RallyIQ

WTA · Right-handed · 69 charted matches · 2018–2026

Emma Raducanu

Archetype: Rarely serves the T · Patient builder

Against an average opponent

Serve points won 59.0% ±2.5 raw 58.0% · tour 56.3% · 4,498 points
Return points won 45.5% ±2.6 raw 43.3% · tour 43.7% · 4,613 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 −0.02 ±0.05 better than 50% of WTA · raw −0.01
Shot selection −0.09 ±0.09 better than 35% of WTA · raw −0.07
Execution +0.76 ±0.31 better than 86% of WTA · raw +0.86
Tactical adaptability −0.06 first serves toward what's working, set to set · 67 matches
Adaptation speed +0.09 same, every two to three service games · per 100 first serves
Points left on the table 2.53 per 100 shots vs best direction · lower than 63% 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 22,153 shots.

Shot expected value

The share of points Emma Raducanu 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 · 1,475 shots

OptionUsedWin %Tour
BH crosscourt 33% 46.0%±3.6 47.6%
BH through the middle 32% 38.5%±3.6 43.3%
BH down the line 14% 51.4%±5.4 46.8%
BH slice through the middle 7% 29.9%±6.6 34.4%
BH slice crosscourt 7% 38.3%±7.2 40.4%
FH inside-in 1% 56.7%±13.1 55.6%
BH slice down the line 1% 30.7%±12.5 31.7%
FH inside-out 1% 53.0%±14.3 52.5%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 1,271 shots

OptionUsedWin %Tour
FH crosscourt 26% 56.9%±4.3 52.7%
BH through the middle 19% 47.8%±5.1 46.2%
FH through the middle 18% 47.7%±5.2 45.8%
FH down the line 13% 51.6%±6.0 52.2%
BH crosscourt 12% 51.3%±6.3 50.9%
BH down the line 7% 43.2%±7.7 50.0%
BH slice through the middle 1% 38.8%±13.4 44.8%
BH slice down the line 1% 44.4%±14.7 43.9%

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

position worth 43% to the average player · 1,251 shots

OptionUsedWin %Tour
FH crosscourt 42% 49.8%±3.5 46.7%
FH through the middle 23% 38.1%±4.5 41.3%
FH down the line 23% 46.5%±4.7 44.9%
FH slice through the middle 5% 21.2%±7.3 29.2%
FH slice down the line 2% 27.7%±10.4 24.3%
FH slice crosscourt 2% 25.3%±10.7 31.9%
FH lob through the middle 1% 26.0%±11.7 29.4%

Return +1: drive to your middle

position worth 50% to the average player · 749 shots

OptionUsedWin %Tour
FH crosscourt 22% 50.5%±6.0 52.3%
BH through the middle 21% 50.1%±6.2 46.2%
FH through the middle 21% 47.0%±6.2 46.5%
FH down the line 13% 54.4%±7.6 53.0%
BH crosscourt 12% 47.0%±7.7 50.8%
BH down the line 7% 45.1%±9.9 50.6%
BH slice through the middle 2% 50.5%±13.7 45.9%
BH slice crosscourt 2% 48.5%±14.3 45.0%

Serve under pressure

Pressure predictability index +4 How much less varied Emma Raducanu's first-serve direction gets on break points. Positive means easier to read. Based on 503 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 47% 39% 68% / 66%
Body 25% 28% 56% / 57%
T 29% 32% 68% / 68%

2,216 normal · 117 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 43% 51% 71% / 66%
Body 17% 13% 51% / 56%
T 39% 37% 63% / 64%

1,773 normal · 386 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
Wide46% 60.1%±2.4 n=1,080 61% ▲
Body25% 53.3%±3.3 n=579 10% ▼
T29% 58.5%±3.1 n=674 29%

Off equilibrium (p = 0.012): serve wide more. Gap 2.1 points per 100 first serves.
Optimal mix: +0.9 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide44% 62.3%±2.5 n=960 60% ▲
Body17% 50.8%±4.2 n=359 1% ▼
T39% 56.8%±2.8 n=840 39%

Off equilibrium (p < 0.001): serve wide more. Gap 4.1 points per 100 first serves.
Optimal mix: +1.4 per 100 first serves.

Exploitability 1.15 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: −2.4±3.0 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. (1,764 repeats, 2,590 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 315 41% −3.3±4.3
1stAd courtT 517 36% +0.6±3.4
1stAd courtWide 547 36% +1.8±3.3
1stDeuce courtBody 423 43% +0.8±3.8
1stDeuce courtT 465 32% +0.3±3.5
1stDeuce courtWide 629 36% +2.0±3.1
2ndAd courtBody 378 57% +2.4±4.0
2ndAd courtT 121 54% −1.1±6.7
2ndAd courtWide 338 50% −3.8±4.3
2ndDeuce courtBody 419 54% −0.7±3.9
2ndDeuce courtT 244 52% −3.9±5.0
2ndDeuce courtWide 210 56% +2.5±5.3

Signature patterns

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

Serve → +1

  1. T serve (ad court) → FH down the line used 3.2% · won 63% · +1.8±6.3 vs own baseline
  2. Wide serve (deuce court) → FH crosscourt used 3.6% · won 59% · −2.4±6.0 vs own baseline
  3. Wide serve (deuce court) → FH down the line used 2.8% · won 58% · −3.6±6.7 vs own baseline
  4. Wide serve (ad court) → FH crosscourt used 2.1% · won 56% · −6.0±7.5 vs own baseline
  5. T serve (ad court) → FH crosscourt used 2.3% · won 54% · −7.4±7.4 vs own baseline

Return

  1. vs body serve (deuce court) → BH through the middle, deep used 2.6% · won 57% · +13.4±7.1 vs own baseline
  2. vs wide serve (deuce court) → FH crosscourt, mid used 2.2% · won 56% · +12.4±7.6 vs own baseline
  3. vs T serve (deuce court) → BH through the middle, deep used 2.2% · won 55% · +11.6±7.6 vs own baseline
  4. vs wide serve (ad court) → BH crosscourt, mid used 4.2% · won 51% · +7.8±5.8 vs own baseline
  5. vs body serve (deuce court) → BH through the middle, mid used 3.2% · won 49% · +6.1±6.5 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH down the line used 5.4% · won 53% · +7.2±4.8 vs own baseline
  2. BH down the line → FH crosscourt used 2.3% · won 57% · +10.9±7.0 vs own baseline
  3. FH crosscourt → FH crosscourt used 4.9% · won 52% · +6.3±5.1 vs own baseline
  4. FH down the line → FH down the line used 1.1% · won 54% · +8.1±9.1 vs own baseline
  5. BH down the line → FH down the line used 1.6% · won 52% · +6.3±8.1 vs own baseline

Discovered sequences

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

  1. FH crosscourt → FH through the middle → FH crosscourt used 0.6% · won 58% · +10.7±8.3 vs own baseline · +6.1 vs tour on the same sequence Disrupted by Renata Zarazua (4/9)
  2. T serve → FH through the middle return, deep → FH down the line used 0.3% · won 62% · +15.1±10.7 vs own baseline · +28.7 vs tour on the same sequence
  3. FH down the line → BH through the middle → FH crosscourt used 0.5% · won 57% · +9.7±9.2 vs own baseline · +4.1 vs tour on the same sequence Disrupted by Jessica Pegula (5/6)
  4. FH crosscourt → FH through the middle → FH through the middle used 0.5% · won 56% · +9.3±9.4 vs own baseline · +15.0 vs tour on the same sequence
  5. FH through the middle → FH through the middle → FH crosscourt used 0.4% · won 57% · +9.8±9.7 vs own baseline · +10.7 vs tour on the same sequence
  6. FH through the middle → FH through the middle → BH through the middle used 0.3% · won 58% · +10.7±10.3 vs own baseline · +18.3 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 · return+3.6264
BH to their forehand · return +1+2.3165
FH to their forehand · return +1+2.2466
BH to their backhand · return +1+2.0384
FH to the middle · return+1.8874

Most exposed to

FH to their forehand · return +1−2.5449
BH to their forehand · return +1−2.3208
FH to their forehand · serve +1−2.2613
FH to their backhand · return +1−1.9320
FH slice to the middle · return−1.7165

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +2.88, Caroline Wozniacki +2.83, Angelique Kerber +2.26, Daria Kasatkina +2.22, Sara Errani +2.08

Favourable matchups

Sara Errani +2.78, Angelique Kerber +2.42, Marie Bouzkova +2.38, Elina Avanesyan +2.18, Katie Volynets +2.06

Active players who are best at the shot in the top weakness: Sara Errani, Paula Badosa, Victoria Azarenka, Linda Noskova, Sara Sorribes Tormo

Tactical fingerprint

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

1st serve in67%
Through the middle33%
Wide serves · deuce46%
Wide serves · ad44%
Deep returns34%
T serves · ad39%
Avg rally length4.1
Backhand slice15%
Chipped returns9%
Serve & volley0%
Forehand share53%
BH down the line19%
Drop shots / shot1.1%
Run-around forehands4%
Point-ending shots21.8%
FH down the line26%
Points at net4%
Unforced errors / shot9.1%
T serves · deuce29%

Plays most like

  1. Emma Navarro 2019–2026 plan v
  2. Lin Zhu 2016–2025 plan v
  3. Iva Jovic 2024–2026 plan v
  4. Marie Bouzkova 2018–2026 plan v
  5. Anna Blinkova 2019–2026 plan v
  6. Andrea Petkovic 2010–2022 plan v
  7. Coco Gauff 2019–2026 plan v
  8. Nao Hibino 2016–2025 plan v

Closest from another era

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

Charted matches