RallyIQ

WTA · Right-handed · 86 charted matches · 2015–2026

Jessica Pegula

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

Against an average opponent

Serve points won 60.5% ±2.5 raw 58.5% · tour 56.3% · 6,140 points
Return points won 46.6% ±2.6 raw 43.9% · tour 43.7% · 6,186 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 ±0.04 better than 25% of WTA · raw −0.16
Shot selection −0.24 ±0.07 better than 26% of WTA · raw −0.26
Execution +0.29 ±0.30 better than 72% of WTA · raw +0.16
Tactical adaptability +0.08 first serves toward what's working, set to set · 86 matches
Adaptation speed +0.08 same, every two to three service games · per 100 first serves
Points left on the table 2.72 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 31,306 shots.

Shot expected value

The share of points Jessica Pegula 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 · 1,839 shots

OptionUsedWin %Tour
FH crosscourt 22% 52.5%±4.0 52.7%
FH through the middle 19% 45.5%±4.3 45.8%
BH through the middle 17% 50.4%±4.5 46.2%
FH down the line 15% 53.6%±4.8 52.2%
BH crosscourt 11% 51.6%±5.5 50.9%
BH down the line 8% 47.3%±6.4 50.0%
BH slice through the middle 1% 44.6%±11.9 44.8%
BH crosscourt + approach 1% 54.5%±12.8 66.7%

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

position worth 45% to the average player · 1,810 shots

OptionUsedWin %Tour
BH crosscourt 37% 52.4%±3.1 47.6%
BH through the middle 27% 48.4%±3.7 43.3%
BH down the line 13% 48.6%±5.1 46.8%
BH slice through the middle 8% 31.3%±5.9 34.4%
BH slice crosscourt 8% 42.9%±6.4 40.4%
BH slice down the line 2% 37.6%±10.1 31.7%
BH drop shot down the line 2% 49.7%±11.4 49.1%
BH lob through the middle 1% 33.6%±12.8 27.1%

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

position worth 43% to the average player · 1,673 shots

OptionUsedWin %Tour
FH crosscourt 43% 50.9%±3.0 46.7%
FH through the middle 26% 39.8%±3.8 41.3%
FH down the line 19% 43.0%±4.4 44.9%
FH slice through the middle 5% 31.4%±7.2 29.2%
FH slice crosscourt 3% 34.8%±9.2 31.9%
FH lob through the middle 1% 25.9%±11.1 29.4%
FH slice down the line 1% 19.2%±10.1 24.3%
FH down the line + approach 1% 56.5%±14.4 65.4%

Return +1: drive to your middle

position worth 50% to the average player · 1,048 shots

OptionUsedWin %Tour
FH crosscourt 21% 56.7%±5.3 52.3%
BH through the middle 18% 50.8%±5.7 46.2%
FH through the middle 17% 46.7%±5.8 46.5%
FH down the line 14% 60.8%±6.2 53.0%
BH crosscourt 13% 50.7%±6.6 50.8%
BH down the line 7% 54.0%±8.6 50.6%
BH slice through the middle 3% 45.5%±11.5 45.9%
BH crosscourt + approach 2% 58.1%±13.5 64.5%

Serve under pressure

Pressure predictability index ±0 How much less varied Jessica Pegula's first-serve direction gets on break points. Positive means easier to read. Based on 656 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 31% 35% 67% / 66%
Body 29% 23% 62% / 57%
T 40% 42% 74% / 68%

3,029 normal · 142 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 29% 31% 66% / 66%
Body 22% 21% 61% / 56%
T 49% 48% 63% / 64%

2,440 normal · 514 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
Wide31% 60.9%±2.5 n=982 46% ▲
Body29% 59.0%±2.6 n=911 14% ▼
T40% 60.0%±2.2 n=1,278 40%

Consistent with an optimal mix (p = 0.68).
Optimal mix: +0.4 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide29% 58.0%±2.7 n=860 44% ▲
Body22% 57.0%±3.1 n=655 7% ▼
T49% 56.4%±2.1 n=1,439 49%

Consistent with an optimal mix (p = 0.71).
Optimal mix: +0.4 per 100 first serves.

Exploitability 0.37 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: −0.8±2.0 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. (2,011 repeats, 3,942 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 363 46% +2.2±4.1
1stAd courtT 661 38% +2.2±3.0
1stAd courtWide 825 36% +1.4±2.7
1stDeuce courtBody 552 45% +2.7±3.4
1stDeuce courtT 653 30% −2.5±2.9
1stDeuce courtWide 750 35% +0.8±2.8
2ndAd courtBody 458 55% ±0.0±3.7
2ndAd courtT 192 57% +2.4±5.5
2ndAd courtWide 468 51% −2.5±3.7
2ndDeuce courtBody 670 55% +0.6±3.1
2ndDeuce courtT 311 56% −0.4±4.4
2ndDeuce courtWide 274 55% +1.2±4.7

Signature patterns

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

Serve → +1

  1. T serve (deuce court) → FH crosscourt used 2.2% · won 62% · +0.8±6.4 vs own baseline
  2. T serve (ad court) → FH down the line used 2.4% · won 56% · −5.3±6.3 vs own baseline
  3. T serve (ad court) → FH crosscourt used 4.2% · won 57% · −4.1±4.9 vs own baseline
  4. Body serve (ad court) → BH crosscourt used 2.2% · won 54% · −7.1±6.5 vs own baseline
  5. Wide serve (deuce court) → FH down the line used 2.1% · won 53% · −8.3±6.7 vs own baseline

Return

  1. vs body serve (deuce court) → FH through the middle, mid used 2.5% · won 58% · +14.1±6.4 vs own baseline
  2. vs wide serve (deuce court) → FH through the middle, deep used 3.0% · won 54% · +10.0±6.0 vs own baseline
  3. vs wide serve (ad court) → BH through the middle, deep used 2.7% · won 54% · +10.3±6.2 vs own baseline
  4. vs body serve (deuce court) → BH through the middle, mid used 3.5% · won 52% · +8.8±5.6 vs own baseline
  5. vs body serve (deuce court) → BH through the middle, deep used 2.1% · won 55% · +11.1±6.8 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 1.4% · won 60% · +11.7±7.6 vs own baseline
  2. BH through the middle → BH down the line used 1.3% · won 58% · +9.6±7.8 vs own baseline
  3. BH crosscourt → BH crosscourt used 3.3% · won 54% · +6.0±5.4 vs own baseline
  4. BH crosscourt → FH crosscourt used 2.8% · won 54% · +5.9±5.9 vs own baseline
  5. FH through the middle → FH crosscourt used 3.5% · won 53% · +5.0±5.3 vs own baseline

Discovered sequences

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

  1. FH through the middle → FH through the middle → FH down the line used 0.4% · won 59% · +10.2±9.1 vs own baseline · +12.9 vs tour on the same sequence
  2. FH down the line → BH crosscourt → BH crosscourt used 0.7% · won 56% · +7.0±7.0 vs own baseline · +9.4 vs tour on the same sequence Disrupted by Iva Jovic (3/6), Iga Swiatek (18/23)
  3. FH through the middle → FH through the middle → FH crosscourt used 0.5% · won 57% · +7.4±8.3 vs own baseline · +7.6 vs tour on the same sequence Disrupted by Iga Swiatek (3/7)
  4. T serve → BH through the middle return, mid → FH crosscourt used 0.2% · won 61% · +12.2±11.2 vs own baseline · +19.7 vs tour on the same sequence
  5. FH down the line → BH through the middle → FH crosscourt used 0.3% · won 59% · +9.5±9.9 vs own baseline · +7.3 vs tour on the same sequence
  6. Body serve → BH down the line return, mid → FH crosscourt used 0.2% · won 61% · +11.4±11.4 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

BH to their forehand · return +1+3.1241
BH to their backhand · return +1+2.9469
Wide 2nd serve · deuce court+2.9238
Body 2nd serve · ad court+2.6472
Wide 2nd serve · ad court+2.4347

Most exposed to

FH slice to the middle · return−1.1171
FH to their forehand · return−0.9687
Body 2nd serve · ad court−0.5458
FH to the middle · return−0.21,141
Wide 2nd serve · deuce court−0.1274

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +1.90, Caroline Wozniacki +1.52, Daria Kasatkina +0.94, Tatjana Maria +0.93, Angelique Kerber +0.81

Favourable matchups

Sara Errani +1.85, Angelique Kerber +1.67, Marie Bouzkova +1.52, Elina Avanesyan +1.31, Katie Volynets +1.19

Active players who are best at the shot in the top weakness: Barbora Krejcikova, Karolina Muchova, Tatjana Maria, Marketa Vondrousova, Daria Kasatkina

Tactical fingerprint

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

T serves · ad49%
Through the middle34%
Deep returns36%
T serves · deuce40%
Drop shots / shot1.8%
Backhand slice19%
Chipped returns12%
Points at net7%
Serve & volley0%
Point-ending shots23.0%
Avg rally length4.0
1st serve in61%
Forehand share53%
BH down the line18%
Unforced errors / shot9.1%
Run-around forehands2%
FH down the line25%
Wide serves · deuce31%
Wide serves · ad29%

Plays most like

  1. Jaqueline Cristian 2021–2026 plan v
  2. R – plan v
  3. Dominika Cibulkova 2009–2019 plan v
  4. Ashlyn Krueger 2023–2026 plan v
  5. Heather Watson 2014–2024 plan v
  6. Elina Svitolina 2013–2026 plan v
  7. Katerina Siniakova 2015–2026 plan v
  8. Alexandra Eala 2021–2026 plan v

Closest from another era

  1. Justine Henin 1999–2010
  2. Elena Dementieva 1999–2010
  3. Anastasia Myskina 2002–2006

Charted matches