RallyIQ

WTA · Right-handed · 10 charted matches · 2005–2013

Nadia Petrova

Archetype: Forehand line-changer · Backhand line-changer

Against an average opponent

Serve points won 59.6% ±3.3 raw 56.2% · tour 56.3% · 735 points
Return points won 43.3% ±3.4 raw 40.5% · tour 43.7% · 714 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 +0.28 ±0.13 better than 94% of WTA · raw +0.27
Shot selection +0.25 ±0.17 better than 73% of WTA · raw +0.23
Execution −0.08 ±0.50 better than 57% of WTA · raw −0.28
Tactical adaptability +0.02 first serves toward what's working, set to set · 10 matches
Adaptation speed +0.05 same, every two to three service games · per 100 first serves
Points left on the table 2.26 per 100 shots vs best direction · lower than 89% 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 4,093 shots.

Shot expected value

The share of points Nadia Petrova 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 · 288 shots

OptionUsedWin %Tour
BH crosscourt 35% 47.9%±7.5 47.6%
BH through the middle 24% 42.8%±8.7 43.3%
BH down the line 23% 39.9%±8.7 46.8%
BH slice through the middle 9% 30.2%±11.1 34.4%
BH slice crosscourt 7% 46.4%±13.1 40.4%

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

position worth 43% to the average player · 272 shots

OptionUsedWin %Tour
FH crosscourt 39% 42.0%±7.2 46.7%
FH down the line 38% 42.3%±7.3 44.9%
FH through the middle 16% 48.0%±10.4 41.3%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 244 shots

OptionUsedWin %Tour
FH down the line 32% 34.8%±7.9 52.2%
FH crosscourt 21% 49.4%±9.7 52.7%
BH crosscourt 14% 48.5%±11.2 50.9%
BH down the line 11% 51.1%±12.0 50.0%
FH through the middle 8% 44.0%±13.1 45.8%
BH through the middle 6% 55.0%±13.8 46.2%

Long rally, 9+: drive to your forehand side

position worth 44% to the average player · 161 shots

OptionUsedWin %Tour
FH crosscourt 43% 48.2%±8.7 47.0%
FH down the line 34% 38.2%±9.3 46.4%
FH through the middle 13% 49.5%±12.8 41.5%
FH down the line + approach 7% 72.7%±13.2 67.7%

Serve under pressure

Pressure predictability index −1 How much less varied Nadia Petrova's first-serve direction gets on break points. Positive means easier to read. Based on 88 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 34% 38% 62% / 66%
Body 19% 29% ▲ 66% / 57%
T 47% 33% ▼ 71% / 68%

356 normal · 21 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 39% 51% ▲ 62% / 66%
Body 11% 10% 57% / 56%
T 50% 39% ▼ 62% / 64%

283 normal · 67 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
Wide34% 58.7%±6.4 n=130 50% ▲
Body20% 64.8%±7.7 n=74 4% ▼
T46% 57.9%±5.7 n=173 46%

Consistent with an optimal mix (p = 0.34).
Optimal mix: +0.3 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide41% 52.2%±6.2 n=144 37% ▼
Body11% 52.8%±10.0 n=38 0% ▼
T48% 52.8%±5.8 n=168 63% ▲

Consistent with an optimal mix (p = 0.99).
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.32 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: −8.5±4.2 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. (269 repeats, 438 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 46 41% −2.9±9.3
1stAd courtT 91 39% +3.0±7.3
1stAd courtWide 94 36% +1.3±7.1
1stDeuce courtBody 43 37% −5.9±9.3
1stDeuce courtT 67 25% −6.7±7.3
1stDeuce courtWide 125 36% +1.6±6.3
2ndAd courtBody 51 49% −6.3±9.1
2ndAd courtT 27 48% −6.8±10.9
2ndAd courtWide 35 57% +3.5±10.1
2ndDeuce courtBody 54 54% −0.5±8.9
2ndDeuce courtT 17 61% +5.3±11.7
2ndDeuce courtWide 62 51% −2.5±8.6

Signature patterns

Recurring sequences that win more than Nadia Petrova'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 4.5% · won 52% · −8.4±11.4 vs own baseline
  2. T serve (deuce court) → FH crosscourt used 9.5% · won 53% · −7.8±9.2 vs own baseline
  3. T serve (ad court) → BH crosscourt used 4.1% · won 46% · −14.3±11.7 vs own baseline

Return

  1. vs wide serve (deuce court) → FH through the middle, mid used 7.5% · won 46% · +6.4±11.4 vs own baseline
  2. vs wide serve (deuce court) → FH through the middle, deep used 6.8% · won 44% · +4.2±11.7 vs own baseline
  3. vs wide serve (deuce court) → FH down the line, mid used 7.9% · won 37% · −2.0±11.0 vs own baseline
  4. vs T serve (ad court) → FH down the line, mid used 9.9% · won 37% · −2.4±10.3 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → BH down the line used 3.7% · won 49% · +5.5±10.9 vs own baseline
  2. BH down the line → FH crosscourt used 5.6% · won 48% · +4.2±9.7 vs own baseline
  3. BH through the middle → FH crosscourt used 3.9% · won 48% · +3.9±10.7 vs own baseline
  4. BH crosscourt → BH crosscourt used 3.7% · won 46% · +2.0±10.9 vs own baseline
  5. FH down the line → BH through the middle used 3.3% · won 45% · +0.9±11.2 vs own baseline

Discovered sequences

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

  1. FH crosscourt → FH crosscourt → FH through the middle used 0.8% · won 54% · +9.3±12.5 vs own baseline · +23.5 vs tour on the same sequence Disrupted by Maria Sharapova (5/7)
  2. BH down the line → FH crosscourt → FH crosscourt used 1.8% · won 49% · +5.0±10.2 vs own baseline · +4.6 vs tour on the same sequence Disrupted by Maria Sharapova (6/13), Elena Dementieva (4/7)
  3. BH crosscourt → BH crosscourt → BH through the middle used 0.9% · won 50% · +5.8±12.4 vs own baseline · +14.0 vs tour on the same sequence Disrupted by Martina Hingis (3/6), Caroline Wozniacki (5/6)
  4. BH down the line → FH crosscourt → FH down the line used 1.0% · won 48% · +3.7±11.9 vs own baseline · +4.7 vs tour on the same sequence Disrupted by Maria Sharapova (1/6), Elena Dementieva (2/6)
  5. BH crosscourt → BH crosscourt → BH down the line used 1.0% · won 47% · +2.6±12.0 vs own baseline · +1.9 vs tour on the same sequence Disrupted by Elena Dementieva (3/7)
  6. FH crosscourt → FH down the line → BH crosscourt used 1.0% · won 45% · +0.5±11.9 vs own baseline · −4.3 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

T 1st serve · ad court+2.4168
FH to their backhand · return+1.1147
Wide 1st serve · ad court±0.0144
T 1st serve · deuce court±0.0173
FH to their forehand · rally−0.3306

Most exposed to

FH to their forehand · rally−2.8336
FH to the middle · rally−1.9129
FH to their backhand · rally−1.9181
BH to the middle · rally−1.8192
FH to the middle · return−1.4131

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.

FH down the line42%
BH down the line33%
T serves · deuce46%
Points at net12%
T serves · ad48%
Avg rally length4.5
Unforced errors / shot12.0%
Deep returns34%
Chipped returns12%
Backhand slice17%
Serve & volley1%
Wide serves · ad41%
1st serve in62%
Point-ending shots23.4%
Forehand share52%
Run-around forehands3%
Drop shots / shot0.8%
Wide serves · deuce34%
Through the middle18%

Plays most like

  1. Mona Barthel 2012–2021 plan v
  2. Jelena Jankovic 2004–2016 plan v
  3. Vera Zvonareva 2003–2020 plan v
  4. Victoria Azarenka 2009–2025 plan v
  5. Daniela Hantuchova 2002–2015 plan v
  6. Simona Halep 2013–2022 plan v
  7. Kate Makarova 2007–2018 plan v
  8. Elise Mertens 2018–2026 plan v

Closest from another era

  1. Mirra Andreeva 2022–2026
  2. Alina Korneeva 2023–2026
  3. Qinwen Zheng 2022–2026

Charted matches