WTA · Right-handed · 8 charted matches · 2007–2016
Elena Vesnina
Archetype: First-strike aggressor · Short-point player
Against an average opponent
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
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 2,666 shots.
Shot expected value
The share of points Elena Vesnina 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 · 158 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| FH crosscourt | 25% | 47.6%±10.6 | 52.7% |
| FH down the line | 18% | 49.9%±11.7 | 52.2% |
| BH crosscourt | 16% | 46.1%±12.1 | 50.9% |
| FH through the middle | 15% | 39.9%±12.3 | 45.8% |
| BH through the middle | 13% | 51.8%±12.8 | 46.2% |
| BH down the line | 12% | 46.2%±13.1 | 50.0% |
Rally, shots 5–8: drive to your forehand side
position worth 43% to the average player · 136 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| FH crosscourt | 54% | 53.1%±8.5 | 46.7% |
| FH down the line | 24% | 38.4%±11.1 | 44.9% |
| FH through the middle | 19% | 37.5%±11.7 | 41.3% |
Rally, shots 5–8: drive to your backhand side
position worth 45% to the average player · 94 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| BH crosscourt | 48% | 51.6%±10.2 | 47.6% |
| BH down the line | 30% | 48.6%±11.9 | 46.8% |
| BH through the middle | 22% | 43.1%±12.7 | 43.3% |
Return +1: drive to your middle
position worth 50% to the average player · 92 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| FH crosscourt | 28% | 51.0%±12.1 | 52.3% |
| BH through the middle | 21% | 46.8%±13.1 | 46.2% |
| FH through the middle | 17% | 50.9%±13.7 | 46.5% |
| BH crosscourt | 17% | 53.2%±13.7 | 50.8% |
Serve under pressure
Pressure predictability index +4 How much less varied Elena Vesnina's first-serve direction gets on break points. Positive means easier to read. Based on 75 break-point first serves.
Deuce court
| 1st serve | Usage | Break pt | Won when in |
|---|---|---|---|
| Wide | 40% | 40% | 60% / 66% |
| Body | 22% | 15% | 52% / 57% |
| T | 38% | 45% | 64% / 68% |
260 normal · 20 break-point 1st serves
Ad court
| 1st serve | Usage | Break pt | Won when in |
|---|---|---|---|
| Wide | 47% | 51% | 61% / 66% |
| Body | 30% | 18% ▼ | 50% / 56% |
| T | 23% | 31% | 58% / 64% |
202 normal · 55 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 serve | Usage | Points won | Optimal |
|---|---|---|---|
| Wide | 40% | 53.9%±6.9 n=112 | 46% ▲ |
| Body | 22% | 46.1%±8.6 n=61 | 7% ▼ |
| T | 38% | 55.3%±7.0 n=107 | 47% ▲ |
Consistent with an optimal mix (p = 0.21).
Optimal mix: +0.7 per 100 first serves.
Ad court
| 1st serve | Usage | Points won | Optimal |
|---|---|---|---|
| Wide | 48% | 44.4%±6.6 n=123 | 48% |
| Body | 27% | 41.5%±8.1 n=70 | 12% ▼ |
| T | 25% | 48.8%±8.5 n=64 | 40% ▲ |
Consistent with an optimal mix (p = 0.42).
Optimal mix: +0.7 per 100 first serves.
Exploitability 0.69 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: +4.7±6.6 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. (170 repeats, 351 switches.)
Return by serve direction
Return points won against each serve direction, compared with the tour average.
| Serve | Court | Direction | Points | Won | vs tour | |
|---|---|---|---|---|---|---|
| 1st | Ad court | Body | 32 | 45% | +1.5±10.4 | |
| 1st | Ad court | T | 59 | 33% | −2.2±8.2 | |
| 1st | Ad court | Wide | 72 | 35% | +0.2±7.8 | |
| 1st | Deuce court | Body | 34 | 45% | +2.4±10.2 | |
| 1st | Deuce court | T | 67 | 25% | −6.7±7.3 | |
| 1st | Deuce court | Wide | 79 | 37% | +2.9±7.6 | |
| 2nd | Ad court | Body | 36 | 61% | +6.3±9.9 | |
| 2nd | Ad court | T | 18 | 51% | −4.0±11.9 | |
| 2nd | Ad court | Wide | 47 | 48% | −5.4±9.4 | |
| 2nd | Deuce court | Body | 55 | 58% | +3.6±8.8 | |
| 2nd | Deuce court | T | 36 | 53% | −3.3±10.1 | |
| 2nd | Deuce court | Wide | 14 | 43% | −10.3±12.3 |
Signature patterns
Recurring sequences that win more than Elena Vesnina's own baseline, ranked by edge weighted by how often they're used.
Serve → +1
- Wide serve (ad court) → BH crosscourt used 6.6% · won 53% · +1.6±11.8 vs own baseline
- T serve (deuce court) → BH crosscourt used 6.6% · won 49% · −2.4±11.8 vs own baseline
- Body serve (deuce court) → BH crosscourt used 6.6% · won 47% · −4.4±11.8 vs own baseline
- Body serve (ad court) → BH crosscourt used 6.6% · won 43% · −8.4±11.7 vs own baseline
Return
- vs wide serve (ad court) → BH crosscourt, mid used 15.3% · won 58% · +2.6±11.6 vs own baseline
Rally, consecutive own shots
- BH crosscourt → FH crosscourt used 6.9% · won 56% · +6.0±11.7 vs own baseline
- BH crosscourt → BH down the line used 8.0% · won 53% · +2.8±11.4 vs own baseline
- FH crosscourt → FH down the line used 8.0% · won 51% · +0.9±11.4 vs own baseline
- FH crosscourt → BH crosscourt used 9.4% · won 49% · −0.9±10.9 vs own baseline
- FH crosscourt → FH crosscourt used 11.1% · won 48% · −1.6±10.3 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 Vesnina wins the point once the sequence happens, weighted by how often it happens. Think of them as chess openings.
- BH crosscourt → BH slice crosscourt → BH crosscourt used 1.1% · won 52% · +4.8±13.0 vs own baseline · +7.3 vs tour on the same sequence Disrupted by Roberta Vinci (9/14)
- FH crosscourt → FH down the line → BH crosscourt used 1.5% · won 49% · +1.2±12.3 vs own baseline · +0.2 vs tour on the same sequence
- FH crosscourt → FH crosscourt → FH crosscourt used 2.7% · won 48% · +0.7±10.6 vs own baseline · +0.3 vs tour on the same sequence Disrupted by Roberta Vinci (1/6), Victoria Azarenka (3/7)
- FH crosscourt → FH crosscourt → FH down the line used 1.5% · won 47% · ±0.0±12.4 vs own baseline · −0.3 vs tour on the same sequence Disrupted by Roberta Vinci (5/8)
- BH crosscourt → BH crosscourt → BH down the line used 1.3% · won 47% · −0.1±12.7 vs own baseline · −1.0 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 forehand · rally | +2.4 | 168 |
| Wide 1st serve · ad court | −0.2 | 123 |
| BH to their backhand · rally | −1.5 | 149 |
Most exposed to
| FH to their forehand · rally | −3.2 | 160 |
| Wide 1st serve · deuce court | −2.1 | 124 |
| T 1st serve · deuce court | −1.0 | 120 |
| Wide 1st serve · ad court | −0.4 | 122 |
Active players who are best at the shot in the top weakness: Linda Fruhvirtova, Maja Chwalinska, Sara Sorribes Tormo, Linda Klimovicova, Nadia Podoroska
Tactical fingerprint
Each bar shows how far a style trait is from the WTA average, in standard deviations.
| Wide serves · ad | 48% | |
| Points at net | 10% | |
| Point-ending shots | 26.5% | |
| BH down the line | 22% | |
| Drop shots / shot | 1.8% | |
| 1st serve in | 64% | |
| Unforced errors / shot | 11.1% | |
| T serves · deuce | 38% | |
| Chipped returns | 11% | |
| Wide serves · deuce | 40% | |
| Serve & volley | 0% | |
| Deep returns | 32% | |
| Backhand slice | 11% | |
| Avg rally length | 3.9 | |
| Run-around forehands | 2% | |
| Through the middle | 25% | |
| FH down the line | 25% | |
| T serves · ad | 25% | |
| Forehand share | 48% |
Plays most like
- Anhelina Kalinina 2019–2025 plan v
- Su Wei Hsieh 2015–2024 plan v
- Anett Kontaveit 2015–2023 plan v
- Sorana Cirstea 2014–2026 plan v
- Magda Linette 2016–2026 plan v
- Olivia Gadecki 2023–2026 plan v
- Iga Swiatek 2018–2026 plan v
- Veronika Kudermetova 2018–2025 plan v
Closest from another era
- Monica Seles 1990–2003
- Jennifer Capriati 1990–2002
- Arantxa Sanchez Vicario 1988–2001
Charted matches
- Elena Vesnina v Serena Williams L Wimbledon SF · Grass · 7 Jul 2016
- Elena Vesnina v Belinda Bencic W Charleston R32 · Clay · 6 Apr 2016
- Lin Zhu v Elena Vesnina L Australian Open Q1 · Hard · 13 Jan 2016
- Elena Vesnina v Victoria Azarenka L Brisbane R32 · Hard · 4 Jan 2016
- Roberta Vinci v Elena Vesnina L Rome R64 · Clay · 14 May 2013
- Elena Vesnina v Victoria Azarenka L Australian Open R16 · Hard · 20 Jan 2013
- Serena Williams v Elena Vesnina L Madrid R64 · Clay · 7 May 2012
- Justine Henin v Elena Vesnina L Roland Garros R128 · Clay · 27 May 2007