RallyIQ

WTA · Right-handed · 81 charted matches · 2014–2026

Belinda Bencic

Archetype: Forehand line-changer · Backhand line-changer

Against an average opponent

Serve points won 61.6% ±2.4 raw 59.6% · tour 56.3% · 5,422 points
Return points won 46.3% ±2.6 raw 43.7% · tour 43.7% · 5,501 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 +0.11 ±0.04 better than 74% of WTA · raw +0.11
Shot selection +0.12 ±0.07 better than 58% of WTA · raw +0.11
Execution +0.91 ±0.34 better than 89% of WTA · raw +0.86
Tactical adaptability −0.09 first serves toward what's working, set to set · 78 matches
Adaptation speed −0.03 same, every two to three service games · per 100 first serves
Points left on the table 2.41 per 100 shots vs best direction · lower than 75% 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 26,259 shots.

Shot expected value

The share of points Belinda Bencic 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 middle

position worth 50% to the average player · 1,668 shots

OptionUsedWin %Tour
FH down the line 22% 57.2%±4.1 52.2%
FH crosscourt 19% 53.4%±4.5 52.7%
FH through the middle 15% 48.4%±4.9 45.8%
BH through the middle 15% 50.6%±5.0 46.2%
BH down the line 13% 55.9%±5.2 50.0%
BH crosscourt 13% 48.6%±5.4 50.9%
FH down the line + approach 1% 69.1%±13.9 68.6%

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

position worth 45% to the average player · 1,413 shots

OptionUsedWin %Tour
BH crosscourt 46% 52.1%±3.2 47.6%
BH through the middle 29% 43.0%±4.0 43.3%
BH down the line 17% 56.1%±5.1 46.8%
BH slice through the middle 2% 27.8%±10.4 34.4%
BH slice crosscourt 1% 31.0%±12.2 40.4%
BH slice down the line 1% 19.2%±11.3 31.7%
BH lob crosscourt 1% 41.1%±14.1 32.8%
BH lob through the middle 1% 23.2%±12.3 27.1%

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

position worth 43% to the average player · 1,411 shots

OptionUsedWin %Tour
FH crosscourt 46% 50.3%±3.2 46.7%
FH down the line 22% 55.3%±4.5 44.9%
FH through the middle 20% 39.9%±4.6 41.3%
FH slice through the middle 7% 30.3%±7.0 29.2%
FH slice crosscourt 3% 36.7%±10.2 31.9%
FH down the line + approach 1% 68.0%±13.8 65.4%
FH slice down the line 1% 18.9%±11.6 24.3%

Serve +1: mid-depth return to your middle

position worth 51% to the average player · 875 shots

OptionUsedWin %Tour
FH down the line 23% 59.3%±5.5 53.3%
FH crosscourt 20% 60.0%±5.7 54.0%
FH through the middle 17% 51.2%±6.3 45.5%
BH through the middle 16% 43.8%±6.5 46.3%
BH crosscourt 14% 57.6%±6.8 52.5%
BH down the line 10% 51.6%±7.9 51.0%

Serve under pressure

Pressure predictability index +3 How much less varied Belinda Bencic's first-serve direction gets on break points. Positive means easier to read. Based on 539 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 49% 58% ▲ 66% / 66%
Body 18% 14% 65% / 57%
T 32% 28% 71% / 68%

2,684 normal · 133 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 41% 46% 70% / 66%
Body 15% 13% 63% / 56%
T 44% 42% 69% / 64%

2,188 normal · 406 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% 60.5%±2.1 n=1,404 65% ▲
Body18% 60.2%±3.5 n=504 3% ▼
T32% 58.5%±2.6 n=909 32%

Consistent with an optimal mix (p = 0.59).
Optimal mix: +0.2 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide42% 56.9%±2.4 n=1,093 41% ▼
Body14% 59.7%±4.0 n=370 0% ▼
T44% 61.8%±2.3 n=1,131 59% ▲

Off equilibrium (p = 0.044): serve T more. Gap 2.4 points per 100 first serves.
Optimal mix: +0.5 per 100 first serves.

Exploitability 0.35 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: +0.8±2.4 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. (1,456 repeats, 3,793 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 339 47% +2.8±4.3
1stAd courtT 656 33% −2.6±3.0
1stAd courtWide 596 31% −3.6±3.0
1stDeuce courtBody 408 45% +2.1±3.9
1stDeuce courtT 567 28% −4.6±3.0
1stDeuce courtWide 772 33% −1.1±2.7
2ndAd courtBody 470 59% +4.1±3.6
2ndAd courtT 221 58% +2.5±5.1
2ndAd courtWide 356 60% +6.1±4.1
2ndDeuce courtBody 546 58% +3.4±3.4
2ndDeuce courtT 279 55% −1.1±4.7
2ndDeuce courtWide 283 57% +2.8±4.6

Signature patterns

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

Serve → +1

  1. Wide serve (deuce court) → BH crosscourt used 3.1% · won 65% · +0.9±5.7 vs own baseline
  2. Wide serve (deuce court) → FH down the line used 4.3% · won 63% · −0.7±5.1 vs own baseline
  3. Body serve (ad court) → FH crosscourt used 2.2% · won 58% · −5.6±6.8 vs own baseline
  4. T serve (ad court) → FH down the line used 2.6% · won 56% · −7.1±6.5 vs own baseline
  5. T serve (ad court) → FH crosscourt used 3.2% · won 57% · −6.6±5.9 vs own baseline

Return

  1. vs T serve (deuce court) → BH through the middle, deep used 2.9% · won 56% · +9.7±6.5 vs own baseline
  2. vs wide serve (deuce court) → FH through the middle, mid used 2.5% · won 55% · +9.3±6.9 vs own baseline
  3. vs wide serve (deuce court) → FH through the middle, deep used 2.2% · won 56% · +9.8±7.3 vs own baseline
  4. vs wide serve (ad court) → BH crosscourt, mid used 3.7% · won 54% · +7.6±5.9 vs own baseline
  5. vs body serve (ad court) → BH through the middle, mid used 2.1% · won 54% · +7.6±7.5 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 1.9% · won 60% · +7.8±7.2 vs own baseline
  2. BH crosscourt → FH crosscourt used 4.1% · won 57% · +5.0±5.3 vs own baseline
  3. FH down the line → BH down the line used 3.0% · won 58% · +5.7±6.1 vs own baseline
  4. BH down the line → BH crosscourt used 1.5% · won 59% · +7.4±8.0 vs own baseline
  5. FH crosscourt → FH down the line used 5.9% · won 56% · +3.7±4.5 vs own baseline

Discovered sequences

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

  1. Wide serve → FH through the middle return, mid → FH down the line used 0.5% · won 63% · +11.7±8.4 vs own baseline · +12.5 vs tour on the same sequence Disrupted by Kiki Bertens (5/7)
  2. FH crosscourt → FH through the middle → FH down the line used 0.9% · won 60% · +8.4±6.8 vs own baseline · +8.1 vs tour on the same sequence Disrupted by Coco Gauff (2/9), Paula Badosa (3/8)
  3. BH crosscourt → BH through the middle → FH crosscourt used 0.9% · won 59% · +8.0±6.9 vs own baseline · +7.4 vs tour on the same sequence Disrupted by Elina Svitolina (3/6), Coco Gauff (11/19)
  4. Wide serve → BH crosscourt return, mid → BH down the line used 0.2% · won 65% · +13.6±10.9 vs own baseline · +26.0 vs tour on the same sequence
  5. FH down the line → BH through the middle → FH crosscourt used 0.5% · won 60% · +8.6±8.3 vs own baseline · +6.2 vs tour on the same sequence Disrupted by Paula Badosa (3/10)
  6. Wide serve → BH through the middle return, mid → FH crosscourt used 0.3% · won 62% · +10.4±9.8 vs own baseline · +10.6 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 · return+4.4308
FH slice to the middle · rally+3.3153
BH to their forehand · serve +1+3.2365
FH to their backhand · return +1+2.7262
BH to their backhand · serve +1+2.6545

Most exposed to

FH to their forehand · return−2.9724
T 1st serve · deuce court−2.31,020
BH to their backhand · serve +1−2.2631
FH to their forehand · rally−2.21,649
BH to their backhand · rally−2.01,198

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +3.10, Caroline Wozniacki +2.99, Daria Kasatkina +2.36, Sara Errani +2.21, Angelique Kerber +2.15

Favourable matchups

Sara Errani +3.17, Marie Bouzkova +2.77, Angelique Kerber +2.73, Elina Avanesyan +2.54, Katie Volynets +2.27

Active players who are best at the shot in the top weakness: Caroline Wozniacki, Su Wei Hsieh, Anhelina Kalinina, Ashlyn Krueger, Katie Boulter

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%
T serves · ad44%
Chipped returns15%
Deep returns34%
FH down the line31%
1st serve in63%
Wide serves · ad42%
Point-ending shots24.4%
Through the middle29%
Serve & volley0%
Points at net6%
Forehand share52%
Avg rally length3.8
T serves · deuce32%
Unforced errors / shot9.1%
Backhand slice3%
Drop shots / shot0.7%
Run-around forehands1%

Plays most like

  1. Karolina Pliskova 2013–2026 plan v
  2. Sorana Cirstea 2014–2026 plan v
  3. Anastasia Potapova 2017–2026 plan v
  4. Shelby Rogers 2014–2024 plan v
  5. Elise Mertens 2018–2026 plan v
  6. Ekaterina Alexandrova 2017–2026 plan v
  7. Emma Raducanu 2018–2026 plan v
  8. Anna Kalinskaya 2019–2026 plan v

Closest from another era

  1. Elena Dementieva 1999–2010
  2. Anastasia Myskina 2002–2006
  3. Lindsay Davenport 1995–2006

Charted matches