RallyIQ

WTA · Right-handed · 11 charted matches · 2020–2023

Rebecca Peterson

Archetype: Ad-court T server · Rallies through the middle

Against an average opponent

Serve points won 55.9% ±3.5 raw 53.3% · tour 56.3% · 794 points
Return points won 42.6% ±3.5 raw 39.5% · tour 43.7% · 806 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 −0.13 ±0.14 better than 31% of WTA · raw −0.13
Shot selection +0.38 ±0.23 better than 88% of WTA · raw +0.37
Execution −0.31 ±0.83 better than 44% of WTA · raw −0.37
Tactical adaptability +0.03 first serves toward what's working, set to set · 11 matches
Adaptation speed +0.05 same, every two to three service games · per 100 first serves
Points left on the table 2.56 per 100 shots vs best direction · lower than 58% 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 4,387 shots.

Shot expected value

The share of points Rebecca Peterson 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 · 325 shots

OptionUsedWin %Tour
BH crosscourt 36% 42.7%±7.0 47.6%
BH through the middle 33% 43.4%±7.3 43.3%
BH down the line 8% 60.8%±12.0 46.8%
FH inside-out 7% 61.6%±12.2 52.5%
BH slice through the middle 5% 32.1%±12.6 34.4%
BH slice crosscourt 4% 41.4%±13.9 40.4%
FH inside-in 4% 44.5%±14.0 55.6%

Rally, shots 5–8: drive to your middle

position worth 50% to the average player · 304 shots

OptionUsedWin %Tour
FH crosscourt 34% 53.3%±7.4 52.7%
FH through the middle 25% 47.6%±8.3 45.8%
FH down the line 18% 46.6%±9.4 52.2%
BH through the middle 11% 45.7%±11.3 46.2%
BH crosscourt 9% 45.1%±11.9 50.9%

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

position worth 43% to the average player · 258 shots

OptionUsedWin %Tour
FH crosscourt 47% 38.3%±6.7 46.7%
FH through the middle 28% 42.2%±8.4 41.3%
FH down the line 17% 43.7%±10.2 44.9%
FH slice through the middle 5% 27.6%±13.0 29.2%

Serve +1: mid-depth return to your middle

position worth 51% to the average player · 155 shots

OptionUsedWin %Tour
FH through the middle 35% 38.8%±9.3 45.5%
FH crosscourt 28% 49.7%±10.3 54.0%
FH down the line 19% 58.5%±11.6 53.3%
BH through the middle 10% 49.3%±13.9 46.3%
BH crosscourt 8% 48.4%±14.5 52.5%

Serve under pressure

Pressure predictability index +3 How much less varied Rebecca Peterson's first-serve direction gets on break points. Positive means easier to read. Based on 97 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 47% 57% ▲ 58% / 66%
Body 21% 19% 51% / 57%
T 32% 24% 74% / 68%

390 normal · 21 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 33% 24% ▼ 58% / 66%
Body 34% 41% 52% / 56%
T 33% 36% 67% / 64%

307 normal · 76 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
Wide48% 51.0%±5.5 n=197 47%
Body21% 50.8%±7.7 n=85 6% ▼
T31% 62.2%±6.3 n=129 47% ▲

Off equilibrium (p = 0.021): serve T more. Gap 7.7 points per 100 first serves.
Optimal mix: +1.0 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide31% 51.2%±6.7 n=120 31%
Body35% 46.5%±6.4 n=134 20% ▼
T34% 58.3%±6.4 n=129 49% ▲

Consistent with an optimal mix (p = 0.06).
Optimal mix: +1.1 per 100 first serves.

Exploitability 1.05 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: −3.1±5.2 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. (253 repeats, 519 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 48 40% −3.9±9.1
1stAd courtT 74 27% −8.9±7.1
1stAd courtWide 127 34% −0.5±6.2
1stDeuce courtBody 83 41% −1.2±7.6
1stDeuce courtT 67 31% −1.6±7.7
1stDeuce courtWide 101 28% −5.6±6.5
2ndAd courtBody 56 55% +0.2±8.8
2ndAd courtT 23 61% +6.3±11.0
2ndAd courtWide 60 46% −7.9±8.6
2ndDeuce courtBody 59 51% −3.5±8.7
2ndDeuce courtT 34 50% −6.3±10.3
2ndDeuce courtWide 70 59% +5.4±8.1

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → BH crosscourt used 3.5% · won 59% · +3.1±11.3 vs own baseline
  2. Body serve (deuce court) → FH crosscourt used 3.5% · won 59% · +3.1±11.3 vs own baseline
  3. Wide serve (deuce court) → FH down the line used 5.6% · won 58% · +2.0±10.0 vs own baseline
  4. Body serve (ad court) → BH crosscourt used 3.4% · won 55% · −1.6±11.5 vs own baseline
  5. T serve (ad court) → FH crosscourt used 3.5% · won 52% · −4.5±11.5 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, mid used 6.0% · won 48% · +5.3±11.2 vs own baseline
  2. vs wide serve (ad court) → BH through the middle, deep used 6.8% · won 47% · +4.5±10.9 vs own baseline
  3. vs wide serve (ad court) → BH through the middle, mid used 6.5% · won 44% · +1.8±10.9 vs own baseline
  4. vs wide serve (deuce court) → FH crosscourt, mid used 5.5% · won 44% · +1.3±11.4 vs own baseline
  5. vs T serve (ad court) → FH through the middle, mid used 5.0% · won 41% · −0.9±11.6 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 4.0% · won 55% · +7.9±10.4 vs own baseline
  2. BH crosscourt → BH through the middle used 4.7% · won 53% · +6.0±9.9 vs own baseline
  3. FH through the middle → BH through the middle used 2.7% · won 54% · +7.0±11.4 vs own baseline
  4. FH through the middle → FH through the middle used 3.9% · won 53% · +5.5±10.5 vs own baseline
  5. FH crosscourt → FH down the line used 8.8% · won 51% · +3.5±8.0 vs own baseline

Discovered sequences

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

  1. FH down the line → BH through the middle → FH crosscourt used 1.2% · won 54% · +7.7±11.3 vs own baseline · +3.7 vs tour on the same sequence Disrupted by Coco Gauff (3/7), Marta Kostyuk (4/6)
  2. BH crosscourt → BH crosscourt → BH through the middle used 1.6% · won 51% · +4.7±10.2 vs own baseline · +9.9 vs tour on the same sequence Disrupted by Coco Gauff (5/11), Marta Kostyuk (3/6)
  3. FH crosscourt → FH through the middle → FH down the line used 1.0% · won 52% · +6.0±11.7 vs own baseline · +4.7 vs tour on the same sequence Disrupted by Coco Gauff (3/6), Marta Kostyuk (5/7)
  4. FH crosscourt → FH crosscourt → FH down the line used 1.8% · won 50% · +4.0±10.0 vs own baseline · +4.7 vs tour on the same sequence Disrupted by Shelby Rogers (2/6), Marta Kostyuk (4/11)
  5. FH through the middle → FH through the middle → FH down the line used 0.9% · won 50% · +4.0±12.0 vs own baseline · +3.3 vs tour on the same sequence
  6. BH crosscourt → BH through the middle → FH crosscourt used 1.0% · won 49% · +3.0±11.6 vs own baseline · −1.9 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 the middle · return+2.4164
BH to the middle · rally+1.0194
FH to the middle · return+0.8192
T 1st serve · deuce court+0.7129
Wide 1st serve · deuce court+0.4197

Most exposed to

FH to their backhand · serve +1−3.3125
FH to their backhand · rally−2.0241
BH to their backhand · rally−1.7262
Wide 1st serve · ad court−1.6184
FH to their forehand · rally−1.4297

Active players who are best at the shot in the top weakness: Katie Boulter, Linda Fruhvirtova, Sara Errani, Leylah Fernandez, Karolina Muchova

Tactical fingerprint

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

Forehand share62%
Run-around forehands17%
Wide serves · deuce48%
1st serve in66%
Through the middle32%
Avg rally length4.4
Deep returns34%
Unforced errors / shot10.9%
Serve & volley0%
Backhand slice11%
T serves · ad34%
Point-ending shots21.7%
Chipped returns4%
T serves · deuce31%
Points at net4%
Wide serves · ad31%
Drop shots / shot0.4%
FH down the line24%
BH down the line12%

Plays most like

  1. Lucia Bronzetti 2021–2025 plan v
  2. Tamara Zidansek 2019–2026 plan v
  3. Carla Suarez Navarro 2009–2021 plan v
  4. Emma Navarro 2019–2026 plan v
  5. Nao Hibino 2016–2025 plan v
  6. Suzan Lamens 2021–2026 plan v
  7. Tereza Martincova 2015–2022 plan v
  8. Yafan Wang 2019–2025 plan v

Closest from another era

  1. Elena Dementieva 1999–2010
  2. Jennifer Capriati 1990–2002
  3. Anastasia Myskina 2002–2006

Charted matches