RallyIQ

WTA · Right-handed · 79 charted matches · 2017–2026

Sofia Kenin

Archetype: First-strike aggressor · Short-point player

Against an average opponent

Serve points won 59.9% ±2.6 raw 57.8% · tour 56.3% · 5,936 points
Return points won 43.8% ±2.7 raw 40.1% · tour 43.7% · 5,694 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 +0.21 ±0.05 better than 86% of WTA · raw +0.20
Shot selection −0.43 ±0.07 better than 14% of WTA · raw −0.44
Execution +0.04 ±0.37 better than 63% of WTA · raw −0.05
Tactical adaptability −0.10 first serves toward what's working, set to set · 76 matches
Adaptation speed +0.02 same, every two to three service games · per 100 first serves
Points left on the table 2.39 per 100 shots vs best direction · lower than 77% 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 27,275 shots.

Shot expected value

The share of points Sofia Kenin 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 · 1,651 shots

OptionUsedWin %Tour
FH crosscourt 28% 56.1%±3.7 52.7%
BH crosscourt 18% 51.3%±4.6 50.9%
FH through the middle 15% 50.2%±5.0 45.8%
BH through the middle 14% 44.9%±5.2 46.2%
FH down the line 9% 49.7%±6.3 52.2%
BH down the line 8% 58.9%±6.7 50.0%
BH drop shot down the line 2% 54.2%±10.8 47.1%
BH slice through the middle 2% 44.2%±11.3 44.8%

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

position worth 43% to the average player · 1,399 shots

OptionUsedWin %Tour
FH crosscourt 45% 52.1%±3.2 46.7%
FH through the middle 24% 42.1%±4.3 41.3%
FH down the line 16% 47.4%±5.2 44.9%
FH slice through the middle 5% 26.7%±7.5 29.2%
FH lob through the middle 3% 33.1%±10.3 29.4%
FH slice crosscourt 2% 31.5%±10.6 31.9%
FH slice down the line 2% 23.7%±9.9 24.3%
FH drop shot down the line 1% 47.4%±14.5 50.9%

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

position worth 45% to the average player · 1,214 shots

OptionUsedWin %Tour
BH crosscourt 47% 47.2%±3.4 47.6%
BH through the middle 22% 44.7%±4.8 43.3%
BH down the line 11% 54.7%±6.5 46.8%
BH slice through the middle 7% 42.5%±7.8 34.4%
BH slice crosscourt 4% 45.8%±9.8 40.4%
BH lob through the middle 2% 22.9%±9.8 27.1%
BH drop shot down the line 2% 43.8%±12.4 49.1%
BH lob crosscourt 2% 39.9%±12.9 32.8%

Serve +1: mid-depth return to your middle

position worth 51% to the average player · 1,078 shots

OptionUsedWin %Tour
FH crosscourt 23% 58.2%±5.0 54.0%
BH crosscourt 21% 56.9%±5.2 52.5%
BH through the middle 18% 52.2%±5.6 46.3%
FH through the middle 17% 51.8%±5.8 45.5%
BH down the line 10% 57.4%±7.1 51.0%
FH down the line 9% 63.4%±7.5 53.3%
BH drop shot down the line 2% 61.5%±12.4 54.1%

Serve under pressure

Pressure predictability index ±0 How much less varied Sofia Kenin's first-serve direction gets on break points. Positive means easier to read. Based on 629 break-point first serves.

Deuce court

1st serveUsageBreak ptWon when in
Wide 47% 46% 67% / 66%
Body 11% 13% 56% / 57%
T 42% 41% 64% / 68%

2,928 normal · 138 break-point 1st serves

Ad court

1st serveUsageBreak ptWon when in
Wide 49% 43% 63% / 66%
Body 10% 9% 53% / 56%
T 42% 47% 65% / 64%

2,361 normal · 491 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
Wide47% 59.5%±2.1 n=1,427 62% ▲
Body11% 55.0%±4.2 n=351 0% ▼
T42% 57.4%±2.2 n=1,288 38% ▼

Consistent with an optimal mix (p = 0.19).
Optimal mix: +0.6 per 100 first serves.

Ad court

1st serveUsagePoints wonOptimal
Wide48% 56.4%±2.2 n=1,358 42% ▼
Body10% 55.9%±4.7 n=272 0% ▼
T43% 59.2%±2.3 n=1,222 58% ▲

Consistent with an optimal mix (p = 0.26).
Optimal mix: +0.6 per 100 first serves.

Exploitability 0.57 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: −1.5±2.4 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. (1,739 repeats, 4,021 switches.)

Return by serve direction

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

ServeCourtDirectionPointsWonvs tour
1stAd courtBody 284 43% −1.2±4.6
1stAd courtT 720 31% −4.2±2.8
1stAd courtWide 667 28% −6.4±2.8
1stDeuce courtBody 358 44% +0.9±4.1
1stDeuce courtT 582 22% −9.6±2.8
1stDeuce courtWide 892 30% −4.1±2.5
2ndAd courtBody 415 58% +3.1±3.8
2ndAd courtT 200 55% +0.4±5.4
2ndAd courtWide 420 54% +0.7±3.9
2ndDeuce courtBody 551 51% −3.1±3.4
2ndDeuce courtT 270 59% +2.9±4.7
2ndDeuce courtWide 315 56% +2.5±4.4

Signature patterns

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

Serve → +1

  1. Wide serve (ad court) → FH crosscourt used 3.7% · won 60% · −1.3±5.2 vs own baseline
  2. Wide serve (deuce court) → BH crosscourt used 2.3% · won 60% · −1.8±6.5 vs own baseline
  3. T serve (ad court) → FH crosscourt used 3.3% · won 60% · −1.8±5.5 vs own baseline
  4. T serve (deuce court) → FH crosscourt used 3.7% · won 59% · −3.0±5.3 vs own baseline
  5. Wide serve (deuce court) → FH down the line used 2.5% · won 57% · −4.3±6.3 vs own baseline

Return

  1. vs wide serve (deuce court) → FH crosscourt, mid used 3.3% · won 60% · +17.3±6.0 vs own baseline
  2. vs wide serve (deuce court) → FH crosscourt, deep used 2.6% · won 61% · +18.4±6.7 vs own baseline
  3. vs body serve (deuce court) → BH crosscourt, mid used 2.2% · won 58% · +16.2±7.2 vs own baseline
  4. vs T serve (ad court) → FH through the middle, deep used 2.6% · won 57% · +14.5±6.7 vs own baseline
  5. vs wide serve (ad court) → BH crosscourt, short used 2.3% · won 56% · +14.0±7.1 vs own baseline

Rally, consecutive own shots

  1. FH crosscourt → FH crosscourt used 7.2% · won 55% · +5.1±4.3 vs own baseline
  2. FH down the line → FH crosscourt used 1.5% · won 60% · +9.5±8.3 vs own baseline
  3. BH crosscourt → BH down the line used 2.9% · won 57% · +6.7±6.5 vs own baseline
  4. FH down the line → BH down the line used 1.4% · won 58% · +8.2±8.5 vs own baseline
  5. FH crosscourt → BH through the middle used 2.2% · won 56% · +6.3±7.2 vs own baseline

Discovered sequences

Mined from every me → opponent → me run of three shots, with no templates. Ranked by how much more often Sofia Kenin 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 crosscourt used 1.0% · won 61% · +11.1±6.4 vs own baseline · +8.1 vs tour on the same sequence Disrupted by Garbine Muguruza (5/11), Elina Svitolina (13/22)
  2. FH down the line → BH through the middle → FH crosscourt used 0.4% · won 67% · +16.8±9.2 vs own baseline · +19.1 vs tour on the same sequence Disrupted by Elina Svitolina (6/8), Yafan Wang (6/6)
  3. FH crosscourt → FH crosscourt → FH crosscourt used 2.2% · won 56% · +5.7±4.6 vs own baseline · +8.1 vs tour on the same sequence Disrupted by Yafan Wang (1/8), Alycia Parks (1/6)
  4. Wide serve → FH through the middle return, mid → BH crosscourt used 0.3% · won 63% · +12.9±9.5 vs own baseline · +14.2 vs tour on the same sequence
  5. Wide serve → BH through the middle return, mid → FH crosscourt used 0.6% · won 59% · +8.9±8.1 vs own baseline · +4.5 vs tour on the same sequence Disrupted by Lauren Davis (3/7)
  6. BH crosscourt → BH through the middle → BH down the line used 0.4% · won 60% · +9.7±9.2 vs own baseline · +14.6 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 · rally+2.3596
FH to their forehand · return+1.7718
BH to their backhand · return +1+1.3517
BH drop shot to their forehand · rally+1.0173
Body 1st serve · deuce court+1.0351

Most exposed to

T 1st serve · ad court−2.21,137
Wide 1st serve · ad court−2.11,158
Wide 1st serve · deuce court−1.91,421
FH to their forehand · return−1.8465
T 1st serve · deuce court−1.81,080

Best-equipped opponents

Active players whose shot mix lines up best against these weaknesses, by structural compatibility per 100 rally shots: Sara Sorribes Tormo +2.53, Caroline Wozniacki +2.32, Daria Kasatkina +1.78, Angelique Kerber +1.77, Maja Chwalinska +1.60

Favourable matchups

Sara Errani +1.51, Angelique Kerber +1.03, Marie Bouzkova +0.93, Elina Avanesyan +0.83, Katie Volynets +0.72

Active players who are best at the shot in the top weakness: Elena Rybakina, Serena Williams, Rebecca Marino, Madison Keys, Karolina Pliskova

Tactical fingerprint

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

Drop shots / shot3.6%
1st serve in67%
Point-ending shots28.3%
Wide serves · deuce47%
Wide serves · ad48%
T serves · deuce42%
T serves · ad43%
Deep returns35%
Unforced errors / shot11.7%
Chipped returns12%
BH down the line21%
Serve & volley0%
Through the middle28%
Backhand slice11%
Forehand share51%
Avg rally length3.7
Run-around forehands2%
Points at net3%
FH down the line21%

Plays most like

  1. Johanna Konta 2013–2020 plan v
  2. Anett Kontaveit 2015–2023 plan v
  3. Clara Tauson 2020–2026 plan v
  4. Su Wei Hsieh 2015–2024 plan v
  5. Anastasija Sevastova 2011–2025 plan v
  6. Antonia Ruzic 2024–2026 plan v
  7. Linda Noskova 2022–2026 plan v
  8. Barbora Krejcikova 2017–2026 plan v

Closest from another era

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

Charted matches