RallyIQ

WTA · Right-handed · 24 charted matches · 2015–2024

Su Wei Hsieh

Archetype: First-strike aggressor · Short-point player

Against an average opponent

Serve points won 57.4% ±3.1 raw 55.2% · tour 56.3% · 1,861 points
Return points won 44.3% ±3.2 raw 42.1% · tour 43.7% · 1,735 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 +0.33 ±0.09 better than 96% of WTA · raw +0.33
Shot selection −0.59 ±0.14 better than 9% of WTA · raw −0.59
Execution +0.24 ±0.61 better than 70% of WTA · raw +0.25
Tactical adaptability +0.03 first serves toward what's working, set to set · 23 matches
Adaptation speed −0.06 same, every two to three service games · per 100 first serves
Points left on the table 2.26 per 100 shots vs best direction · lower than 89% 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 9,303 shots.

Shot expected value

The share of points Su Wei Hsieh 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 · 500 shots

OptionUsedWin %Tour
BH crosscourt 46% 52.8%±5.2 47.6%
BH through the middle 24% 47.2%±7.0 43.3%
BH down the line 16% 51.3%±8.1 46.8%
BH slice crosscourt 5% 36.3%±11.5 40.4%
BH slice through the middle 4% 33.1%±11.9 34.4%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 434 shots

OptionUsedWin %Tour
FH crosscourt 23% 58.9%±7.4 52.7%
BH crosscourt 19% 47.8%±8.1 50.9%
FH down the line 13% 49.3%±9.3 52.2%
BH through the middle 12% 54.5%±9.7 46.2%
BH down the line 12% 47.1%±9.8 50.0%
FH through the middle 11% 48.7%±10.1 45.8%
FH drop shot down the line 4% 53.5%±13.7 51.4%
FH slice down the line 3% 51.8%±14.5 47.9%

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

position worth 43% to the average player · 420 shots

OptionUsedWin %Tour
FH crosscourt 46% 52.3%±5.6 46.7%
FH down the line 15% 54.3%±9.1 44.9%
FH through the middle 12% 39.3%±9.5 41.3%
FH slice crosscourt 11% 41.7%±9.8 31.9%
FH slice through the middle 10% 36.4%±10.2 29.2%
FH slice down the line 3% 32.9%±13.5 24.3%

Serve +1: mid-depth return to your middle

position worth 51% to the average player · 343 shots

OptionUsedWin %Tour
FH crosscourt 20% 60.0%±8.6 54.0%
BH crosscourt 20% 52.8%±8.8 52.5%
FH down the line 17% 55.8%±9.1 53.3%
BH through the middle 17% 56.2%±9.3 46.3%
BH down the line 10% 44.8%±11.1 51.0%
FH through the middle 9% 49.2%±11.5 45.5%
FH drop shot down the line 4% 48.3%±14.1 47.1%

Serve under pressure

Pressure predictability index −1 How much less varied Su Wei Hsieh's first-serve direction gets on break points. Positive means easier to read. Based on 231 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 49% 35% ▼ 66% / 66%
Body 20% 25% 54% / 57%
T 32% 40% ▲ 60% / 68%

915 normal · 55 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 44% 47% 66% / 66%
Body 20% 22% 60% / 56%
T 36% 32% 61% / 64%

711 normal · 176 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
Wide48% 59.6%±3.6 n=465 63% ▲
Body20% 52.2%±5.5 n=194 5% ▼
T32% 52.5%±4.4 n=311 32%

Off equilibrium (p = 0.040): serve wide more. Gap 3.7 points per 100 first serves.
Optimal mix: +1.0 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide45% 55.6%±4.0 n=395 59% ▲
Body20% 55.0%±5.7 n=179 5% ▼
T35% 53.7%±4.4 n=313 36%

Consistent with an optimal mix (p = 0.85).
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.68 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: +3.5±4.0 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. (647 repeats, 1,162 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 114 41% −2.8±6.7
1stAd courtT 207 32% −3.2±5.0
1stAd courtWide 209 34% ±0.0±5.1
1stDeuce courtBody 109 51% +8.3±7.0
1stDeuce courtT 221 28% −4.4±4.6
1stDeuce courtWide 260 34% −0.2±4.6
2ndAd courtBody 102 53% −1.6±7.1
2ndAd courtT 60 57% +2.2±8.6
2ndAd courtWide 134 57% +3.2±6.4
2ndDeuce courtBody 139 55% +0.8±6.3
2ndDeuce courtT 109 53% −2.9±7.0
2ndDeuce courtWide 71 56% +1.8±8.1

Signature patterns

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

Serve → +1

  1. Wide serve (deuce court) → FH down the line used 3.7% · won 61% · +2.3±8.6 vs own baseline
  2. Wide serve (deuce court) → FH crosscourt used 3.0% · won 59% · +1.0±9.3 vs own baseline
  3. Wide serve (deuce court) → BH crosscourt used 3.7% · won 59% · +0.4±8.7 vs own baseline
  4. T serve (deuce court) → BH through the middle used 2.0% · won 57% · −0.8±10.5 vs own baseline
  5. Wide serve (deuce court) → FH through the middle used 3.1% · won 55% · −3.1±9.3 vs own baseline

Return

  1. vs wide serve (ad court) → BH through the middle, mid used 4.3% · won 53% · +6.9±9.3 vs own baseline
  2. vs wide serve (deuce court) → FH crosscourt, mid used 4.1% · won 53% · +6.3±9.5 vs own baseline
  3. vs wide serve (ad court) → BH crosscourt, mid used 4.7% · won 52% · +5.5±9.0 vs own baseline
  4. vs T serve (deuce court) → BH through the middle, deep used 3.6% · won 51% · +4.3±9.9 vs own baseline
  5. vs T serve (deuce court) → BH through the middle, mid used 4.6% · won 50% · +3.6±9.1 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → FH crosscourt used 5.8% · won 61% · +6.4±7.6 vs own baseline
  2. FH down the line → FH crosscourt used 1.8% · won 64% · +9.0±10.8 vs own baseline
  3. FH crosscourt → FH crosscourt used 5.7% · won 59% · +4.7±7.7 vs own baseline
  4. BH through the middle → FH down the line used 1.7% · won 61% · +6.4±11.0 vs own baseline
  5. FH down the line → BH down the line used 2.2% · won 60% · +5.3±10.5 vs own baseline

Discovered sequences

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

  1. FH crosscourt → FH crosscourt → FH crosscourt used 1.7% · won 59% · +7.3±8.2 vs own baseline · +12.8 vs tour on the same sequence Disrupted by Caroline Wozniacki (14/20), Karolina Pliskova (6/7)
  2. BH crosscourt → BH slice crosscourt → BH down the line used 0.5% · won 62% · +10.8±11.5 vs own baseline · +19.5 vs tour on the same sequence Disrupted by Lara Arruabarrena (8/10)
  3. FH crosscourt → FH through the middle → FH crosscourt used 0.6% · won 62% · +10.3±11.3 vs own baseline · +16.7 vs tour on the same sequence
  4. FH crosscourt → FH down the line → BH crosscourt used 1.4% · won 56% · +4.3±8.8 vs own baseline · +7.6 vs tour on the same sequence Disrupted by Vera Zvonareva (0/6), Caroline Wozniacki (11/16)
  5. Body serve → BH crosscourt return, mid → BH crosscourt used 0.5% · won 57% · +6.1±12.1 vs own baseline · +17.7 vs tour on the same sequence
  6. Wide serve → FH through the middle return, mid → BH crosscourt used 0.5% · won 57% · +5.8±11.9 vs own baseline · +7.4 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 forehand · serve +1+3.7141
FH to their forehand · return+3.5184
BH to the middle · serve +1+2.3199
FH to their backhand · rally+2.2282
BH to the middle · return+2.0345

Most exposed to

BH to their forehand · return−3.5121
T 1st serve · ad court−2.6304
FH to their backhand · return−2.3208
FH to their forehand · return−2.2207
T 1st serve · deuce court−2.1374

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +3.01, Caroline Wozniacki +2.80, Daria Kasatkina +2.19, Angelique Kerber +2.16, Sara Errani +1.96

Favourable matchups

Sara Errani +2.39, Marie Bouzkova +2.03, Angelique Kerber +1.88, Linda Fruhvirtova +1.76, Elina Avanesyan +1.73

Active players who are best at the shot in the top weakness: Alexandra Eala, Magdalena Frech, Belinda Bencic, Angelique Kerber, Clara Tauson

Tactical fingerprint

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

Drop shots / shot3.5%
Wide serves · deuce48%
Chipped returns19%
Wide serves · ad45%
1st serve in64%
Deep returns34%
BH down the line22%
Point-ending shots25.0%
Serve & volley2%
Points at net8%
Avg rally length4.1
T serves · ad35%
Unforced errors / shot10.0%
Backhand slice10%
FH down the line26%
T serves · deuce32%
Run-around forehands2%
Through the middle23%
Forehand share47%

Plays most like

  1. Anastasija Sevastova 2011–2025 plan v
  2. Elena Vesnina 2007–2016 plan v
  3. Anhelina Kalinina 2019–2025 plan v
  4. Sofia Kenin 2017–2026 plan v
  5. Anna Kalinskaya 2019–2026 plan v
  6. Antonia Ruzic 2024–2026 plan v
  7. R – plan v
  8. Sorana Cirstea 2014–2026 plan v

Closest from another era

  1. Elena Dementieva 1999–2010
  2. Jelena Dokic 2000–2009
  3. Anastasia Myskina 2002–2006

Charted matches