RallyIQ

WTA · Right-handed · 5 charted matches · 2018–2025

Claire Liu

Against an average opponent

Serve points won 54.4% ±4.0 raw 53.4% · tour 56.3% · 369 points
Return points won 46.2% ±4.0 raw 43.1% · tour 43.7% · 376 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.

Shot expected value

The share of points Claire Liu 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 forehand side

position worth 43% to the average player · 111 shots

OptionUsedWin %Tour
FH crosscourt 50% 49.1%±9.4 46.7%
FH through the middle 26% 33.2%±11.1 41.3%
FH down the line 23% 34.7%±11.5 44.9%

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

position worth 45% to the average player · 83 shots

OptionUsedWin %Tour
BH crosscourt 58% 47.8%±10.0 47.6%
BH through the middle 31% 40.6%±11.9 43.3%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 72 shots

OptionUsedWin %Tour
BH crosscourt 26% 44.1%±13.1 50.9%
FH crosscourt 21% 44.4%±13.8 52.7%
FH through the middle 19% 44.6%±14.0 45.8%
BH through the middle 17% 47.6%±14.5 46.2%

Return +1: drive to your forehand side

position worth 43% to the average player · 52 shots

OptionUsedWin %Tour
FH crosscourt 56% 43.9%±11.7 47.6%
FH through the middle 25% 49.3%±14.3 41.3%
FH down the line 19% 42.8%±14.9 44.1%

Serve under pressure

Pressure predictability index ±0 How much less varied Claire Liu's first-serve direction gets on break points. Positive means easier to read. Based on 48 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 42% 38% 63% / 66%
Body 19% 31% ▲ 56% / 57%
T 39% 31% ▼ 65% / 68%

177 normal · 13 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 49% 60% ▲ 63% / 66%
Body 9% 11% 47% / 56%
T 42% 29% ▼ 67% / 64%

143 normal · 35 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 won
Wide42% 54.4%±7.8 n=79
Body20% 56.1%±9.9 n=38
T38% 55.6%±8.1 n=73

Consistent with an optimal mix (p = 0.95).

Ad court

1st serveUsagePoints won
Wide51% 52.9%±7.5 n=91
Body10% 44.4%±11.9 n=17
T39% 53.7%±8.2 n=70

Consistent with an optimal mix (p = 0.18).

Repeating the previous direction to the same court: +1.3±9.3 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. (128 repeats, 230 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 15 51% +7.6±12.3
1stAd courtT 60 40% +4.1±8.5
1stAd courtWide 46 28% −6.4±8.5
1stDeuce courtBody 24 35% −7.8±10.7
1stDeuce courtT 32 33% +1.2±9.8
1stDeuce courtWide 74 33% −1.1±7.6
2ndAd courtBody 28 60% +4.5±10.6
2ndAd courtT 13 62% +6.6±12.2
2ndAd courtWide 18 54% +0.8±11.8
2ndDeuce courtBody 37 57% +2.8±9.9
2ndDeuce courtT 16 56% +0.1±12.0
2ndDeuce courtWide 13 51% −2.3±12.5

Signature patterns

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

Serve → +1

  1. Not enough data

Return

  1. vs wide serve (deuce court) → FH through the middle, mid used 18.6% · won 42% · −6.0±11.6 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → BH crosscourt used 10.9% · won 45% · +0.2±11.8 vs own baseline
  2. FH crosscourt → FH down the line used 11.4% · won 42% · −2.7±11.6 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Claire Liu 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 2.7% · won 46% · +3.9±11.7 vs own baseline · +1.7 vs tour on the same sequence Disrupted by Petra Martic (6/12)
  2. BH crosscourt → BH crosscourt → BH crosscourt used 2.4% · won 40% · −1.8±11.9 vs own baseline · −10.5 vs tour on the same sequence Disrupted by Petra Martic (4/10)
  3. FH crosscourt → FH crosscourt → FH through the middle used 1.8% · won 33% · −9.1±12.2 vs own baseline · −24.5 vs tour on the same sequence
  4. FH crosscourt → FH crosscourt → FH down the line used 2.4% · won 34% · −8.3±11.5 vs own baseline · −23.9 vs tour on the same sequence Disrupted by Petra Martic (3/10)

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

Most exposed to

FH to their forehand · rally−1.8144

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

Charted matches