RallyIQ

WTA · Right-handed · 137 charted matches · 2019–2026

Elena Rybakina

Archetype: First-strike aggressor · Short-point player

Against an average opponent

Serve points won 64.3% ±2.3 raw 63.5% · tour 56.3% · 9,398 points
Return points won 47.2% ±2.5 raw 44.2% · tour 43.7% · 9,500 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 +0.15 ±0.03 better than 80% of WTA · raw +0.14
Shot selection +0.33 ±0.06 better than 81% of WTA · raw +0.32
Execution +0.40 ±0.26 better than 75% of WTA · raw +0.34
Tactical adaptability −0.05 first serves toward what's working, set to set · 133 matches
Adaptation speed +0.02 same, every two to three service games · per 100 first serves
Points left on the table 2.42 per 100 shots vs best direction · lower than 73% 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 43,049 shots.

Shot expected value

The share of points Elena Rybakina 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 · 2,498 shots

OptionUsedWin %Tour
FH crosscourt 39% 55.6%±2.6 52.7%
BH crosscourt 17% 51.1%±4.0 50.9%
FH through the middle 16% 43.4%±3.9 45.8%
BH through the middle 11% 45.1%±4.8 46.2%
FH down the line 9% 52.7%±5.3 52.2%
BH down the line 5% 50.7%±7.1 50.0%
FH crosscourt + approach 2% 64.3%±10.3 69.7%
FH down the line + approach 1% 65.0%±12.7 68.6%

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

position worth 43% to the average player · 2,026 shots

OptionUsedWin %Tour
FH crosscourt 51% 47.8%±2.5 46.7%
FH down the line 21% 45.4%±3.9 44.9%
FH through the middle 20% 38.5%±3.9 41.3%
FH slice through the middle 4% 25.6%±7.4 29.2%
FH slice down the line 2% 19.8%±7.8 24.3%
FH down the line + approach 1% 66.9%±12.9 65.4%

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

position worth 45% to the average player · 1,819 shots

OptionUsedWin %Tour
BH crosscourt 46% 50.1%±2.8 47.6%
BH through the middle 26% 44.7%±3.7 43.3%
BH down the line 16% 45.5%±4.7 46.8%
BH slice through the middle 4% 28.0%±7.8 34.4%
BH slice crosscourt 3% 41.5%±9.7 40.4%
BH slice down the line 2% 27.1%±10.0 31.7%
BH lob through the middle 1% 13.2%±8.7 27.1%
FH inside-in 1% 51.9%±14.3 55.6%

Return +1: drive to your middle

position worth 50% to the average player · 1,798 shots

OptionUsedWin %Tour
FH crosscourt 32% 54.6%±3.4 52.3%
BH crosscourt 17% 56.0%±4.5 50.8%
FH through the middle 16% 46.6%±4.7 46.5%
BH through the middle 16% 49.4%±4.7 46.2%
FH down the line 8% 48.1%±6.6 53.0%
BH down the line 7% 48.1%±6.6 50.6%
FH crosscourt + approach 2% 62.5%±11.6 66.8%
BH crosscourt + approach 1% 61.3%±12.8 64.5%

Serve under pressure

Pressure predictability index +1 How much less varied Elena Rybakina's first-serve direction gets on break points. Positive means easier to read. Based on 783 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 39% 39% 71% / 66%
Body 11% 10% 63% / 57%
T 50% 51% 78% / 68%

4,729 normal · 168 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 55% 57% 78% / 66%
Body 9% 9% 61% / 56%
T 36% 35% 70% / 64%

3,871 normal · 615 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
Wide39% 63.5%±1.8 n=1,930 53% ▲
Body11% 61.2%±3.4 n=524 0% ▼
T50% 63.2%±1.6 n=2,443 47% ▼

Consistent with an optimal mix (p = 0.57).
Optimal mix: +0.5 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide55% 64.6%±1.6 n=2,483 68% ▲
Body9% 59.8%±3.9 n=402 0% ▼
T36% 64.0%±2.0 n=1,601 32% ▼

Consistent with an optimal mix (p = 0.12).
Optimal mix: +0.6 per 100 first serves.

Exploitability 0.54 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: −0.4±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. (3,485 repeats, 5,624 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 651 42% −1.9±3.1
1stAd courtT 1,154 35% −0.3±2.3
1stAd courtWide 1,020 32% −2.2±2.4
1stDeuce courtBody 847 43% +0.6±2.8
1stDeuce courtT 927 33% +1.1±2.5
1stDeuce courtWide 1,337 35% +1.0±2.1
2ndAd courtBody 770 59% +3.9±2.9
2ndAd courtT 301 59% +3.7±4.5
2ndAd courtWide 657 58% +4.6±3.1
2ndDeuce courtBody 972 55% +0.1±2.6
2ndDeuce courtT 409 61% +4.5±3.8
2ndDeuce courtWide 451 56% +1.8±3.7

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 3.9% · won 66% · −0.8±4.0 vs own baseline
  2. Wide serve (deuce court) → FH down the line used 2.3% · won 61% · −5.8±5.3 vs own baseline
  3. T serve (deuce court) → BH crosscourt used 2.4% · won 58% · −8.8±5.3 vs own baseline
  4. Wide serve (ad court) → BH down the line used 2.8% · won 59% · −8.6±4.8 vs own baseline
  5. Wide serve (ad court) → BH crosscourt used 2.7% · won 58% · −9.1±5.0 vs own baseline

Return

  1. vs wide serve (deuce court) → FH through the middle, deep used 3.7% · won 53% · +9.8±4.4 vs own baseline
  2. vs wide serve (ad court) → BH crosscourt, mid used 3.0% · won 54% · +10.7±4.9 vs own baseline
  3. vs body serve (deuce court) → BH through the middle, deep used 2.6% · won 55% · +11.4±5.2 vs own baseline
  4. vs T serve (ad court) → FH through the middle, deep used 2.0% · won 56% · +12.6±5.8 vs own baseline
  5. vs body serve (ad court) → BH crosscourt, mid used 2.1% · won 55% · +11.7±5.7 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 1.3% · won 60% · +10.1±7.4 vs own baseline
  2. BH crosscourt → FH crosscourt used 6.1% · won 53% · +3.6±3.9 vs own baseline
  3. BH crosscourt → BH crosscourt used 4.8% · won 54% · +4.0±4.4 vs own baseline
  4. BH through the middle → FH crosscourt used 5.2% · won 53% · +3.7±4.2 vs own baseline
  5. FH crosscourt → FH down the line used 6.0% · won 53% · +3.3±3.9 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Elena Rybakina 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 0.5% · won 65% · +15.6±6.9 vs own baseline · +11.5 vs tour on the same sequence Disrupted by Iga Swiatek (7/10)
  2. BH crosscourt → BH through the middle → FH crosscourt used 1.5% · won 57% · +7.5±4.6 vs own baseline · +4.2 vs tour on the same sequence Disrupted by Anna Blinkova (1/7), Jessica Pegula (3/7)
  3. T serve → BH through the middle return, short → FH crosscourt used 0.2% · won 67% · +17.5±9.9 vs own baseline · +23.5 vs tour on the same sequence
  4. FH crosscourt → FH slice through the middle → FH crosscourt used 0.3% · won 62% · +11.6±8.8 vs own baseline · +5.6 vs tour on the same sequence
  5. BH crosscourt → BH through the middle → FH down the line used 0.2% · won 62% · +11.8±9.4 vs own baseline · +14.7 vs tour on the same sequence
  6. BH through the middle return, deep → FH through the middle → BH crosscourt used 0.2% · won 64% · +14.1±10.5 vs own baseline · +21.8 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 1st serve · ad court+2.71,584
Wide 2nd serve · ad court+2.51,177
Wide 2nd serve · deuce court+2.4331
Wide 1st serve · deuce court+2.31,909
FH to their backhand · serve +1+2.3792

Most exposed to

FH to their forehand · serve +1−2.41,113
FH slice to their forehand · return−1.6183
FH to the middle · serve +1−1.0932
BH to their forehand · rally−0.9758
BH to their backhand · return +1−0.9500

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +2.45, Caroline Wozniacki +2.15, Daria Kasatkina +1.54, Sara Errani +1.46, Angelique Kerber +1.40

Favourable matchups

Sara Errani +2.02, Angelique Kerber +1.52, Elina Avanesyan +1.33, Marie Bouzkova +1.28, Katie Volynets +1.13

Active players who are best at the shot in the top weakness: Barbora Krejcikova, Shelby Rogers, Sara Sorribes Tormo, Jil Teichmann, Maria Sakkari

Tactical fingerprint

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

T serves · deuce50%
Point-ending shots32.6%
Wide serves · ad55%
Deep returns39%
Unforced errors / shot13.0%
Forehand share56%
BH down the line20%
Points at net7%
Serve & volley0%
Wide serves · deuce39%
T serves · ad36%
Drop shots / shot1.2%
Chipped returns6%
Run-around forehands4%
Backhand slice7%
Through the middle26%
1st serve in58%
Avg rally length3.5
FH down the line21%

Plays most like

  1. Anett Kontaveit 2015–2023 plan v
  2. Barbora Krejcikova 2017–2026 plan v
  3. Petra Kvitova 2010–2025 plan v
  4. Rebecca Marino 2018–2024 plan v
  5. Caroline Garcia 2013–2025 plan v
  6. Veronika Kudermetova 2018–2025 plan v
  7. Danielle Collins 2018–2025 plan v
  8. Johanna Konta 2013–2020 plan v

Closest from another era

  1. Jelena Dokic 2000–2009
  2. Lindsay Davenport 1995–2006
  3. Monica Seles 1990–2003

Charted matches