RallyIQ

WTA · Right-handed · 14 charted matches · 2008–2014

Na Li

Archetype: Ad-court T server · Rallies through the middle

Against an average opponent

Serve points won 60.1% ±3.2 raw 58.8% · tour 56.3% · 1,069 points
Return points won 45.8% ±3.3 raw 43.9% · tour 43.7% · 1,041 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 +0.21 ±0.11 better than 85% of WTA · raw +0.20
Shot selection +0.55 ±0.15 better than 95% of WTA · raw +0.54
Execution −0.31 ±0.59 better than 44% of WTA · raw −0.41
Tactical adaptability +0.01 first serves toward what's working, set to set · 14 matches
Adaptation speed +0.07 same, every two to three service games · per 100 first serves
Points left on the table 2.18 per 100 shots vs best direction · lower than 95% 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 5,508 shots.

Shot expected value

The share of points Na Li 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 · 418 shots

OptionUsedWin %Tour
FH crosscourt 50% 52.1%±5.5 46.7%
FH down the line 26% 46.1%±7.2 44.9%
FH through the middle 25% 49.0%±7.4 41.3%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 333 shots

OptionUsedWin %Tour
FH crosscourt 31% 57.4%±7.3 52.7%
FH down the line 21% 60.1%±8.5 52.2%
FH through the middle 15% 42.2%±9.8 45.8%
BH crosscourt 14% 52.6%±10.2 50.9%
BH through the middle 11% 43.5%±10.7 46.2%
BH down the line 7% 47.7%±12.4 50.0%

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

position worth 45% to the average player · 289 shots

OptionUsedWin %Tour
BH crosscourt 42% 52.5%±6.9 47.6%
BH down the line 28% 49.9%±8.2 46.8%
BH through the middle 23% 44.4%±8.8 43.3%
BH slice through the middle 4% 33.0%±13.5 34.4%

Serve +1: mid-depth return to your middle

position worth 51% to the average player · 191 shots

OptionUsedWin %Tour
FH crosscourt 26% 54.0%±9.8 54.0%
BH crosscourt 23% 44.5%±10.2 52.5%
BH through the middle 14% 53.8%±12.0 46.3%
BH down the line 14% 52.6%±12.1 51.0%
FH down the line 12% 66.6%±11.8 53.3%
FH through the middle 11% 44.2%±12.8 45.5%

Serve under pressure

Pressure predictability index −9 How much less varied Na Li's first-serve direction gets on break points. Positive means easier to read. Based on 106 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 42% 33% ▼ 62% / 66%
Body 18% 24% 58% / 57%
T 39% 43% 66% / 68%

528 normal · 21 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 32% 34% 69% / 66%
Body 5% 8% 61% / 56%
T 63% 58% 64% / 64%

431 normal · 85 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
Wide42% 58.4%±5.0 n=231 57% ▲
Body18% 53.7%±7.2 n=101 3% ▼
T40% 56.4%±5.2 n=217 40%

Consistent with an optimal mix (p = 0.60).
Optimal mix: +0.7 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide32% 67.4%±5.5 n=166 47% ▲
Body6% 61.6%±10.4 n=29 0% ▼
T62% 58.1%±4.3 n=321 53% ▼

Consistent with an optimal mix (p = 0.07).
Optimal mix: +0.8 per 100 first serves.

Exploitability 0.72 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: +0.2±5.4 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. (365 repeats, 672 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 56 47% +2.8±8.8
1stAd courtT 145 35% −0.9±5.9
1stAd courtWide 102 30% −4.7±6.5
1stDeuce courtBody 77 46% +3.0±7.9
1stDeuce courtT 93 37% +5.0±7.2
1stDeuce courtWide 170 29% −4.9±5.3
2ndAd courtBody 63 56% +1.4±8.5
2ndAd courtT 45 54% −1.0±9.5
2ndAd courtWide 84 59% +5.3±7.6
2ndDeuce courtBody 75 60% +5.9±7.9
2ndDeuce courtT 67 60% +3.6±8.2
2ndDeuce courtWide 57 55% +1.6±8.8

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 2.5% · won 65% · +3.5±10.8 vs own baseline
  2. Body serve (deuce court) → BH crosscourt used 2.3% · won 64% · +2.1±11.1 vs own baseline
  3. T serve (ad court) → FH down the line used 3.3% · won 62% · +0.9±10.3 vs own baseline
  4. Wide serve (ad court) → BH through the middle used 3.2% · won 62% · +0.3±10.4 vs own baseline
  5. Wide serve (ad court) → BH down the line used 3.7% · won 62% · +0.1±10.0 vs own baseline

Return

  1. vs wide serve (deuce court) → FH down the line, mid used 3.3% · won 56% · +12.4±11.6 vs own baseline
  2. vs T serve (deuce court) → BH through the middle, mid used 4.4% · won 53% · +9.0±10.9 vs own baseline
  3. vs wide serve (ad court) → BH crosscourt, mid used 7.3% · won 50% · +5.7±9.4 vs own baseline
  4. vs T serve (ad court) → FH through the middle, deep used 4.2% · won 50% · +6.4±11.0 vs own baseline
  5. vs T serve (ad court) → FH down the line, mid used 4.1% · won 49% · +5.5±11.1 vs own baseline

Rally, consecutive own shots

  1. BH through the middle → FH down the line used 2.6% · won 61% · +10.2±10.6 vs own baseline
  2. FH down the line → FH crosscourt used 3.6% · won 58% · +7.8±9.7 vs own baseline
  3. FH through the middle → FH crosscourt used 4.6% · won 56% · +6.0±9.0 vs own baseline
  4. FH crosscourt → FH crosscourt used 8.0% · won 55% · +4.4±7.4 vs own baseline
  5. BH crosscourt → FH crosscourt used 5.1% · won 54% · +3.9±8.8 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Na Li 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 0.9% · won 64% · +12.4±11.2 vs own baseline · +19.0 vs tour on the same sequence Disrupted by Maria Sharapova (7/12)
  2. FH crosscourt → FH through the middle → FH down the line used 1.0% · won 62% · +10.6±11.0 vs own baseline · +17.8 vs tour on the same sequence Disrupted by Maria Sharapova (3/6), Dominika Cibulkova (5/9)
  3. BH through the middle → FH crosscourt → FH down the line used 0.8% · won 60% · +8.8±11.6 vs own baseline · +27.4 vs tour on the same sequence Disrupted by Maria Sharapova (3/6), Kim Clijsters (6/6)
  4. FH down the line → BH crosscourt → BH crosscourt used 1.1% · won 58% · +7.0±10.6 vs own baseline · +15.2 vs tour on the same sequence Disrupted by Caroline Wozniacki (4/6), Maria Sharapova (4/6)
  5. BH crosscourt → BH through the middle → FH crosscourt used 1.1% · won 58% · +7.0±10.6 vs own baseline · +9.8 vs tour on the same sequence Disrupted by Maria Sharapova (4/8), Caroline Wozniacki (8/9)
  6. FH through the middle → FH crosscourt → FH crosscourt used 0.9% · won 58% · +7.2±11.4 vs own baseline · +18.7 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 backhand · rally+1.6318
BH to their backhand · serve +1+1.5156
BH to their forehand · serve +1+0.9121
FH to the middle · rally+0.7210
Wide 1st serve · deuce court+0.3231

Most exposed to

FH to the middle · return−2.0183
FH to their forehand · return−1.9139
BH to their backhand · rally−1.3228
BH to the middle · return−1.2226
BH to their backhand · return−1.0193

Active players who are best at the shot in the top weakness: Elina Avanesyan, Caroline Wozniacki, Sara Sorribes Tormo, Lin Zhu, Qiang Wang

Tactical fingerprint

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

T serves · ad62%
BH down the line29%
1st serve in68%
Forehand share57%
Point-ending shots27.2%
Unforced errors / shot11.8%
T serves · deuce40%
Wide serves · deuce42%
Avg rally length4.1
Serve & volley0%
Points at net7%
FH down the line27%
Chipped returns5%
Deep returns30%
Backhand slice5%
Run-around forehands2%
Through the middle25%
Wide serves · ad32%
Drop shots / shot0.4%

Plays most like

  1. Maria Sharapova 2003–2020 plan v
  2. Rebecca Sramkova 2016–2026 plan v
  3. Ashlyn Krueger 2023–2026 plan v
  4. Shuai Zhang 2009–2026 plan v
  5. Qiang Wang 2012–2024 plan v
  6. Naomi Osaka 2016–2026 plan v
  7. Belinda Bencic 2014–2026 plan v
  8. Katerina Siniakova 2015–2026 plan v

Closest from another era

  1. Jennifer Capriati 1990–2002
  2. Chris Evert 1979–1989
  3. Arantxa Sanchez Vicario 1988–2001

Charted matches