RallyIQ

ATP · Right-handed · 138 charted matches · 2006–2026

Stan Wawrinka

Archetype: Rallies through the middle · Crosscourt backhand

Against an average opponent

Serve points won 67.3% ±2.2 raw 64.8% · tour 63.4% · 12,352 points
Return points won 38.0% ±2.3 raw 34.7% · tour 36.6% · 12,305 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 ±0.05 better than 88% of ATP · raw +0.14
Shot selection −0.72 ±0.08 better than 5% of ATP · raw −0.73
Execution −0.11 ±0.23 better than 63% of ATP · raw −0.26
Tactical adaptability +0.15 first serves toward what's working, set to set · 137 matches
Adaptation speed +0.20 same, every two to three service games · per 100 first serves
Long-rally execution −0.28 ±0.43 shot 9 on v own earlier rally shots · 7,237 shots · better than 39% of ATP
Points left on the table 2.40 per 100 shots vs best direction · lower than 74% of ATP

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 63,388 shots.

Shot expected value

The share of points Stan Wawrinka 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 46% to the average player · 3,942 shots

OptionUsedWin %Tour
BH crosscourt 40% 48.7%±2.1 47.6%
BH slice crosscourt 16% 41.7%±3.2 42.5%
BH through the middle 15% 43.1%±3.3 43.7%
BH down the line 11% 48.7%±3.8 46.4%
BH slice through the middle 7% 37.9%±4.7 35.1%
FH inside-in 3% 58.9%±6.9 54.7%
FH inside-out 3% 53.7%±7.1 51.8%
BH slice down the line 3% 33.7%±7.1 37.1%

Rally, shots 5–8: drive to your middle

position worth 51% to the average player · 3,077 shots

OptionUsedWin %Tour
FH crosscourt 26% 52.9%±2.9 52.7%
FH down the line 17% 49.4%±3.5 51.5%
FH through the middle 16% 48.3%±3.6 47.0%
BH crosscourt 15% 49.5%±3.7 49.1%
BH through the middle 13% 46.6%±4.0 46.8%
BH down the line 5% 46.9%±6.2 48.3%
FH down the line + approach 2% 70.8%±8.6 70.5%
BH slice crosscourt 2% 53.3%±9.7 47.0%

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

position worth 44% to the average player · 2,926 shots

OptionUsedWin %Tour
FH crosscourt 45% 48.6%±2.2 46.6%
FH through the middle 24% 42.7%±3.0 41.5%
FH down the line 19% 44.5%±3.4 44.7%
FH slice through the middle 5% 21.4%±5.1 24.5%
FH slice crosscourt 3% 35.2%±7.9 30.9%
FH slice down the line 1% 20.2%±8.5 25.6%
FH down the line + approach 1% 80.1%±8.8 69.3%

Long rally, 9+: drive to your backhand side

position worth 46% to the average player · 2,144 shots

OptionUsedWin %Tour
BH crosscourt 35% 48.7%±3.0 48.0%
BH slice crosscourt 19% 42.8%±4.0 42.1%
BH through the middle 15% 45.0%±4.5 43.8%
BH down the line 15% 46.8%±4.5 46.5%
BH slice through the middle 8% 32.8%±5.5 35.1%
BH slice down the line 3% 34.9%±9.1 35.8%
FH inside-in 2% 52.2%±10.5 54.3%
FH inside-out 2% 47.5%±10.8 52.6%

Serve under pressure

Pressure predictability index −2 How much less varied Stan Wawrinka's first-serve direction gets on break points. Positive means easier to read. Based on 1022 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 45% 58% ▲ 72% / 73%
Body 9% 9% 63% / 63%
T 47% 34% ▼ 77% / 75%

6,170 normal · 262 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 53% 47% 73% / 73%
Body 4% 6% 63% / 63%
T 43% 47% 73% / 72%

5,088 normal · 760 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. No measurable response (−0.05 ± 0.15 points per 100 serves for every 10 points of habitual usage), measured from ATP 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
Wide45% 65.1%±1.4 n=2,905 41% ▼
Body9% 60.1%±3.3 n=560 0% ▼
T46% 65.4%±1.4 n=2,967 59% ▲

Off equilibrium (p = 0.026): serve T more. Gap 0.6 points per 100 first serves.
Optimal mix: +0.6 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide52% 64.9%±1.4 n=3,039 65% ▲
Body4% 63.4%±4.7 n=256 0% ▼
T44% 64.4%±1.6 n=2,553 35% ▼

Consistent with an optimal mix (p = 0.58).
Optimal mix: +0.2 per 100 first serves.

Exploitability 0.40 points per 100 first serves What the optimal mix would win over the current one, both courts. More exploitable than 100% of ATP servers. Tested on matches they weren't fitted on, ATP mixes picked this way win 0.33 per 100 first serves on average.

Repeating the previous direction to the same court: +1.0±1.4 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. (6,001 repeats, 6,005 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 478 34% −2.7±3.5
1stAd courtT 1,420 27% −1.2±1.9
1stAd courtWide 1,748 26% −1.3±1.7
1stDeuce courtBody 531 34% −2.7±3.3
1stDeuce courtT 1,662 25% −0.1±1.7
1stDeuce courtWide 1,772 27% −0.5±1.7
2ndAd courtBody 615 47% −2.0±3.2
2ndAd courtT 337 44% −4.9±4.3
2ndAd courtWide 1,227 47% −1.4±2.3
2ndDeuce courtBody 891 48% −1.2±2.7
2ndDeuce courtT 1,015 49% −1.2±2.5
2ndDeuce courtWide 550 47% −0.8±3.4

Signature patterns

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

Serve → +1

  1. T serve (deuce court) → FH down the line used 2.3% · won 64% · −2.5±4.6 vs own baseline
  2. T serve (ad court) → FH crosscourt used 2.5% · won 59% · −8.0±4.5 vs own baseline
  3. Wide serve (ad court) → FH crosscourt used 2.7% · won 59% · −7.9±4.3 vs own baseline
  4. T serve (deuce court) → FH crosscourt used 3.4% · won 58% · −8.4±3.9 vs own baseline
  5. Wide serve (ad court) → BH crosscourt used 3.3% · won 54% · −12.5±4.0 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, mid used 2.7% · won 50% · +14.0±4.7 vs own baseline
  2. vs wide serve (ad court) → BH slice crosscourt, mid used 2.7% · won 45% · +9.0±4.6 vs own baseline
  3. vs wide serve (deuce court) → FH through the middle, mid used 2.1% · won 39% · +2.6±5.1 vs own baseline
  4. vs T serve (deuce court) → BH slice through the middle, mid used 2.3% · won 38% · +1.8±4.8 vs own baseline
  5. vs T serve (deuce court) → BH slice through the middle used 2.2% · won 17% · −19.0±3.9 vs own baseline

Rally, consecutive own shots

  1. BH crosscourt → FH down the line used 2.0% · won 55% · +8.8±4.6 vs own baseline
  2. BH crosscourt → BH crosscourt used 5.0% · won 51% · +4.3±3.0 vs own baseline
  3. FH crosscourt → FH crosscourt used 4.8% · won 51% · +4.2±3.1 vs own baseline
  4. FH through the middle → BH crosscourt used 2.3% · won 52% · +5.5±4.4 vs own baseline
  5. FH crosscourt → BH down the line used 1.1% · won 53% · +6.6±6.2 vs own baseline

Discovered sequences

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

  1. T serve → BH through the middle return, mid → FH down the line used 0.2% · won 65% · +17.3±8.2 vs own baseline · +18.1 vs tour on the same sequence Disrupted by Roger Federer (9/14), Novak Djokovic (5/6)
  2. FH crosscourt → FH crosscourt → FH down the line + approach used 0.1% · won 70% · +21.9±10.4 vs own baseline · +18.6 vs tour on the same sequence Disrupted by Novak Djokovic (6/6)
  3. Wide serve → BH crosscourt return, short → BH crosscourt used 0.2% · won 60% · +12.1±8.1 vs own baseline · +11.5 vs tour on the same sequence Disrupted by Roger Federer (4/9), Andy Murray (5/7)
  4. T serve → FH through the middle return, mid → FH crosscourt used 0.3% · won 59% · +10.7±7.7 vs own baseline · +6.6 vs tour on the same sequence Disrupted by Andy Murray (4/8), Roger Federer (5/9)
  5. Wide serve → FH through the middle return, mid → BH crosscourt used 0.1% · won 62% · +13.9±9.7 vs own baseline · +18.5 vs tour on the same sequence Disrupted by Andy Murray (3/6), Novak Djokovic (6/9)
  6. T serve → BH through the middle return, mid → FH crosscourt used 0.3% · won 57% · +8.9±7.3 vs own baseline · +4.4 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

FH slice to their forehand · return+3.4400
FH slice to their forehand · rally+2.5169
Body 2nd serve · ad court+1.9506
FH slice to their backhand · return+1.8199
T 2nd serve · deuce court+1.61,159

Most exposed to

FH volley to their backhand · rally−3.6213
FH volley to their forehand · rally−2.6234
Wide 2nd serve · deuce court−1.3550
FH slice to the middle · rally−1.2338
FH slice to their forehand · rally−1.1148

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Rafael Nadal +0.59, Miomir Kecmanovic +0.51, Nishesh Basavareddy +0.33, Casper Ruud +0.28, Roberto Bautista Agut +0.27

Favourable matchups

Miomir Kecmanovic +0.61, Fabian Marozsan +0.45, Roberto Bautista Agut +0.39, Alexander Shevchenko +0.31, Pedro Martinez +0.30

Active players who are best at the shot in the top weakness: Rafael Nadal, Denis Shapovalov, Casper Ruud, Carlos Alcaraz, Novak Djokovic

Tactical fingerprint

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

Chipped returns46%
T serves · ad44%
Unforced errors / shot11.1%
Wide serves · deuce45%
Wide serves · ad52%
Backhand slice24%
Deep returns29%
T serves · deuce46%
Point-ending shots24.7%
Avg rally length4.1
Through the middle24%
BH down the line20%
Forehand share53%
Serve & volley3%
Run-around forehands14%
Points at net8%
Drop shots / shot0.8%
FH down the line27%
1st serve in58%

Plays most like

  1. Roger Federer 1998–2021 plan v
  2. Tommy Haas 1996–2017 plan v
  3. Benjamin Bonzi 2021–2025 plan v
  4. Ivan Ljubicic 2003–2011 plan v
  5. Grigor Dimitrov 2009–2026 plan v
  6. Richard Gasquet 2002–2025 plan v
  7. Fabio Fognini 2012–2025 plan v
  8. Gregoire Barrere 2016–2024 plan v

Closest from another era

  1. Yevgeny Kafelnikov 1994–2002
  2. Ivan Lendl 1979–1994
  3. Magnus Norman 2000–2001

Charted matches