RallyIQ

WTA · Right-handed · 147 charted matches · 1998–2026

Serena Williams

Archetype: First-strike aggressor · Short-point player

Against an average opponent

Serve points won 64.1% ±2.2 raw 62.2% · tour 56.3% · 9,747 points
Return points won 47.8% ±2.4 raw 45.1% · tour 43.7% · 10,251 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 +0.34 ±0.04 better than 97% of WTA · raw +0.34
Shot selection +0.47 ±0.05 better than 93% of WTA · raw +0.46
Execution −0.04 ±0.27 better than 59% of WTA · raw −0.05
Tactical adaptability +0.14 first serves toward what's working, set to set · 135 matches
Adaptation speed +0.07 same, every two to three service games · per 100 first serves
Points left on the table 2.20 per 100 shots vs best direction · lower than 94% 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 45,473 shots.

Shot expected value

The share of points Serena Williams 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 · 2,545 shots

OptionUsedWin %Tour
BH crosscourt 40% 44.8%±2.5 47.6%
BH through the middle 28% 39.6%±3.0 43.3%
BH down the line 22% 48.6%±3.5 46.8%
BH slice crosscourt 3% 37.2%±7.8 40.4%
BH slice through the middle 3% 34.3%±8.2 34.4%
BH crosscourt + approach 1% 73.1%±11.8 68.9%
BH slice down the line 1% 20.4%±11.0 31.7%
BH down the line + approach 1% 76.6%±11.9 70.2%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 2,167 shots

OptionUsedWin %Tour
FH crosscourt 24% 50.0%±3.5 52.7%
BH crosscourt 15% 49.6%±4.4 50.9%
BH through the middle 15% 44.6%±4.5 46.2%
FH down the line 14% 54.4%±4.5 52.2%
BH down the line 13% 49.7%±4.7 50.0%
FH through the middle 13% 42.6%±4.7 45.8%
FH down the line + approach 3% 68.8%±8.5 68.6%
FH crosscourt + approach 1% 73.2%±10.9 69.7%

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

position worth 43% to the average player · 2,164 shots

OptionUsedWin %Tour
FH crosscourt 52% 47.3%±2.5 46.7%
FH through the middle 21% 40.9%±3.7 41.3%
FH down the line 20% 48.7%±3.9 44.9%
FH slice through the middle 3% 21.3%±7.6 29.2%
FH down the line + approach 1% 70.2%±10.6 65.4%
FH slice crosscourt 1% 35.5%±11.2 31.9%
FH slice down the line 1% 20.7%±10.8 24.3%

Return +1: drive to your middle

position worth 50% to the average player · 1,658 shots

OptionUsedWin %Tour
FH crosscourt 22% 51.8%±4.2 52.3%
BH crosscourt 19% 54.8%±4.5 50.8%
BH through the middle 17% 45.9%±4.7 46.2%
FH down the line 14% 54.6%±5.2 53.0%
BH down the line 12% 56.5%±5.4 50.6%
FH through the middle 11% 51.4%±5.9 46.5%
FH down the line + approach 3% 72.9%±8.9 69.2%
BH crosscourt + approach 2% 65.0%±11.6 64.5%

Serve under pressure

Pressure predictability index ±0 How much less varied Serena Williams's first-serve direction gets on break points. Positive means easier to read. Based on 884 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 50% 48% 70% / 66%
Body 8% 10% 62% / 57%
T 42% 42% 79% / 68%

4,864 normal · 187 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 45% 45% 75% / 66%
Body 6% 6% 60% / 56%
T 49% 48% 70% / 64%

3,932 normal · 697 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% 62.5%±1.6 n=2,501 44% ▼
Body8% 57.9%±3.9 n=413 0% ▼
T42% 63.2%±1.7 n=2,137 56% ▲

Consistent with an optimal mix (p = 0.08).
Optimal mix: +0.5 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide45% 61.3%±1.7 n=2,076 41% ▼
Body6% 59.7%±4.5 n=295 0% ▼
T49% 62.9%±1.7 n=2,258 59% ▲

Consistent with an optimal mix (p = 0.33).
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.45 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: +1.6±1.7 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. (4,089 repeats, 5,299 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 672 43% −1.0±3.1
1stAd courtT 1,256 39% +3.3±2.2
1stAd courtWide 1,087 34% −0.3±2.3
1stDeuce courtBody 793 47% +4.1±2.9
1stDeuce courtT 1,274 34% +2.3±2.2
1stDeuce courtWide 1,216 35% +1.2±2.2
2ndAd courtBody 774 55% +0.2±2.9
2ndAd courtT 483 57% +1.6±3.6
2ndAd courtWide 633 56% +2.3±3.2
2ndDeuce courtBody 938 56% +1.9±2.6
2ndDeuce courtT 543 60% +4.2±3.4
2ndDeuce courtWide 514 58% +4.0±3.5

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 2.4% · won 65% · −1.6±5.0 vs own baseline
  2. T serve (deuce court) → FH crosscourt used 2.2% · won 56% · −10.6±5.5 vs own baseline
  3. T serve (ad court) → FH crosscourt used 2.5% · won 56% · −10.2±5.1 vs own baseline
  4. Wide serve (ad court) → BH crosscourt used 2.3% · won 54% · −12.0±5.3 vs own baseline
  5. Wide serve (deuce court) → FH down the line used 2.4% · won 54% · −12.1±5.2 vs own baseline

Return

  1. vs wide serve (deuce court) → FH crosscourt, mid used 3.3% · won 63% · +18.6±4.4 vs own baseline
  2. vs T serve (ad court) → FH through the middle, deep used 2.6% · won 55% · +10.7±5.1 vs own baseline
  3. vs T serve (deuce court) → BH through the middle, deep used 2.3% · won 54% · +10.1±5.3 vs own baseline
  4. vs wide serve (ad court) → BH crosscourt, mid used 3.7% · won 51% · +7.1±4.3 vs own baseline
  5. vs T serve (ad court) → FH through the middle, mid used 4.1% · won 49% · +4.2±4.1 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH down the line used 4.5% · won 55% · +6.4±4.1 vs own baseline
  2. FH down the line → FH crosscourt used 1.9% · won 56% · +7.7±6.0 vs own baseline
  3. FH crosscourt → BH crosscourt used 5.2% · won 53% · +4.1±3.8 vs own baseline
  4. BH down the line → FH down the line used 2.6% · won 54% · +5.5±5.3 vs own baseline
  5. FH crosscourt → BH down the line used 1.6% · won 55% · +6.3±6.4 vs own baseline

Discovered sequences

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

  1. Wide serve → BH through the middle return, mid → FH crosscourt used 0.3% · won 60% · +12.5±8.8 vs own baseline · +7.8 vs tour on the same sequence Disrupted by Venus Williams (10/17)
  2. FH crosscourt → FH crosscourt → FH down the line used 1.4% · won 53% · +5.7±4.7 vs own baseline · +6.1 vs tour on the same sequence Disrupted by Katarina Srebotnik (1/6), Elena Dementieva (4/15)
  3. FH crosscourt → FH through the middle → FH down the line + approach used 0.1% · won 65% · +17.6±10.9 vs own baseline · +10.0 vs tour on the same sequence Disrupted by Venus Williams (8/8)
  4. BH through the middle → FH through the middle → FH crosscourt used 0.6% · won 55% · +7.4±7.0 vs own baseline · +7.7 vs tour on the same sequence Disrupted by Maria Sharapova (7/13), Venus Williams (11/13)
  5. FH crosscourt → FH through the middle → BH down the line used 0.2% · won 58% · +10.6±9.6 vs own baseline · +9.3 vs tour on the same sequence
  6. T serve → FH through the middle return, deep → FH down the line used 0.2% · won 61% · +12.9±10.7 vs own baseline · +25.5 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

T 2nd serve · ad court+3.6416
T 1st serve · deuce court+3.42,111
FH to their backhand · return+2.9692
T 1st serve · ad court+2.62,231
FH to their backhand · serve +1+2.6848

Most exposed to

BH slice to the middle · serve +1−2.8136
FH slice to the middle · return−2.1237
BH to their backhand · return +1−2.0666
BH slice to the middle · rally−1.7367
FH to their forehand · return +1−1.6777

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +2.71, Caroline Wozniacki +2.27, Tatjana Maria +1.86, Daria Kasatkina +1.69, Sara Errani +1.67

Favourable matchups

Sara Errani +1.98, Angelique Kerber +1.27, Elina Avanesyan +1.18, Marie Bouzkova +1.15, Katie Volynets +0.99

Active players who are best at the shot in the top weakness: Tatjana Maria, Bianca Andreescu

Tactical fingerprint

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

BH down the line27%
Wide serves · deuce50%
Point-ending shots29.9%
T serves · ad49%
Unforced errors / shot12.4%
T serves · deuce42%
Wide serves · ad45%
Points at net8%
FH down the line29%
Serve & volley1%
Deep returns32%
1st serve in61%
Backhand slice6%
Drop shots / shot0.8%
Through the middle25%
Run-around forehands2%
Chipped returns2%
Avg rally length3.5
Forehand share47%

Plays most like

  1. Naomi Osaka 2016–2026 plan v
  2. Lindsay Davenport 1995–2006 plan v
  3. Veronika Kudermetova 2018–2025 plan v
  4. Karolina Pliskova 2013–2026 plan v
  5. Daniela Hantuchova 2002–2015 plan v
  6. Sorana Cirstea 2014–2026 plan v
  7. Ekaterina Alexandrova 2017–2026 plan v
  8. Elena Gabriela Ruse 2016–2026 plan v

Closest from another era

  1. Monica Seles 1990–2003
  2. Jennifer Capriati 1990–2002
  3. Arantxa Sanchez Vicario 1988–2001

Charted matches