RallyIQ

WTA · Right-handed · 237 charted matches · 2018–2026

Iga Swiatek

Archetype: First-strike aggressor · Short-point player

Against an average opponent

Serve points won 63.5% ±2.2 raw 62.5% · tour 56.3% · 14,500 points
Return points won 50.7% ±2.4 raw 48.9% · tour 43.7% · 15,046 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 +0.17 ±0.03 better than 82% of WTA · raw +0.17
Shot selection +0.32 ±0.04 better than 81% of WTA · raw +0.32
Execution +0.91 ±0.19 better than 89% of WTA · raw +0.92
Tactical adaptability −0.06 first serves toward what's working, set to set · 236 matches
Adaptation speed −0.03 same, every two to three service games · per 100 first serves
Points left on the table 2.13 per 100 shots vs best direction · lower than 96% 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 72,304 shots.

Shot expected value

The share of points Iga Swiatek 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 · 4,401 shots

OptionUsedWin %Tour
FH crosscourt 27% 60.8%±2.3 52.7%
FH down the line 22% 58.3%±2.6 52.2%
BH crosscourt 17% 57.5%±3.0 50.9%
FH through the middle 12% 47.6%±3.5 45.8%
BH through the middle 11% 48.5%±3.6 46.2%
BH down the line 8% 58.8%±4.1 50.0%
FH down the line + approach 1% 66.1%±11.2 68.6%
FH crosscourt + approach 0% 65.7%±12.2 69.7%

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

position worth 45% to the average player · 4,020 shots

OptionUsedWin %Tour
BH crosscourt 48% 51.8%±1.9 47.6%
BH through the middle 23% 49.4%±2.7 43.3%
BH down the line 18% 54.0%±3.0 46.8%
BH slice crosscourt 2% 35.8%±8.0 40.4%
BH slice through the middle 2% 29.7%±7.7 34.4%
FH inside-out 1% 56.7%±9.4 52.5%
FH inside-in 1% 61.1%±10.0 55.6%
BH lob through the middle 1% 28.6%±10.1 27.1%

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

position worth 43% to the average player · 3,681 shots

OptionUsedWin %Tour
FH crosscourt 47% 51.9%±2.0 46.7%
FH down the line 23% 52.8%±2.8 44.9%
FH through the middle 21% 46.9%±2.9 41.3%
FH slice through the middle 4% 28.2%±5.7 29.2%
FH slice crosscourt 2% 44.3%±8.7 31.9%
FH slice down the line 1% 19.1%±8.2 24.3%
FH lob through the middle 1% 34.6%±11.9 29.4%
FH down the line + approach 0% 66.9%±12.9 65.4%

Return +1: drive to your middle

position worth 50% to the average player · 2,764 shots

OptionUsedWin %Tour
FH crosscourt 29% 60.9%±2.8 52.3%
FH down the line 18% 58.7%±3.6 53.0%
BH crosscourt 17% 53.0%±3.7 50.8%
FH through the middle 12% 55.5%±4.3 46.5%
BH through the middle 11% 47.3%±4.5 46.2%
BH down the line 10% 56.3%±4.7 50.6%
FH down the line + approach 1% 73.0%±12.5 69.2%
FH crosscourt + approach 0% 68.9%±13.7 66.8%

Serve under pressure

Pressure predictability index −1 How much less varied Iga Swiatek's first-serve direction gets on break points. Positive means easier to read. Based on 1266 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 40% 36% 69% / 66%
Body 27% 31% 64% / 57%
T 32% 33% 73% / 68%

7,254 normal · 314 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 39% 33% 72% / 66%
Body 28% 32% 63% / 56%
T 33% 35% 68% / 64%

5,963 normal · 952 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
Wide40% 64.2%±1.4 n=3,026 55% ▲
Body28% 60.9%±1.7 n=2,083 12% ▼
T32% 63.1%±1.6 n=2,459 33%

Off equilibrium (p = 0.032): serve wide more. Gap 1.3 points per 100 first serves.
Optimal mix: +0.5 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide38% 63.9%±1.5 n=2,609 52% ▲
Body29% 58.2%±1.8 n=1,992 14% ▼
T33% 63.3%±1.6 n=2,314 34%

Off equilibrium (p < 0.001): serve wide more. Gap 1.8 points per 100 first serves.
Optimal mix: +0.8 per 100 first serves.

Exploitability 0.61 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: +1.0±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. (4,919 repeats, 9,090 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 862 49% +5.5±2.8
1stAd courtT 1,833 41% +5.0±1.9
1stAd courtWide 1,721 38% +3.7±1.9
1stDeuce courtBody 949 49% +6.0±2.6
1stDeuce courtT 1,794 39% +6.8±1.9
1stDeuce courtWide 2,078 40% +5.5±1.8
2ndAd courtBody 1,154 60% +5.0±2.3
2ndAd courtT 593 61% +5.9±3.2
2ndAd courtWide 1,062 62% +8.9±2.4
2ndDeuce courtBody 1,326 60% +5.5±2.2
2ndDeuce courtT 934 63% +6.6±2.6
2ndDeuce courtWide 707 58% +4.2±3.0

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 2.7% · won 64% · −1.7±3.9 vs own baseline
  2. T serve (ad court) → FH crosscourt used 2.3% · won 63% · −2.7±4.2 vs own baseline
  3. Wide serve (ad court) → BH down the line used 2.1% · won 60% · −5.2±4.5 vs own baseline
  4. T serve (deuce court) → FH crosscourt used 3.3% · won 61% · −4.3±3.6 vs own baseline
  5. Wide serve (deuce court) → FH down the line used 2.4% · won 59% · −6.2±4.2 vs own baseline

Return

  1. vs wide serve (ad court) → BH crosscourt, mid used 4.0% · won 60% · +11.0±3.4 vs own baseline
  2. vs T serve (ad court) → FH through the middle, deep used 2.4% · won 62% · +13.6±4.2 vs own baseline
  3. vs wide serve (deuce court) → FH crosscourt, mid used 2.7% · won 61% · +11.8±4.0 vs own baseline
  4. vs wide serve (ad court) → BH through the middle, deep used 2.2% · won 60% · +11.2±4.4 vs own baseline
  5. vs wide serve (deuce court) → FH through the middle, deep used 2.6% · won 59% · +9.8±4.1 vs own baseline

Rally, consecutive own shots

  1. FH down the line → FH crosscourt used 2.4% · won 68% · +11.8±4.1 vs own baseline
  2. BH crosscourt → FH crosscourt used 4.4% · won 62% · +5.9±3.1 vs own baseline
  3. FH crosscourt → FH crosscourt used 6.4% · won 60% · +4.7±2.6 vs own baseline
  4. FH down the line → FH down the line used 2.0% · won 64% · +8.3±4.5 vs own baseline
  5. FH crosscourt → FH down the line used 5.6% · won 60% · +4.3±2.8 vs own baseline

Discovered sequences

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

  1. FH crosscourt → FH through the middle → FH down the line used 0.8% · won 65% · +10.6±4.4 vs own baseline · +12.7 vs tour on the same sequence Disrupted by Bianca Andreescu (2/6), Jasmine Paolini (4/10)
  2. FH down the line → BH through the middle → FH crosscourt used 0.5% · won 67% · +12.4±5.4 vs own baseline · +11.9 vs tour on the same sequence Disrupted by Elina Svitolina (4/10), Linda Noskova (5/9)
  3. BH crosscourt → BH through the middle → FH crosscourt used 1.1% · won 63% · +8.3±4.0 vs own baseline · +9.8 vs tour on the same sequence Disrupted by Ekaterina Alexandrova (2/8), Daria Kasatkina (2/6)
  4. FH crosscourt → FH through the middle → FH crosscourt used 0.8% · won 64% · +9.6±4.6 vs own baseline · +10.0 vs tour on the same sequence Disrupted by Anastasija Sevastova (1/6), Jule Niemeier (4/8)
  5. FH down the line → BH slice through the middle → FH down the line used 0.2% · won 73% · +17.8±7.5 vs own baseline · +17.4 vs tour on the same sequence Disrupted by Daria Kasatkina (5/6)
  6. BH crosscourt → BH slice through the middle → FH crosscourt used 0.3% · won 68% · +13.0±7.0 vs own baseline · +11.3 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

Smash to their backhand · rally+5.9164
BH to their forehand · return +1+4.1902
BH to their forehand · serve +1+3.51,032
FH volley to their backhand · rally+3.3188
BH to their forehand · rally+3.02,300

Most exposed to

Wide 2nd serve · ad court−0.81,060
Wide 2nd serve · deuce court−0.4704
FH to the middle · rally−0.42,493
FH slice to the middle · rally−0.4430
Wide 1st serve · deuce court−0.33,142

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +1.83, Caroline Wozniacki +1.48, Daria Kasatkina +0.87, Sara Errani +0.71, Angelique Kerber +0.69

Favourable matchups

Sara Errani +3.22, Angelique Kerber +2.70, Marie Bouzkova +2.58, Elina Avanesyan +2.48, Katie Volynets +2.29

Active players who are best at the shot in the top weakness: Sloane Stephens, Karolina Muchova, Caroline Wozniacki, Ons Jabeur, Magda Linette

Tactical fingerprint

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

Point-ending shots29.0%
BH down the line23%
Deep returns35%
Unforced errors / shot11.3%
1st serve in64%
FH down the line29%
Forehand share54%
Wide serves · deuce40%
Serve & volley0%
Run-around forehands5%
Wide serves · ad38%
Points at net6%
T serves · ad33%
Avg rally length3.9
Chipped returns5%
T serves · deuce32%
Backhand slice5%
Drop shots / shot0.6%
Through the middle23%

Plays most like

  1. Eugenie Bouchard 2013–2023 plan v
  2. Ekaterina Alexandrova 2017–2026 plan v
  3. Shuai Zhang 2009–2026 plan v
  4. Anna Blinkova 2019–2026 plan v
  5. Anastasia Potapova 2017–2026 plan v
  6. Anett Kontaveit 2015–2023 plan v
  7. Sorana Cirstea 2014–2026 plan v
  8. Varvara Gracheva 2021–2026 plan v

Closest from another era

  1. Jelena Dokic 2000–2009
  2. Lindsay Davenport 1995–2006
  3. Elena Dementieva 1999–2010

Charted matches