RallyIQ

WTA · Right-handed · 26 charted matches · 2010–2024

Petra Martic

Archetype: Ad-court slider · Avoids the wide serve

Against an average opponent

Serve points won 60.8% ±2.7 raw 57.8% · tour 56.3% · 1,822 points
Return points won 43.2% ±2.8 raw 40.3% · tour 43.7% · 1,844 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 +0.06 ±0.09 better than 64% of WTA · raw +0.04
Shot selection ±0.00 ±0.22 better than 45% of WTA · raw −0.03
Execution +0.40 ±0.47 better than 75% of WTA · raw +0.24
Tactical adaptability −0.07 first serves toward what's working, set to set · 26 matches
Adaptation speed +0.04 same, every two to three service games · per 100 first serves
Points left on the table 2.71 per 100 shots vs best direction · lower than 31% 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 9,914 shots.

Shot expected value

The share of points Petra Martic 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 · 728 shots

OptionUsedWin %Tour
BH crosscourt 29% 48.7%±5.4 47.6%
BH through the middle 18% 39.8%±6.6 43.3%
BH slice crosscourt 13% 40.1%±7.5 40.4%
BH slice through the middle 11% 35.5%±7.8 34.4%
BH slice down the line 9% 40.2%±8.6 31.7%
BH down the line 9% 45.7%±8.9 46.8%
BH drop shot down the line 3% 43.8%±12.4 49.1%
FH inside-in 2% 54.4%±13.5 55.6%

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

position worth 43% to the average player · 515 shots

OptionUsedWin %Tour
FH crosscourt 44% 40.1%±5.2 46.7%
FH through the middle 27% 38.9%±6.3 41.3%
FH down the line 23% 46.0%±7.0 44.9%
FH slice through the middle 3% 23.9%±11.5 29.2%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 427 shots

OptionUsedWin %Tour
FH crosscourt 23% 55.5%±7.5 52.7%
FH down the line 22% 52.1%±7.7 52.2%
FH through the middle 18% 49.1%±8.4 45.8%
BH through the middle 10% 45.7%±10.2 46.2%
BH crosscourt 9% 46.9%±10.8 50.9%
FH down the line + approach 4% 67.8%±13.0 68.6%
BH slice down the line 3% 46.4%±14.1 43.9%
BH down the line 3% 41.2%±13.9 50.0%

Long rally, 9+: drive to your backhand side

position worth 44% to the average player · 374 shots

OptionUsedWin %Tour
BH crosscourt 26% 40.3%±7.4 47.9%
BH slice crosscourt 19% 38.6%±8.4 38.7%
BH through the middle 16% 41.2%±9.1 42.7%
BH slice through the middle 16% 37.6%±9.0 33.4%
BH slice down the line 9% 38.1%±11.1 34.0%
BH down the line 7% 43.0%±12.1 46.7%
BH drop shot down the line 5% 46.9%±13.0 48.7%

Serve under pressure

Pressure predictability index +3 How much less varied Petra Martic's first-serve direction gets on break points. Positive means easier to read. Based on 203 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 50% 44% 65% / 66%
Body 14% 22% ▲ 57% / 57%
T 36% 34% 72% / 68%

896 normal · 50 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 49% 50% 68% / 66%
Body 20% 12% 58% / 56%
T 31% 37% 60% / 64%

719 normal · 153 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% 58.0%±3.6 n=470 49%
Body14% 51.1%±6.4 n=135 0% ▼
T36% 63.3%±4.1 n=341 51% ▲

Off equilibrium (p = 0.013): serve T more. Gap 4.4 points per 100 first serves.
Optimal mix: +1.1 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide50% 58.7%±3.8 n=432 65% ▲
Body19% 52.3%±5.9 n=163 4% ▼
T32% 57.5%±4.6 n=277 31%

Consistent with an optimal mix (p = 0.23).
Optimal mix: +0.7 per 100 first serves.

Exploitability 0.89 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: −1.1±5.3 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. (597 repeats, 1,169 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 139 41% −3.0±6.2
1stAd courtT 188 31% −5.0±5.1
1stAd courtWide 260 36% +1.5±4.6
1stDeuce courtBody 151 41% −1.3±6.0
1stDeuce courtT 231 33% +0.7±4.8
1stDeuce courtWide 260 28% −6.0±4.3
2ndAd courtBody 116 52% −2.6±6.8
2ndAd courtT 54 57% +1.5±8.9
2ndAd courtWide 118 53% −0.8±6.8
2ndDeuce courtBody 130 55% +0.8±6.5
2ndDeuce courtT 116 53% −2.7±6.8
2ndDeuce courtWide 75 54% +0.6±8.0

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → BH crosscourt used 2.4% · won 61% · −0.8±9.9 vs own baseline
  2. Wide serve (ad court) → FH crosscourt used 2.9% · won 59% · −2.6±9.5 vs own baseline
  3. T serve (deuce court) → FH crosscourt used 3.2% · won 59% · −3.0±9.2 vs own baseline
  4. Wide serve (deuce court) → FH crosscourt used 3.6% · won 59% · −3.0±8.9 vs own baseline
  5. Wide serve (ad court) → FH through the middle used 2.8% · won 58% · −3.7±9.7 vs own baseline

Return

  1. vs body serve (deuce court) → FH through the middle, mid used 2.5% · won 51% · +10.8±10.7 vs own baseline
  2. vs wide serve (deuce court) → FH crosscourt, mid used 4.5% · won 48% · +8.1±9.0 vs own baseline
  3. vs T serve (deuce court) → BH through the middle, mid used 2.9% · won 49% · +9.1±10.3 vs own baseline
  4. vs wide serve (ad court) → BH crosscourt, short used 2.4% · won 49% · +9.1±10.9 vs own baseline
  5. vs wide serve (ad court) → BH crosscourt, deep used 2.1% · won 48% · +8.1±11.2 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → BH crosscourt used 2.2% · won 51% · +7.3±9.7 vs own baseline
  2. FH crosscourt → BH through the middle used 1.7% · won 50% · +6.6±10.4 vs own baseline
  3. BH crosscourt → FH down the line used 1.2% · won 51% · +7.6±11.3 vs own baseline
  4. BH crosscourt → FH crosscourt used 2.5% · won 48% · +4.7±9.3 vs own baseline
  5. FH down the line → FH crosscourt used 1.9% · won 49% · +5.1±10.1 vs own baseline

Discovered sequences

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

  1. BH crosscourt → BH crosscourt → BH crosscourt used 0.9% · won 61% · +15.5±9.9 vs own baseline · +22.1 vs tour on the same sequence Disrupted by Caroline Wozniacki (9/12), Magda Linette (7/8)
  2. FH down the line → BH through the middle → FH crosscourt used 0.8% · won 52% · +5.8±10.5 vs own baseline · −1.5 vs tour on the same sequence Disrupted by Paula Badosa (7/11)
  3. FH crosscourt → FH through the middle → FH down the line used 0.4% · won 50% · +4.1±12.6 vs own baseline · +1.9 vs tour on the same sequence
  4. BH crosscourt → BH through the middle → FH down the line used 0.4% · won 50% · +4.1±12.6 vs own baseline · +2.2 vs tour on the same sequence
  5. FH through the middle → FH through the middle → FH through the middle used 0.3% · won 50% · +4.1±12.9 vs own baseline · +10.2 vs tour on the same sequence
  6. FH crosscourt → FH through the middle → FH crosscourt used 0.4% · won 49% · +3.0±12.4 vs own baseline · −2.7 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 slice to their forehand · rally+1.9143
BH slice to the middle · rally+1.8183
Body 2nd serve · ad court+1.6133
FH to their forehand · return+1.6234
FH to their backhand · rally+1.2455

Most exposed to

FH to their forehand · return−3.0132
BH to their forehand · serve +1−2.3128
T 1st serve · ad court−2.1294
BH to their backhand · return +1−1.5188
BH to their backhand · return−1.4335

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 +2.78, Angelique Kerber +2.14, Daria Kasatkina +2.09, Sara Errani +2.00

Favourable matchups

Sara Errani +2.10, Angelique Kerber +2.08, Marie Bouzkova +1.72, Elina Avanesyan +1.65, Linda Fruhvirtova +1.45

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.

Drop shots / shot3.6%
Backhand slice38%
Wide serves · deuce50%
Points at net12%
Wide serves · ad50%
Run-around forehands12%
Avg rally length4.4
Forehand share55%
Serve & volley3%
Chipped returns13%
FH down the line30%
T serves · deuce36%
Through the middle28%
Unforced errors / shot10.2%
Deep returns31%
Point-ending shots22.7%
1st serve in61%
T serves · ad32%
BH down the line16%

Plays most like

  1. Kiki Bertens 2012–2021 plan v
  2. Anastasija Sevastova 2011–2025 plan v
  3. Karolina Muchova 2019–2026 plan v
  4. Bianca Andreescu 2017–2026 plan v
  5. Marta Kostyuk 2018–2026 plan v
  6. Xin Yu Wang 2019–2026 plan v
  7. Kristina Mladenovic 2015–2023 plan v
  8. Svetlana Kuznetsova 2004–2021 plan v

Closest from another era

  1. Lindsay Davenport 1995–2006
  2. Martina Hingis 1996–2007
  3. Conchita Martinez 1993–2003

Charted matches