot in the top weakness: Linda Fruhvirtova, Maja Chwalinska, Sara Sorribes Tormo, Linda Klimovicova, Nadia Podoroska

Tactical fingerprint

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

Through the middle36%
Deep returns39%
Wide serves · deuce50%
Avg rally length4.5
1st serve in65%
T serves · ad41%
FH down the line29%
Unforced errors / shot10.3%
Run-around forehands6%
Serve & volley0%
BH down the line19%
Drop shots / shot1.2%
Chipped returns7%
Backhand slice9%
Points at net5%
Point-ending shots20.8%
Forehand share51%
Wide serves · ad34%
T serves · deuce26%

Plays most like

  1. Kimberly Birrell 2016–2026 plan v
  2. Emma Raducanu 2018–2026 plan v
  3. Marie Bouzkova 2018–2026 plan v
  4. Emma Navarro 2019–2026 plan v
  5. Iva Jovic 2024–2026 plan v
  6. R – plan v
  7. Elena Dementieva 1999–2010 plan v
  8. Sloane Stephens 2013–2026 plan v

Closest from another era

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

Charted matches