WTA · Right-handed · 10 charted matches · 2015–2022
Monica Puig
Archetype: Ad-court T server · Rallies through the middle
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 2,467 shots.
Shot expected value
The share of points Monica Puig 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 · 137 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| FH through the middle | 22% | 48.3%±11.6 | 45.8% |
| BH through the middle | 21% | 43.4%±11.6 | 46.2% |
| FH crosscourt | 15% | 55.0%±12.8 | 52.7% |
| BH crosscourt | 14% | 41.5%±13.0 | 50.9% |
| FH down the line | 14% | 47.3%±13.2 | 52.2% |
| BH down the line | 14% | 48.7%±13.2 | 50.0% |
Rally, shots 5–8: drive to your backhand side
position worth 45% to the average player · 128 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| BH crosscourt | 48% | 42.1%±9.0 | 47.6% |
| BH through the middle | 38% | 41.5%±9.8 | 43.3% |
| BH down the line | 13% | 52.3%±13.5 | 46.8% |
Rally, shots 5–8: drive to your forehand side
position worth 43% to the average player · 103 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| FH through the middle | 39% | 42.1%±10.5 | 41.3% |
| FH crosscourt | 32% | 40.3%±11.1 | 46.7% |
| FH down the line | 23% | 40.9%±12.2 | 44.9% |
Return +1: drive to your middle
position worth 50% to the average player · 82 shots
| Option | Used | Win % | Tour |
|---|---|---|---|
| BH through the middle | 34% | 35.9%±11.4 | 46.2% |
| BH crosscourt | 20% | 47.6%±13.7 | 50.8% |
| FH crosscourt | 17% | 60.2%±13.8 | 52.3% |
| FH through the middle | 12% | 51.0%±15.0 | 46.5% |
Serve under pressure
Pressure predictability index ±0 How much less varied Monica Puig's first-serve direction gets on break points. Positive means easier to read. Based on 86 break-point first serves.
Deuce court
| 1st serve | Usage | Break pt | Won when in |
|---|---|---|---|
| Wide | 27% | 29% | 60% / 66% |
| Body | 19% | 24% | 58% / 57% |
| T | 54% | 48% | 60% / 68% |
281 normal · 21 break-point 1st serves
Ad court
| 1st serve | Usage | Break pt | Won when in |
|---|---|---|---|
| Wide | 41% | 35% | 65% / 66% |
| Body | 17% | 15% | 55% / 56% |
| T | 43% | 49% | 59% / 64% |
223 normal · 65 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 | 27% | 53.4%±7.8 n=82 | 42% ▲ |
| Body | 19% | 55.1%±8.7 n=58 | 4% ▼ |
| T | 54% | 50.4%±5.9 n=162 | 54% |
Consistent with an optimal mix (p = 0.65).
Optimal mix: +0.5 per 100 first serves.
Ad court
| 1st serve | Usage | Points won | Optimal |
|---|---|---|---|
| Wide | 40% | 53.0%±6.8 n=114 | 55% ▲ |
| Body | 16% | 52.4%±9.4 n=47 | 1% ▼ |
| T | 44% | 51.1%±6.6 n=127 | 44% |
Consistent with an optimal mix (p = 0.92).
Optimal mix: +0.5 per 100 first serves.
Exploitability 0.50 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: −4.3±7.3 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. (180 repeats, 390 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 | 29 | 43% | −1.2±10.6 | |
| 1st | Ad court | T | 49 | 30% | −5.6±8.5 | |
| 1st | Ad court | Wide | 66 | 26% | −8.1±7.4 | |
| 1st | Deuce court | Body | 41 | 41% | −2.1±9.6 | |
| 1st | Deuce court | T | 58 | 20% | −12.1±7.0 | |
| 1st | Deuce court | Wide | 76 | 31% | −2.7±7.4 | |
| 2nd | Ad court | Body | 50 | 53% | −1.9±9.2 | |
| 2nd | Ad court | T | 23 | 56% | +0.6±11.2 | |
| 2nd | Ad court | Wide | 35 | 63% | +9.6±9.8 | |
| 2nd | Deuce court | Body | 45 | 46% | −8.7±9.5 | |
| 2nd | Deuce court | T | 39 | 49% | −7.0±9.9 | |
| 2nd | Deuce court | Wide | 25 | 44% | −9.9±11.0 |
Signature patterns
Recurring sequences that win more than Monica Puig's own baseline, ranked by edge weighted by how often they're used.
Serve → +1
- Not enough data
Return
- Not enough data
Rally, consecutive own shots
- BH through the middle → FH through the middle used 6.5% · won 46% · +3.1±11.5 vs own baseline
- BH through the middle → BH through the middle used 5.9% · won 46% · +2.9±11.7 vs own baseline
- FH through the middle → BH crosscourt used 5.9% · won 44% · +0.9±11.7 vs own baseline
- BH through the middle → BH crosscourt used 8.6% · won 42% · −0.7±10.6 vs own baseline
- BH crosscourt → BH through the middle used 8.3% · won 38% · −5.1±10.5 vs own baseline
Discovered sequences
Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Monica Puig wins the point once the sequence happens, weighted by how often it happens. Think of them as chess openings.
- FH through the middle → FH down the line → BH crosscourt used 1.3% · won 49% · +6.9±13.0 vs own baseline · +14.4 vs tour on the same sequence
- BH through the middle → FH down the line → BH crosscourt used 1.6% · won 47% · +5.8±12.6 vs own baseline · +9.6 vs tour on the same sequence Disrupted by Nicole Gibbs (5/8)
- BH crosscourt → BH crosscourt → BH through the middle used 2.0% · won 40% · −1.2±11.7 vs own baseline · −4.8 vs tour on the same sequence Disrupted by Danielle Collins (6/10)
- BH crosscourt → BH crosscourt → BH crosscourt used 1.6% · won 36% · −5.8±12.1 vs own baseline · −20.8 vs tour on the same sequence Disrupted by Danielle Collins (1/6)
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 · rally | ±0.0 | 127 |
| T 1st serve · deuce court | −0.4 | 143 |
| BH to their backhand · rally | −1.9 | 147 |
Most exposed to
| FH to their backhand · rally | −1.4 | 127 |
Active players who are best at the shot in the top weakness: Clara Burel, Victoria Jimenez Kasintseva, Sara Sorribes Tormo, Arianne Hartono, Angelique Kerber
Tactical fingerprint
Each bar shows how far a style trait is from the WTA average, in standard deviations.
| T serves · deuce | 54% | |
| Through the middle | 36% | |
| Unforced errors / shot | 13.0% | |
| FH down the line | 34% | |
| T serves · ad | 44% | |
| Point-ending shots | 26.4% | |
| Deep returns | 34% | |
| 1st serve in | 62% | |
| Serve & volley | 0% | |
| Wide serves · ad | 40% | |
| Points at net | 6% | |
| Run-around forehands | 4% | |
| Backhand slice | 5% | |
| Chipped returns | 3% | |
| BH down the line | 17% | |
| Avg rally length | 3.7 | |
| Drop shots / shot | 0.3% | |
| Wide serves · deuce | 27% | |
| Forehand share | 47% |
Plays most like
- Maya Joint 2024–2026 plan v
- Garbine Muguruza 2013–2023 plan v
- Veronika Kudermetova 2018–2025 plan v
- Alexandra Eala 2021–2026 plan v
- Heather Watson 2014–2024 plan v
- Kate Makarova 2007–2018 plan v
- Jaqueline Cristian 2021–2026 plan v
- Ashlyn Krueger 2023–2026 plan v
Closest from another era
- Lindsay Davenport 1995–2006
- Monica Seles 1990–2003
- Jennifer Capriati 1990–2002
Charted matches
- Danielle Collins v Monica Puig L Madrid R64 · Clay · 29 Apr 2022
- Karolina Pliskova v Monica Puig L Wimbledon R64 · Grass · 5 Jul 2019
- Xiyu Wang v Monica Puig L Miami R128 · Hard · 20 Mar 2019
- Monica Puig v Danielle Collins L Miami R16 · Hard · 26 Mar 2018
- Monica Puig v Garbine Muguruza L Tokyo R16 · Hard · 20 Sep 2017
- Monica Puig v Saisai Zheng L US Open R128 · Hard · 29 Aug 2016
- Svetlana Kuznetsova v Monica Puig L Sydney F · Hard · 15 Jan 2016
- Monica Puig v Nicole Gibbs W Indian Wells R128 · Hard · 11 Mar 2015
- Monica Puig v Arina Rodionova W Australian Open R128 · Hard · 19 Jan 2015
- Monica Puig v Kaia Kanepi L Hobart International R32 · Hard · 11 Jan 2015